Publications

Refereed Publications of CAPS

Publication Year

 

2020 .

  1. Burke, A., N. Snook, D.J. Gagne II, S. McCorkle, and A. McGovern, 2020: Calibration of Machine Learning–Based Probabilistic Hail Predictions for Operational Forecasting. Wea. Forecasting, 35, 149-168, https://doi.org/10.1175/WAF-D-19-0105.1
  2. Kong, R., M. Xue, A. O. Fierro, Y. Jung, C. Liu, E. R. Mansell, and D. R. MacGorman, 2020: Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI EnKF for the Analysis and Short Term Forecast of a Mesoscale Convective System. Mon. Wea. Rev., Conditionally accepted
  3. Li, X.-B., Peng, Z.-R., Lu, Q.-C., Wang, D., Hu, X.-M., Wang, D., . . . He, H. (2020): Evaluation of unmanned aerial system in measuring lower tropospheric ozone and fine aerosol particles using portable monitors. Atmospheric Environment, 117134. 10.1016/j.atmosenv.2019.117134.

2019 .

  1. Dahl, N. A., A. Shapiro, C. K. Potvin, A. Theisen, J. G. Gebauer, A. D. Schenkman, and M. Xue, 2019: High-resolution, rapid-scan dual-Doppler retrievals of vertical velocity in simulated supercells. J Atmos Ocean Tech, 36,1477-1500.
  2. Dang, R., Yang, Y., Hu, X.-M., Wang, Z., and Zhang, S. (2019). A Review of Techniques for Diagnosing the Atmospheric Boundary Layer Height (ABLH) Using Aerosol Lidar Data. Remote Sensing, 11(13), 1590. doi:10.3390/rs11131590.
  3. Dang, R.*, Yang, Y., Li, H., HH X-M., Wang, Z., Huang, Z., . . . Zhang, T. (2019) Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro-Pulse Lidar. Remote Sensing, 11(3), 263. doi:10.3390/rs11030263
  4. Dawson, D, II, B. Roberts, M. Xue, 2019: A method to maintain the environmental wind profile in idealized simulations of deep convection with surface friction. Mon. Wea. Rev. doi:10.1175/MWR-D-18-0462.1
  5. Fu, P., K. Zhu, K. Zhao, B. Zhou, and M. Xue, 2019: The role of nocturnal low-level jet in the formation of morning precipitation peak over Dabie Mountains. Adv. Atmos. Sci., 36, 15-28.
  6. Hu, X.-M., M. Xue, F. Kong, and H. Zhang, 2019: Meteorological conditions during an ozone episode in Dallas-Fort Worth, Texas and impact of their model uncertainties on air quality prediction J. Geophy. Res., Accepted.
  7. Hu, X.-M., M. Xue, and X. Li (2019), The Use of High-Resolution Sounding Data to Evaluate and Optimize NonLocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer. Mon. Wea. Rev., doi:10.1175/MWR-D-19-0085.1.
  8. Hu, X.-M., Xue, M., Kong, F., and Zhang, H. (2019), Meteorological Conditions during an Ozone Episode in Dallas-Fort Worth, Texas and Impact of their Modeling Uncertainties on Air Quality Prediction. J. Geophys. Res.-Atmospheres, 124,1941-1961 doi:10.1029/2018JD029791.
  9. Johnson, M., Y. Jung, J. A. Milbrandt, H. Morrison, and M. Xue, 2019: Effects of the representation of rimed ice in bulk microphysics schemes on polarimetric signatures. Mon. Wea. Rev., 147, 3785-3810.
  10. Johnson, M., Y. Jung, J. Milbrandt, H. Morrison, and M. Xue, 2019: Effects of the representation of rimed-ice in bulk microphysics schemes on polarimetric signatures, Mon. Wea. Rev., 147, 3785-3810, doi:10.1175/MWR-D-18-0398.1.
  11. Labriola, J., N. Snook, M. Xue, and K. Thomas, 2019: Analysis of next-day hail forecasts using multi-moment microphysics schemes for the 8 May 2017 severe hail event in Colorado. Mon. Wea. Rev., Conditionally accepted.
  12. Labriola, J., N. Snook, Y. Jung, and M. Xue, 2019: Explicit Ensemble Prediction of Hail in 19 May 2013 Oklahoma City Thunderstorms and Analysis of Hail Growth Pocesses with Several Multi-Moment Microphysics Schemes, Mon. Wea. Rev., 147, 1193-1213, doi:10.1175/MWR-D-18-0266.1.
  13. Labriola, J., N. Snook, M. Xue, and K.W. Thomas, 2019: Forecasting the 8 May 2017 Severe Hail Storm in Denver, Colorado, at a Convection-Allowing Resolution: Understanding Rimed Ice Treatments in Multimoment Microphysics Schemes and Their Effects on Hail Size Forecasts. Mon. Wea. Rev., 147, 3045-3068, doi:10.1175/MWR-D-18-0319.1
  14. Lagerquist, R., A. McGovern, and D.J. Gagne II. (2019) Deep learning for spatially explicit prediction of synoptic-scale fronts. Weather and Forecasting, Number 4, Pages 1137-1160. doi:10.1175/WAF-D-18-0183.1
  15. Li, J., G. Wang, M. A. Mayes, S. D. Allison, S. D. Frey, Z. Shi, X.-M. Hu, Y. Luo, and J. M. Melillo, 2019: Reduced carbon use efficiency and increased microbial turnover with soil warming, Global Change Biol, 25, 900-910.
  16. Li, X., Hu, X.-M., et al. (2019), Spatiotemporal Variations and Regional Transport of Air Pollutants in Two Urban Agglomerations in Northeast China Plain. Chinese Geographical Science, 20(6), 917-933. doi:10.1007/s11769-019-1081-8
  17. Li, X., Hu, X.-M., et al. (2019) Impact of planetary boundary layer structure on the formation and evolution of air-pollution episodes in Shenyang, Northeast China. Atmos. Environ., 116850 doi:10.1016/j.atmosenv.2019.116850
  18. Li, J., G. Wang, M. A. Mayes, S. D. Allison, S. D. Frey, Z. Shi, X.-M. Hu, Y. Luo, and J. M. Melillo (2018), Reduced carbon use efficiency and increased microbial turnover with soil warming, Global Change Biol, doi:10.1111/gcb.14517.
  19. Liu, C., M. Xue, and R. Kong, 2019: Direct variational assimilation of radar reflectivity and radial velocity data: Issues with nonlinear reflectivity operator and solutions. Mon. Wea Rev., 137,17-29
  20. Liu, C., E. Fedorovich, J. Huang, X.-M. Hu, Y. Wang, X. Lee, 2019: Impact of aerosol shortwave radiative heating on the entrainment in atmospheric convective boundary layer: a large-eddy simulation study, J. Atmos. Sci., 76, 785-799. doi:10.1175/JAS-D-18-0107.1
  21. Liu, C., M. Xue, and R. Kong, 2019: Direct assimilation of radar reflectivity data using 3DVAR: Treatment of hydrometeor background errors and OSSE tests. Mon. Wea. Rev., 137, 17-29.
  22. Loken, E. D., A. J. Clark, M. Xue, and F. Kong, 2019: Spread and skill in mixed- and single-physics convection-allowing ensembles. Wea. Forecasting, 34, 305-330.
  23. Mahale, V. N., G. Zhang, M. Xue, J. Gao, and H. D. Reeves, 2019: Variational retrieval of rain microphysics and related parameters from polarimetric radar data with a parameterized operator. J. Atmos. Oceanic Technol., 36, 2483-2500.
  24. McGovern, A., D.J. Gagne II, R. Lagerquist, K. Elmore, and G.E. Jergensen, 2019: Making the black box more transparent: Understanding the physical implications of machine learning. Bulletin of the American Meteorological Society, Volume 100, Number 11, Pages 2175-2199.
  25. McGovern, A., C. Karstens, T. Smith, and R. Lagerquist, (2019) Quasi-Operational Testing of Real-time Storm-longevity Prediction via Machine Learning. Weather and Forecasting, Volume 34, Number 5, Pages 1437-1451.
  26. Moss, R.H.; Avery, S.; Baja, K.; Burkett, M.; Chischilly, A.M.; Dell, J.; Fleming, P.A.,; Geil, K.; Jacobs, K.; Jones, A.; Knowlton, K.; Koh, J.; Melillo, J.; Pandya, R.; Richmond, T.C.; Scarlett, L.; Snyder, J.; Stults, M.; Waple, A.; Whitehead, J.; Zarrilli, D.; Ayyub, B.; Fox, J.; Ganguly, A.; Joppa, L.; Julius, S.; Kirshen, P.; Kreutter, R.; McGovern, A.; Meyer, R.; Neumann, J.; Solecki, W.; Smith, J.; Tissot, P.; Yohe, G.; Zimmerman, R.,(2019) Evaluating Knowledge to Support Climate Action: A Framework for Sustained Assessment: Report of an Independent Advisory Committee on Applied Climate Assessment. Weather, Climate, and Society. 11:3, pages 465-487.
  27. Oliveira, M. I., M. Xue, B. Roberts, and L. J. Wicker, 2019: Horizontal vortex tubes near tornadoes: three-dimensional structure and dynamics. Atmosphere, 10, 716. doi:10.3390/atmos10110716.
  28. Potvin, C. K., J. R. Carley, A. Clark, L. J. Wicker, P. S. Skinner, A. E. Reinhart, B. T. Gallo, J. S. Kain, G. Romine, E. Aligo, B. A. Brewster, D. C. Dowell, L. M. Harris, I. L. Jirak, F. Kong, T. A. Supinie, K. W. Thomas, X. Wang, Y. Wang, and M. Xue, 2019: Systematic comparison of convection-allowing models during the 2017 NOAA HWT Spring Forecasting Experiment. Wea. Forecasting, 34, 1395-1416.
  29. Putnam, B., M. Xue, Y. Jung, N. Snook, and G. Zhang, 2019: Ensemble Kalman Filter Assimilation of Polarimetric Radar Observations for the 20 May 2013 Oklahoma Tornadic Supercell Case. Mon. Wea. Rev., 147, 2511-2533, doi:10.11754/MWR-D-18-0251.1.
  30. Rao, X., K. Zhao, X. Chen, A. Huang, M. Xue, Q. Zhang, and M. Wang, 2019: Influence of synoptic pattern and low-level wind speed on intensity and diurnal variations of orographic convection in summer over Pearl River Delta, South China. J. Geophy. Res., 124, 657-679.
  31. Snook, N., F. Kong, K. Brewster, M. Xue, B. Albright, S. Perfater, K. Thomas, and T. Supinie, 2019: Evaluation of Convection-Permitting Precipitation Forecast Products using WRF, NMMB, and FV3 for the 2016-2017 NOAA Hydrometeorology Testbed Flash Flood and Intense Rainfall Experiments. Wea. and Forecasting, 34, 781-804, doi:10.1175/WAF-D-18-0155.1
  32. Snook, N., M. Xue, and Y. Jung, 2019: Tornado-Resolving Ensemble and Probabilistic Predictions of the 20 May 2013 Newcastle-Moore EF5 Tornado. Mon. Wea. Rev., 147, 1215-1235. doi:10.1175/MWR-D-18-0236
  33. Stratman, D., N. Yussouf, Y. Jung, T. Supinie, M. Xue, P. Skinner, and B. Putnam, 2019: Optimal Temporal Frequency of Phased-Array Radar Observations for Storm-Scale Data Assimilation, Wea. Forecasting, Accepted.
  34. Sun, Z., M. Xue, K. Zhu, and B. Zhou, 2019: Prediction of a rare EF4 tornado in Funing, China: Resolution dependency of simulated tornadoes. Atmos. Res., 229, 175-189.
  35. Thomas, A., Huff, A., Hu, X.-M., and Zhang F. (2019), Quantiying Uncertainties of Ground-Level Ozone within WRF-Chem Simulations in the Mid-Atlantic Region of the United States as a Response to Variability, J. Adv. Modeling Earth Systems, doi:10.1029/2018MS001457
  36. Wang, Hong, Fanyou Kong, Naiyu Wu, Hongping Lan, 2019: Investigation of microphysical structure of a squall line in South China observed with a polarimetric radar and a disdrometer, Atmospheric Research, Conditionally accepted.
  37. Xu, X., M. A. C. Teixeira, M. Xue, and Y. Wang, 2019: Parameterization of Directional Absorption of Orographic Gravity Waves and Its Impact on the Atmospheric General Circulation Simulated by the Weather Research and Forecasting Model. J. Atmos. Sci., 76, 3435-3453.
  38. Xu, X., M. Xue, M. A. C. Teixeira, J. Tang, and Y. Wang, 2019: Impacts of parameterized directional absorption of orographic gravity waves on the simulated atmospheric general circulation in Weather Research and Forecasting model. J. Atmos. Sci., Conditionally accepted.
  39. Yang, Y., X.-M. Hu, S. Gao, Y. Wang (2019), Sensitivity of WRF Simulations with the YSU PBL Scheme to the Lowest Model Level Height for a Sea Fog Event over the Yellow Sea, Atmospheric Research, 215, 253-267. doi:10.1016/j.atmosres.2018.09.004.
  40. Yao, D., Z. Meng, and M. Xue, 2019: Genesis, maintenance and demise of a simulated tornado and the evolution of its preceding descending reflectivity core (DRC). Atmosphere, 10236; doi:10.3390/atmos10050236.
  41. Zhang, C., M. Xue, T. A. Supinie, F. Kong, N. Snook, K. W. Thomas, K. Brewster, Y. Jung, L. M. Harris, and S.-J. Lin, 2019: How Well Does the FV3 Model Predict Precipitation at a Convection-Allowing Resolution? Results from CAPS Forecasts for the 2018 NOAA Hazardous Weather Testbed with Different Physics Combinations. Geophys. Res. Lett., doi:10.1029/2018GL081702,.
  42. Zhang, G., V. N. Mahale, B. J. Putnam, Y. Qi, Q. Cao, A. D. Bryd, P. Bukovcic, D. S. Zrnic, J. Gao, M. Xue, Y. Jung, H. D. Reeves, P. L. Heinselman, A. Ryzhkov, R. D. Palmer, P. Zhang, M. Weber, G. M. McFarquhar, B. M. III, Y. Zhang, J. Zhang, J. Vivekanandan, Y. Al-Rashid, R. L. Ice, D. S. Berkowitz, C. Tong, C. Fulton, and R. J. Doviak, 2019: Current status and future challenges of weather radar polarimetry: Bridging the gap between radar meteorology/hydrology/engineering and numerical weather prediction. Adv. Atmos. Sci., 36, 571-588. doi:10.1007/s00376-019-8172-4.
  43. Zhang, X.*, J. Huang, ... X.-M. Hu, X. Lee (2019), Improvng lake-breeze simulation with WRF nested LES and lake-model over a large shallow lake, J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-18-0282.1.
  44. Zhang, C., M. Xue, T. Supinie, F. Kong, N. Snook, K. Thomas, K. Brewster, Y. Jung, L. Harris, and S.-J. Lin, 2019: How well does the FV3 model predict precipitation at a convection-allowing resolution? Results from CAPS forecasts for the 2018 NOAA Hazardous Weather Testbed with different physics combinations, Geophys. Res. Letters, 46, 3523-3531, doi:10.1029/2018GL081702.
  45. Zhang, Y., M. Xue, K. Zhu, and B. Zhou, 2019: What is the main cause of diurnal variation and nocturnal peak of summer precipitation in Sichuan Basin, China? The key role of boundary layer low-level jet inertial oscillations. J. Geophy. Res., 124, 2643-2664. doi:10.1029/2018JD029834.
  46. Zhao, K., H. Huang, M. Wang, W.-C. Lee, G. Chen, L. Wen, J. Wen, G. Zhang, M. Xue, Z. Yang, L. Liu, C. Wu, Z. Hu, and S. Chen, 2019: Recent Progress of Dual-Polarization Radar Research and Application in China. Adv. Atmos. Sci., 36, 961-974.
  47. Zhu, K., M. Xue, K. Ouyan, and Y. Jung, 2019: Assimilating Polarimetric Radar Data with an Ensemble Kalman Filter：OSSEs with a Tornadic Supercell Storm Simulated with a Two-Moment Microphysics Scheme, Q. J. RQ. J. Roy. Meteor. Soc., Conditionally accepted.
  48. Zhu, K., M. Xue, Y. Pan, M. H. S. G. Benjamin, S. S. Weygandt, and H. Lin, 2019: The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using GSI-based Ensemble Kalman Filter. Adv. Atmos. Sci., 36, 1308-1326.

2018 .

  1. Bluestein, H. B., G. S. Romine, R. Rotunno, D. W. Reif, and C. C. Weiss, 2018: On the Anomalous Counterclockwise Turning of the Surface Wind with Time in the Plains of the United States. Monthly Weather Review, 146, 467-484.
  2. Chen, X., H. Yuan, and M. Xue, 2018: Spatial spread-skill relationship in terms of agreement scales for precipitation forecasts in a convection-allowing ensemble. Quart. J. Roy. Meteor. Soc., 144,85-98.
  3. Chen, X., Y. Wang, J. Fang, and M. Xue, 2018: A numerical study on rapid intensification of typhoon Vicente (2012) in the South China Sea. Part II: Roles of inner-core processes. J. Atmos. Sci., 75, 235-255.
  4. Chen, X., M. Xue, and J. Fang, 2018: Rapid intensification of typhoon Mujigae (2015) over anomalously warm sea surface of the South China Sea. J. Atmos. Sci., 75, 4313-4335.
  5. Clark, A, I. Jirak, S. Dembek, F. Kong, K. Thomas, K. Knopfmeier, B. Gallo, C. Melick, M. Xue, K. Brewster, Y. Jung, A. Kennedy, X. Dong, J. Markel, G. Romine, K. Fossell, R. Sobash, J. Carley, B. Ferrier, M. Pyle, C. Alexander, S. Weiss, J. Kain, L. Wicker, G. Thompson, D. Imy, G. Creager, 2018: The Community Leveraged Unified Ensemble (CLUE) in the 2016 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment. Bull. Amer. Meteor. Soc. 99, 1433-1448.
  6. Dang, R., Yang, Y., Li, H., Hu, X.-M., Wang, Z., Huang, Z., Zhou, T., Zhang, T. (2019). Atmosphere Boundary Layer Height (ABLH) Determination under Multiple-Layer Conditions Using Micro- Pulse Lidar. Remote Sensing, 11, 263.
  7. Ernst, S., D. LaDue, and A. Gerard, 2018. Understanding emergency manager forecast use in severe weather events. J. Operational Meteorology, 6, 95-105,
  8. Gasperoni, N.A., K.A. Brewster, X. Wang, and F.H. Carr. 2018: Assessing impacts of the high frequency assimilation of surface observations for the forecast of convection initiation on 3 April 2014 within the Dallas-Ft. Worth Testbed., Mon. Wea. Rev., 146, 3845-3872.
  9. Grasso, Lewis, Daniel T. Lindsey, Yoo-Jeong Noh, Christopher O'Dell, Fanyou Kong, 2018: Improvements to cloud top brightness temperatures computed from the CRTM at 3.9 μm. Mon. Wea. Rev., 146, 3927-3944
  10. Griffin, C. B., C. C. Weiss, A. E. Reinhart, J. C. Snyder, H. B. Bluestein, J. Wurman, and K. A. Kosiba, 2018: In Situ and Radar Observations of the Low Reflectivity Ribbon in Supercells during VORTEX2. Monthly Weather Review, 146, 307-327.
  11. Hu, J., Li, Y., Zhao, T., Liu, J., Hu, X.-M., Liu, D., Jiang, Y., J. Xu, Chang, L. (2018), An important mechanism of regional O3 transport for summer smog over the Yangtze River Delta in East China, Atmos. Chem. Phys., 18, 16239-16251.
  12. Hu, X.-M., M. Xue, R. A. McPherson, E. Martin, D. H. Rosendahl, and L. Qiao, 2018: Precipitation dynamical downscaling over the Great Plains. J. Adv. Modeling Earth Systems, 10, 421-447.
  13. Hu, X.-M., Xue, M., Kong, F., & Zhang, H., 2019: Meteorological Conditions during an Ozone Episode in Dallas-Fort Worth, Texas and Impact of their Modeling Uncertainties on Air Quality Prediction. J. Geophys. Res.-Atmospheres , doi:10.1029/2018JD029791
  14. Johnson, M., Y. Jung, D. Dawson, T. A. Supinie, M. Xue, J. Park, and Y.-H. Lee, 2018: Evaluation of Unified Model microphysics in high-resolution NWP simulations using polarimetric radar observations. Adv. Atmos. Sci., 35, 771-784.
  15. Karstens, C. D., J. Correia Jr., D. S. LaDue, J. Wolfe, T. C. Meyer, D. R. Harrison, J. L. Cintineo, K. M. Calhoun, T. M. Smith, A. E. Gerard, and L. P. Rothfusz, 2018: Development of a human- machine mix for forecasting severe convective events. Wea. Forecasting, 33, 715-737,
  16. Kim, D., C.-H. Ho, D.-S. Park, J. Chan, and Y. Jung, 2018: The relationship between tropical cyclone rainfall area and environmental conditions over the subtropical oceans, J. Climate, 31, 4605-4616.
  17. Kong, Fanyou, 2018: A Study of Storm-Scale Ensemble Forecast. Adv. in Meteo. Sci. and Tech. (in Chinese), 8, 53-60.
  18. Kong, R., M. Xue, and C. Liu, 2018: Development of a hybrid en3DVar data assimilation system and comparisons with 3DVar and EnKF for radar data assimilation with observing system simulation experiments. Mon. Wea. Rev., 146, 175-198.
  19. LaDue, D. S., and A. E. Cohen, 2018. Facilitating the self-directed learning efforts of professional meteorologists. Bulletin of the American Meteorological Society, 99, 2519-2527.
  20. LaDue, D. S., R. R. Hoffman, R. Pliske, and P. Daipha, 2019: Expertise in weather forecasting. In P. Ward, J. M. Schraagen, J. Gore, and E. Roth (Eds.), The Oxford Handbook of Expertise: Research and Application, United Kingdom: Oxford University Press.
  21. Li, X.-B., D. Wang, Q.-C. Lu, Z.-R. Peng, Q. Fu, X.-M. Hu, J. Huo, G. Xiu, B. Li, C. Li, D.-S. Wang, H. Wang, 2018:. Three-dimensional analysis of ozone and PM2.5 distributions obtained by observations of tethered balloon and unmanned aerial vehicle in Shanghai, China. Stochastic Environmental Research and Risk Assessment. 32, 1189-1203.
  22. Liu, C., J. Huang, E. Fedorovich, X.-M. Hu, Y. Wang, X. Lee, 2018: The effect of aerosol radiative heating on turbulence statistics and spectra in the atmospheric convective boundary layer: a largeeddy simulation study, Atmosphere, 9, 347, doi:10.3390/atmos9090347.
  23. Luo, L., M. Xue, K. Zhu, and B. Zhou, 2018: Explicit prediction of hail in a long-lasting multi-cellular convective system in Eastern China using multi-moment microphysics schemes. J. Atmos. Sci., 75, 3115-3137.
  24. Luo, X., M. Xue, and J. Fei, 2018: Simulation and Analysis of the Initiation of a Squall Line within a Meiyu Frontal System in East China. Atmosphere, 9, 183; doi:10.3390/atmos9050183.
  25. Meng, Z., L. Bai, M. Zhang, Z. Wu, Z. Li, M. Pu, Y. Zheng, X. Wang, D. Yao, M. Xue, K. Zhao, Z. Li, S. Peng, and L. Li, 2018: The Deadliest Tornado (EF4) in the Past 40 Years in China. Wea. Forecasting, 33, 693-713.
  26. Pan, Y., M. Xue, K. Zhu, and M. Wang, 2018: A prototype regional GSI-based EnKF-variational hybrid data assimilation system for the Rapid Refresh forecasting system: Dual-resolution implementation and testing results. Adv. Atmos. Sci., 35, 518-530.
  27. Wang, Hong, Fanyou Kong, Youngsun Jung, Naigeng Wu, Jinfang Yin, 2018: Quality Control of S-band Polarimetric Radar Measurements for Data Assimilation. J. Appl. Meteor. Sci. (in Chinese), 29, 546-558.
  28. Xu, X., Y. Tang, Y. Wang, and M. Xue, 2018: Directional Absorption of Mountain Waves and Its Influence on the Wave Momentum Transport in the Northern Hemisphere. J. Geophy. Res., 123, 2640-2654.
  29. Xue, M., X. Luo, K. Zhu, Z. Sun, and J. Fei, 2018: The controlling role of boundary layer inertial oscillations in meiyu frontal precipitation and its diurnal cycles over China J. Geophy. Res., 123, 5090-5115.
  30. Zhou, B., M. Xue, and K. Zhu, 2018: A grid-refinement-based approach to modeling the convective boundary layer in the gray zone: Algorithm Implementation and Testing. J. Atmos. Sci. 75, 1143-1161.
  31. Zhu, J., F. Kong, X.-M. Hu, Y. Guo, L. Ran, H. Lei 2018: Impact of Soil Moisture Uncertainty on Summertime Short-range Ensemble Forecasts. Advances in Atmos. Sci., 35,839-852
  32. Zhu, K., M. Xue, B. Zhou, K. Zhao, Z. Sun, P. Fu, Y. Zheng, X. Zhang, and Q. Meng, 2018: Evaluation of real-time precipitation forecasts during 2013-2014 summer seasons over China at a convection-permitting resolution: spatial distribution, propagation, diurnal cycles and skill scores. J. Geophy. Res., 123, 1037-1064.

2017 .

  1. Bluestein, H. B. 2017: Tornadoes and their parent convective storms. Oxford Handbooks Online in Natural Hazard Science (pp. 67). Oxford University Press.
  2. Bluestein, H. B., Wienhoff, Z., Turner, D., Reif, D. W., Thiem, K. J., Houser, J. 2017:. A comparison of the fine-scale structures of a prefrontal wind-shift line and a strong cold front in the Southern Plains of the U. S. Monthly Weather Review, 145, 3307-3330.
  3. Chen, G., Zhao, K., Zhang, G., Huang, H., Liu, S., Wen, L., Yang, Z., Yang, Z., Xu, L., Zhu, W. 2017:. Improving Polarimetric C-Band Radar Rainfall Estimation with Two-Dimensional Video Disdrometer Observations in Eastern China. J. Hydrometeor. 18, 1375-1391.
  4. Duda, J., X. Wang, and M. Xue, 2017: Sensitivity of Convection-Allowing Forecasts to Land-Surface Model Perturbations and Implications for Ensemble Design. Mon. Wea. Rev., 145, 2001-2025.
  5. Fedorovich, E., Gibbs, J. A., Shapiro, A. 2017: Numerical study of nocturnal low-level jets over gently sloping terrain. J. Atmos. Sci., 74, 2813-2834.
  6. Fedorovich, E., Shapiro, A. 2017:. Oscillations in Prandtl slope flow started from rest. Quart. J. Roy. Meteor. Soc., 143, 670-677.
  7. Fulton, C., Salazar-Cerreño, J. L., Zhang, Y., Zhang, G., Kelly, R., Meier, J., McCord, M., Schmidt, D., Byrd, A., Mohan, L., Karimkashi, S., Zrnic, D., Doviak, R., Zahrai, A., Yeary, M., Palmer, R. (2017). Cylindrical Polarimetric Phased Array Radar (CPPAR): Beamforming and Calibration for Weather Applications. IEEE Trans. Geosci. Remote Sensing. 55. 2827 - 2841.
  8. Gagne II, D. J., S. E. Haupt, A. McGovern, and J. K. Williams, 2017: Evaluation of Statistical Learning Configurations for Gridded Solar Irradiance Forecasting. Solar Energy. 150, 383-393.
  9. Gagne, D. J., II, A. McGovern, S. E. Haupt, R. Sobash, J. K. Williams, and M. Xue, 2017: Storm-Based Probabilistic Hail Forecasting with Machine Learning Applied to Convection-Allowing Ensembles. Weather Forecasting, 32, 1819-1840.
  10. Gallo, B. T., A. J. Clark, I. Jirak, J. S. Kain, S. J. Weiss, M. Coniglio, K. Knopfmeier, J. C. Jr., C. J. Melick, E. Iyer, A. R. Dean, M. Xue, F. Kong, Y. Jung, F. Shen, K. W. Thomas, K. Brewster, D. Stratman, G. Carbin, W. Line, R. Adams-Selin, and S. Willington, 2017: Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment. Wea. Forecasting, 32, 1541-1568.
  11. Gebauer, J. G., Fedorovich, E., Shapiro, A. 2017: A 1D theoretical analysis of northerly low- level jets over the Great Plains. J. Atmos. Sci., 74, 3419-3431.
  12. Geerts, B., D. Parsons, C. L. Ziegler, T. M. Weckwerth, M. I. Biggerstaff, R. D. Clark, M. C. Coniglio, B. B. Demoz, R. A. Ferrare, W. A. G. Jr., K. Haghi, J. M. Hanesiak, P. M. Klein, K. R. Knupp, K. Kosiba, G. M. McFarquhar, J. A. Moore, A. R. Nehrir, M. D. Parker, J. O. Pinto, R. M. Rauber, R. S. Schumacher, D. D. Turner, Q. Wang, X. Wang, Z. Wang, and J. Wurman, 2017: The 2015 Plains Elevated Convection at Night Field Project. Bull. Amer. Meteor. Soc. 98, 767-786.
  13. Haghi, K. R., Parsons, D. B., Shapiro, A. 2017: Bores observed during IHOP_2002: The relationship of bores to the nocturnal environment. Mon. Wea. Rev., 145, 3929-3946.
  14. Hoffman, R. R., D. S. LaDue, H. M. Mogil, P. J. Roebber, and J. G. Trafton, 2017:. Minding the Weather: How Expert Forecasters Think. MIT Press, 470 pp.
  15. Hu, X.-M., M. Xue, and R. A. McPherson, 2017: The importance of soil type contrast in modulating August precipitation distribution near the Edwards Plateau and Balcones Escarpment in Texas. J. Geophy. Res., 122, 10,711-10,728.
  16. Huang, H., Zhang, G., Zhao, K., Giangrande, S. E. 2017: A Hybrid Method to Estimate Specific Differential Phase and Rainfall With Linear Programming and Physics Constraints. IEEE Trans. Geosci. Remote Sensing, 55, 96-111.
  17. Karstens, C. D., J. Correia Jr., D. S. LaDue, J. Wolfe, T. C. Meyer, D. R. Harrison, J. L. Cintineo, K. M. Calhoun, T. M. Smith, A. E. Gerard, and L. P. Rothfusz, 2018: Development of a human-machine mix for forecasting severe convective events. Wea. Forecasting, Early Online Release,
  18. Labriola, J., N. Snook, Y. Jung, B. Putnam, and M. Xue, 2017: Ensemble hail prediction for the storms of 10 May 2010 in south-central Oklahoma using single- and double-moment microphysical schemes Mon. Wea. Rev., 145, 4911-4936.
  19. LaDue, D. S., R. R. Hoffman, R. Pliske, and P. Daipha, 2018: Expertise in weather forecasting. In P. Ward, J. M. Schraagen, J. Gore, and E. Roth (Eds.), The Oxford Handbook of Expertise: Research and Application. Oxford University Press.
  20. Lagerquist, R., A. McGovern and T. Smith. 2017: Machine Learning for Real-Time Prediction of Damaging Straight-Line Convective Wind. Weather Forecasting, 32, 2175-2193.
  21. Li, H., Y. Yang, X.-M. Hu, Z. Huang, G. Wang, and B. Zhang 2017: Application of Convective Condensation Level Limiter in Convective Boundary Layer Height Retrieval Based on Lidar Data, Atmosphere, 8, 79; doi:10.3390/atmos8040079.
  22. Li, H., Y. Yang, X.-M. Hu, Z. Huang, G. Wang, B. Zhang, and T. Zhang 2017: Evaluation of retrieval methods of daytime convective boundary layer height based on Lidar data, J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD025620.
  23. Loken, E., A. Clark, M. Xue; F. Kong, 2017: Impact of Horizontal Resolution on CAM-Derived Next-Day Probabilistic Severe Weather Forecasts, Wea. Forecasting, 32, 1403-1421.
  24. Luo, L., M. Xue, K. Zhu, and B. Zhou, 2017: Explicit prediction of hail in a hailstorm of 19 March 2014 in eastern China using multi-moment microphysics schemes. J. Geophy. Res., 122 7560-7581.
  25. McGovern, A., C. Potvin, and, R. A. Brown, 2017: Using Large-scale Machine Learning to Improve our Understanding of the Formation of Tornadoes. In Large-Scale Machine Learning in the Earth Sciences.
  26. McGovern, A., K. Elmore, D. J. Gagne II, S. E. Haupt, C. Karstens, R. Lagerquist, T. Smith, and J. K. Williams. Using Artificial Intelligence to Improve Real-time Decision Making for High-Impact Weather, 2017: Bull. Ameri. Meteor. Soc. 98, 2073-2090.
  27. Nemunaitis-Berry, K. L., P. M. Klein, J. B. Basara, and E. Fedorovich, 2017: Sensitivity of Predictions of the Urban Surface Energy Balance and Heat Island to Variations of Urban Canopy Parameters in Simulations with the WRF Model. J. Appl. Meteor. Climatol, 56, 573-595.
  28. Putnam, B. J., M. Xue, Y. Jung, G. Zhang, and F. Kong, 2017: Simulation of polarimetric radar variables from 2013 CAPS spring experiment storm scale ensemble forecasts and evaluation of microphysics schemes. Mon. Wea. Rev., 145, 46-73.
  29. Putnam, B. J., M. Xue, Y. Jung, N. A. Snook, and G. Zhang, 2017: Ensemble probabilistic prediction of a mesoscale convective system and associated polarimetric radar variables using single-moment and double-moment microphysics schemes and EnKF radar data assimilation. Mon. Wea. Rev., 145, 2257-2279.
  30. Reif, D. W. and H. B. Bluestein, 2017: A 20-Year Climatology of Nocturnal Convection Initiation over the Central and Southern Great Plains during the Warm Season. Monthly Weather Review, 145, 1615-1639.
  31. Roberts, B. and M. Xue, 2017: The role of surface drag in mesocyclone intensification leading to tornadogenesis within an idealized supercell simulation. J. Atmos. Sci., 74, 3055-3077.
  32. Saeidi-Manesh, H., Mirmozafari, M., Zhang, G. 2017:. Low cross-polarisation high-isolation frequency scanning aperture coupled microstrip patch antenna array with matched dual-polarisation radiation patterns. Electronics Letters, 53(14), 901-902. 10.1049/el.2017.1282. (Published)
  33. Saeidi-Manesh, H., Zhang, G. 2017: Characterization and Optimization of Cylindrical Polarimetric Array Antenna Patterns for Multi-Mission Applications. PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER, 158, 49-61.
  34. Saeidi-Manesh, H., Zhang, G. 2017: Cross-polarization suppression in cylindrical array antenna. Electronics LETTERS, 53(9), 577-578. 10.1109/LAWP.2017.2684538.
  35. Shen, F., M. Xue, and J. Min, 2017: A comparison of the limited-area 3DVAR and Hybrid ETKF-En3DVAR data assimilation using radar observations at convective-scale for the prediction of Typhoon Saomai (2006) Meteor. Apps., 24, 628-641.
  36. Smith, E., Fedorovich, E., Shapiro, A. 2017: Comparison of analytical descriptions of nocturnal low-level jets within the Ekman model framework. Environ. Fluid Mech., 17, 485-495.
  37. Snyder, J., H. Bluestein, D. Dawson, and Y. Jung, 2017a: Simulations of Polarimetric, X-Band Radar Signatures in Supercells. Part I: Description of Experiment and Simulated ρhv Rings. Appl. Meteor. Climatol., 56, 1977-1999.
  38. Snyder, J., H. Bluestein, D. Dawson, and Y. Jung, 2017b: Simulations of Polarimetric, X-Band Radar Signatures in Supercells. Part II: ZDR Columns and Rings and KDP Columns. Appl. Meteor. Climatol., 56, 2001-2026.
  39. Stratman, D.R. and K.A. Brewster, 2017: Sensitivities of 1-km Forecasts of 24 May 2011 Tornadic Supercells to Microphysics Parameterizations, Mon. Wea. Rev. 147, 2697-2721.
  40. Supinie, T. A., N. Yussouf, J. Cheng, Y. Jung, M. Xue, and S. Wang, 2017: Comparison of the analyses and forecasts of a tornadic supercell storm from assimilating phased array radar and WSR-88D observations Wea. Forecasting, 32, 1379-1401.
  41. Surcel, M., I. Zawadzki, M. K. Yau, M. Xue, and F. Kong, 2017: More on the scale-dependence of the predictability of precipitation patterns: Extension to the 2009-2013 CAPS Spring Experiment ensemble forecasts. Mon. Wea. Rev., 145, 3625-3646.
  42. Trytten, D. and A. M/cGovern, 2017: Moving from Managing Enrollment to Predicting Student Success. Proceedings of the Frontiers in Education.
  43. Wen, L., Zhao, K., Zhang, G., Liu, S., Chen, G. 2017:. Impacts of Instrument Limitations on Estimated Raindrop Size Distribution, Radar Parameters, and Model Microphysics during Mei-Yu Season in East China. J. Atmos. Oceanic Tech., 34, 1021-1037.
  44. Xu, X., J. Song, Y. Wang, and M. Xue, 2017: Quantifying the effect of horizontal propagation of three-dimensional mountain waves on the wave momentum flux using Gaussian beam approximation. J. Atmos. Sci., 74, 1783-1798.
  45. Xu, X., M. Xue, Y. Wang, and H. Huang, 2017: Mechanisms of secondary convection within a meiyu frontal mesoscale convective system in eastern China. J. Geophy. Res., 122, 47-64.
  46. Xu, X., Y. Wang, M. Xue, and K. Zhu, 2017: Impacts of horizontal propagation of orographic gravity waves on the wave drag in the stratosphere and lower mesosphere. J. Geophy. Res., 122, 11,301-11,312.
  47. Zhang, C. and Y. Wang, 2017: Projected Future Changes of Tropical Cyclone Activity over the Western North and South Pacific in a 20-km-Mesh Regional Climate Model. Journal of Climate, 30, 5923-5941.
  48. Zhao, K., M. Wang, M. Xue, P. Fu, Z. Yang, Y. Zhang, W.-C. Lee, F. Zhang, Q. Lin, and Z. Li, 2017: Doppler radar analysis of a tornadic miniature supercell during the Landfall of Typhoon Mujigae (2015) in South China. Bull. Amer. Meteor. Soc., 98, 1821-1831.
  49. Zhou, B., K. Zhu, and M. Xue, 2017: A Physically-based horizontal subgrid-scale turbulent mixing parameterization for the convective boundary layer in mesoscale models. J. Atmos. Sci., 74 2657-2674.
  50. Zhou, B., M. Xue, and K. Zhu, 2017: A Grid-Refinement-Based Approach to Modeling the Convective Boundary Layer in the Gray Zone: A pilot study. J. Atmos. Sci., 74, 3497-3513.

2016 .

  1. Bluestein, H. B., French, M. M., Snyder, J. C., Houser, J. B. 2016: Doppler-radar observations of anticyclonic tornadoes in cyclonically rotating, right-moving supercells. Monthly Weather Review, 144, 1591-1616.
  2. Bodine, D. J., Maruyama, T., Palmer, R. D., Fulton, C. J., Bluestein, H. B. 2016: Sensitivity of tornado dynamics to soil debris. J. Atmos. Sci., 73, 2783-2801.
  3. Bonin, T. A., Newman, J. F., Klein, P. M., Chilson, P. B., Wharton, S. 2016: Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations. Atmospheric Measurement Techniques, 9(12), 5833-5852.
  4. Boroka, L., G. Zhang and D. Zrnic, 2016: Spectral Processing for Step Scanning Phased-Array Radars. IEEE Transactions on Geoscience and Remote Sensing, 54, (8), 4534-4543.
  5. Byrd, A.D., Ivic, I.R., Palmer, R.D., Isom, B.M., Cheong, B.L., Schenkman, A., Xue, M. 2016: A weather radar simulator for the evaluation of polarimetric phased array performance. IEEE Trans. Geosci. Remote Sensing, 54, 4178-4189.
  6. Chen, S., J. J. Gourley, Y. Hong, Q. Cao, N. Carr, P.-E. Kirstetter, J. Zhang, and Z. Flamig, 2016: Using Citizen Science Reports to Evaluate Estimates of Surface Precipitation Type. Bull. Ameri. Meteor. Soc., 97, 187-193.
  7. Dahl, N. and M. Xue  Prediction of the 14 June 2010 Oklahoma City extreme precipitation and flooding event in a multi-physics multi-Initial condition storm scale ensemble forecasting system. Wea. Forecasting, 31, 1215-1246.
  8. Dawson, D.T., II M. Xue, A. Shapiro, and J. Milbrandt, 2016: Sensitivity of Real-Data Simulations of the 3 May 1999 Oklahoma City Tornadic Supercell and Associated Tornadoes to Multi-moment Microphysics. Part II: Analysis of Buoyancy and Dynamic Pressure Forces in Simulated Tornado-Like Vortices. Journal of Atmospheric Sciences, 73,1039-1061.
  9. Derin, Y., E. Anagnostou, A. Berne, M. Borga, B. Boudevillain, W. Buytaert, C.-H. Chang, G. Delrieu, Y. Hong, Y. C. Hsu, W. Lavado-Casimiro, B. Manz, S. Moges, E. I. Nikolopoulos, D. Sahlu, F. Salerno, J.-P. Rodríguez-Sánchez, H. J. Vergara, and K. K. Yilmaz, 2016: Multiregional Satellite Precipitation Products Evaluation over Complex Terrain. J. Hydrometeor., 17, 1817-1836.
  10. Duda, D.J., X. Wang, F, Kong, M. Xue and J. Berner, 2016: Impact of a Stochastic Kinetic Energy Backscatter Scheme on Warm season Convection-Allowing Ensemble Forecasts. Mon. Wea. Rev., 144, 1887-1908.
  11. Golbon- Haghighi, M., G. Zhang, Y. Li and R. Doviak, 2016: Detection of Ground Clutter from Weather Radar Using a Dual-Polarization and Dual-Scan Method. Atmosphere, 7, 83, 12 pp.
  12. Guo, L., Wang, K., Bluestein, H. B. 2016: Variability in tornado occurrence over the Continental U. S. since 1950. Journal of Geophysical Research Atmospheres, 121, 6943-6953.
  13. Hao, Z., F. Hao, Y. Xia, V. P. Singh, Y. Hong, X. Shen, and W. Ouyang, 2016: A Statistical Method for Categorical Drought Prediction Based on NLDAS-2. J. Appl. Meteor. Climatol., 55, 1049-1061.
  14. Hardy, J., J. J. Gourley, P.-E. Kirstetter, Y. Hong, F. Kong, and Z. L. Flamig, 2016: A method for probabilistic flash flood forecasting. J. Hydrol., 541, 480-494.
  15. Houser, J. B., Bluestein, H. B., Snyder, J. C. 2016: A fine-scale radar examination of the tornadic debris signature and a weak reflectivity band associated with a large, violent tornado. Monthly Weather Review, 144, 4101-4130. (Published).
  16. Hu, X.-M. and M. Xue  Influence of synoptic sea breeze fronts on the urban heat island intensity in Dallas-Fort Worth, Texas, Mon. Wea. Rev., 144, 1487-1507.
  17. Hu, X.-M., J. Fuentes, R. Forkel, J. Huang, and N. Zhang, 2016: Editorial Advances in Boundary-Layer/Air Pollution Meteorology, Advances in Meteorology.
  18. Hu, X.-M., X. Li, M. Xue, D. Wu, and J.D. Fuentes, 2016: The formation of barrier winds east of the Loess Plateau and their effects on the dispersion conditions in the North China plains, Bound. Layer Meter, 161, 145-163.
  19. Hu, X.-M., M. Xue, and P. Klein  Analysis of Urban Effects in Oklahoma City using a Dense Surface Observing Network, J. Appl. Meteor. Climatol., 55, 723-741.
  20. Hu, X.-M. and M. Xue 2016: Influence of synoptic sea breeze fronts on the urban heat island intensity in Dallas-Fort Worth, Texas, Mon. Wea. Rev., 144, 1487-1507.
  21. Hu, X.-M., M. Xue, and P. Klein 2016: Analysis of Urban Effects in Oklahoma City using a Dense Surface Observing Network, J. Appl. Meteor. Climatol., 55, 723-741.
  22. Huang, H., G. Zhang, K. Zhao, and S. Giangrande, 2017: A hybrid method to estimate specific differential phase and rainfall with linear programming and physics constraints, IEEE Trans. On Geoscience and Remote Sensing, 55(1), 96-111.
  23. Iyer, E., R., A. Clark, M. Xue, and F. Kong, 2016: A comparison of 36-60 hour precipitation forecasts from convection-allowing and convection-parameterized ensembles, Wea. Forecasting, 31, 347-661.
  24. Johnson, M., Y. Jung, D. Dawson, and M. Xue 2016: Comparison of simulated polarimetric signatures in idealized supercell storms using two-moment bulk microphysics schemes in WRF, Mon. Wea. Rev., 144, 971-996.
  25. Klein, P., X.-M. Hu, A. Shapiro, M. Xue 2016: Linkages between Boundary-Layer Structure and the Development of Nocturnal Low-Level Jets in Central Oklahoma, Boundary Layer Meteor, 158 (3), 383-408.
  26. Liu, C. and M. Xue 2016: Relationships among Four-Dimensional Hybrid Ensemble-Variational Data Assimilation Algorithms with Full and Approximate Ensemble Covariance Localization, Mon. Wea. Rev., 144, 591-606.
  27. Mahale, V., Zhang, G., Xue, M. 2016: Characterization of the 14 June 2011 Norman, Oklahoma Downburst through Dual-Polarization Radar Observations and Hydrometeor Classification. Journal of Applied Meteorology and Climatology, 55(12), 2635-2654.
  28. Matsangouras, I. T., Nastos, P. T., Bluestein, H. B., Papachristopoulou, K., Pytharoulis, I., Miglietta, M. M. 2016: Analysis of waterspout environmental conditions and of parent-storm behavior based on satellite data over the southern Aegean Sea of Greece. International Journal of Climatology. 10.1002/joc.4757. (Published).
  29. Meng, Z., D. Yao, LBai, Y. Zheng, M. Xue, X. Zhang, K. Zhao, F. Tian, and M. Wang, 2016: Wind Estimation around the Shipwreck of Oriental Star based on Field Damage Surveys and Radar Observations, Sci. Cull., 61 330-337.
  30. Newman, J. F., Bonin, T. A., Klein, P. M., Wharton, S., Newsom, R. K. 2016: Testing and validation of multi-lidar scanning strategies for wind energy applications. Wind Energy, 19(12), 2239-2254. 10.1002/we.1978.
  31. Newman, J. F., Klein, P. M., Wharton, S., Sathe, A., Bonin, T. A., Chilson, P. B., Muschinski, A. 2016: Evaluation of three lidar scanning strategies for turbulence measurements. Atmospheric Measurement Techniques, 9(5), 1993-2013.
  32. Pan, Y., M. Xue and G. Ge, 2016: Incorporating diagnosed intercept parameters and the graupel category within the ARPS cloud analysis system for the initialization of double-moment microphysics with the assimilation of reflectivity data and testing with a squall line over south China. Mon. Wea. Rev., 144, 371-392.
  33. Parsons, D. B., Beland, M., Burridge, D., Bougeault, P., Brunet, G., Caughey, J., Cavallo, S., Charron, M., Davies, H. C., Niang, A. D., Ducrocq, V., Gauthier, P., Hamill, T. M., Harr, P. A., Jones, S. C., Langland, R. H., Majumdar, S. J., Mills, B. N., Moncrieff, M., Nakazawa, T., Paccagnella, T., Rabier, F., Redelsperger, J. -L., Saunders, R. W., Shapiro, M. A., Swinbank, R., Szunyogh, I., Thorncroft, C., Thorpe, A. J., Waliser, D., Wernli, H., Toth, Z., 2016: THORPEX Research and the Science of Prediction. Bulletin of the American Meteorological Society. Published online.
  34. Putnam, B. J., Xue, M., Jung, Y., Zhang, G., Kong, F. 2016: Simulation of polarimetric radar variables from 2013 CAPS spring experiment storm scale ensemble forecasts and evaluation of microphysics schemes. Mon. Wea. Rev., 145, 46-73.
  35. Ren, D. and M. Xue, 2016: Retrieval of land surface model state variables through assimilating screen-level atmospheric humidity and potential temperature, Adv. Meteor., doi:10.1007/s10546-016-0159-4.
  36. Roberts, B., M. Xue, A.D. Schenkman, and D.T. Dawson II, 2016: The role of surface friction in tornadogenesis within an idealized supercell simulations, Journal of the Atmospheric Sciences, 73, 3371-3395.
  37. Schenkman, A.D. and M. Xue, 2016: Bow-Echo Mesovortices: A Review. Atmospheric Research, 170, 1-13.
  38. Schenkman, A.D., M. Xue and D. Dawson 2016: The cause of internal surges in a high-resolution simulation of the 8 May 2003 Oklahoma City tornadic supercell. J. Atmos. Sci, 73, 353-370.
  39. Shapiro, A., E. Fedorovich, and S. Rahimi, 2016: A unified theory for the Great Plains nocturnal low-level jet. J. Atmos. Sci., 73, 3037–3057.
  40. Snook, N., Y. Jung, J. Brotzge, B. Putnam and M. Xue, 2016: Prediction and ensemble forecast verfication of hail in the supercell storms of 20 May 2013, Wea. Forecasting, 31, 811-825.
  41. Stanesic, A. and K.A. Brewster, 2016: Impact of radar data assimilation on the numerical simulation of a severe storm in Croatia, Meteorologicische Zeitschrift, 25, 37-53.
  42. Sun, X., Xue, M., Brotzge, J., McPherson, R. A., Hu, X., Yang, X.-Q. 2016: An evaluation of dynamical downscaling of Central Plains summer precipitation using a WRF-based regional climate model at a convection-permitting 4-km resolution. J. Geophys. Res. - Atmospheres, 121, 13801-13826.
  43. Supinie, T., Y. Jung, M. Xue, D. Stensrud, M. French, and H. Bluestein, 2016: Impact of VORTEX2 observations on analyses and forecasts of the 5 June 2009 Goshen County, Wyoming, supercell, Mon. Wea. Rev., 144, 429-449.
  44. Tang, G., Y. Ma, D. Long, L. Zhong, and Y. Hong, 2016: Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales. J. Hydrol., 533, 152-167.
  45. Tang, G., Z. Zeng, D. Long, X. Guo, B. Yong, W. Zhang, and Y. Hong, 2016: Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7? J. Hydrometeor., 17, 121-137.
  46. Thompson, Gregory, Mukul Tewari, Kyoko Ikeda, Sarah Tessendorf, Courtney Weeks, Jason Otkin, and Fanyou Kong, 2016: "Explicitly-Coupled Cloud Physics and Radiation Parameterizations and Subsequent Evaluation in WRF High-Resolution Convective Forecasts". Atmos. Res., 168, 92-104.
  47. Vergara, H., P.-E. Kirstetter, J. J. Gourley, Z. L. Flamig, Y. Hong, A. Arthur, and R. Kolar, 2016: Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States. J. Hydrol., 541, 421-433.
  48. Wakimoto, R. M., Atkins, N. T., Butler, K. M., Bluestein, H. B., Thiem, K., Snyder, J., Houser, J., Wurman, J. 2016: Aerial damage survey of the 2013 El Reno tornado combined with mobile radar data. Monthly Weather Review, 144, 1749-1776. (Published).
  49. Wang, M., M. Xue, and K. Zhao,  The impact of T-TREC-retrieved wind and radial velocity data assimilation using EnKF and effects of assimilation window on the analysis and prediction of Typhoon Jangmi (2008), J. Geophy. Res., 121, 259-277.
  50. Wang, M., Xue, M., Zhao, K. 2016: An investigation on how inner-core structures obtained through radar data assimilation affect track forecasting of typhoon Jangmi (2008) near Taiwan Island. Journal of Geophysical Research: Atmospheres, 121(18), 10,601-10,616.
  51. Wang, M., Zhao, K., Xue, M., Zhang, G., Liu, S., Wen, L., Chen, G. 2016: Precipitation Microphysics Characteristics of a Typhoon Matmo (2014) Rainband after Landfall over Eastern China based on Polarimetric Radar Observations: Microphysics of typhoon rainband. J. Geophy. Res., 121, 12,415-12,433.
  52. Wang, Z., M. Xue, and Z. Tan, 2016: Convective initiation by topgraphically induced convergence forcing over Dabie Mountains on 24 June 2010, Adv. Atmos. Sci., 33, 1120-1136.
  53. Wen, L., K. Zhao, G. Zhang, B. Zhou, S. Liu, X. Chen, and M. Xue, 2016: Statistical characteristics of raindrop size distributions observed in east China during the Asian summer monsoon season from the 2D-video disdrometer and mico-rain radar, J. Geophy. Res.,121, 2265-2282.
  54. Wen, Y., P. Kirstetter, Y. Hong, J. J. Gourley, Q. Cao, J. Zhang, Z. Flamig, and X. Xue, 2016: Evaluation of a Method to Enhance Real-Time, Ground Radar–Based Rainfall Estimates Using Climatological Profiles of Reflectivity from Space. J. Hydrometeor., 17, 761-775
  55. Xue, M., 2016: Preface to the Special Issue on the "Observation Prediction and Analysis of severe Convection of China" (OPACC) National "973" Project, Adv. Atmos. Sci., 33, 1099-1101.
  56. Xue, M., K. Zhao, M.J. Wang, Z. H. Li, Y.G. Zheng, 2016: Recent significant torandoes in China, Adv. Atmos, Sci., 33, 1209-1217.
  57. Yong, B., J. Wang, L. Ren, Y. You, P. Xie, and Y. Hong, 2016: Evaluating Four Multisatellite Precipitation Estimates over the Diaoyu Islands during Typhoon Seasons. J. Hydrometeor., 17, 1623-1641.
  58. Zhang, G., 2016: Weather Radar Polarimetry (book), 322 pages. CRC Press, Boca Raton, Florida.
  59. Zheng, Y., F. Tian, Z. Meng, M. Xue, D. Yao, L. Bai, X. Zhou, X. Mao, M. Wang, 2016: Survey and multi-scale characteristics of wind damage caused by convective storms in the surrounding areas of the capsizing accident of cruise ship "Dong Fang Zhi Xing", Meteorology (in Chinese), 42, 1-13.
  60. Zheng, Y., M. Xue, J. Chen, B. Li, and Z. Tao, 2016: Spatial Characteristics of Extreme Rainfall over China with Hourly through 24-Hour Accumulation Periods Based on National-Level Hourly Rain Gauge Data, Adv. Atmos. Sci, 33, 1218-1232.
  61. Zhu, L. and M. Xue, 2016: Evaluation of WRF-based Convection-Permitting Multi-Physics Ensemble Forecasts over China for the July 21, 201 Beijing Extreme Rainfall Event, Adv. Atmos. Sci, 33, 1240-1258.

 

2015 .

  1. Bokuvcic, P., D.S. Zrnic and G. Zhang, 2015: Convective-Straitform Separation Characterized by Video Disdrometer and Polarimetric Radar Observations - The Bayesian Approach. Atmospheric Research, 155, 176-191 .
  2. Borowska, L., G. Zhang and D.S. Zrnic, 2015: Considerations for Oversampling in Azimuth on the Phased Array Weather. J. Atmos. Oceanic Tech, 32 (9), 1614-1629.
  3. Brotzge, J., and C. Luttrell, 2015: Genesis of the Chickasha, Oklahoma, tornado on 24 May 2011 as observed by CASA radar. J. Operational Meteor.,3 (6) 59-69.
  4. Carlaw, L.B., J.A. Brotzge and F.H. Carr, 2015: Investigating the impacts of assimilating surface observations on high-resolution forecasts on the 15 May 2013 tornado event. Electronic J. Severe Storms Meteor., 10 (2), 1-34.
  5. Chen, S., J. Zhang, E. Mullens, Y. Hang, A. Behrangi, Y. tian, X.-M. Hu, J. Hu, Z. Zhang, 2015: Mapping the Precipitation Type Distribution over the Contiguous United States Using NOAA/NSSL National Multisensor Mosaic QPE, Transactions on Geoscience and Remote Sensing, Geoscience and Remote Sensing, IEEE Transactions, 53 (8), 4434-4443.
  6. Chen, X.-C., K. Zhao, M. Xue, B. Zhou, and W. Xu, 2015: Radar observed diurnal cycle and propogation of convection over the Pear River Delta during Mei-Yu season. J. Geophy. Res.,120, 12557-12575.
  7. Clark, A., M. C. Coniglio, B. Coffer, G. Thompson, M. Xue, and F. Kong, 2015: Sensitivity of 24 h forecast dryline position and structure to boundary layer parameterizations in convection-allowing WRF model simulations, Wea. Forecasting, 30, 613-638.
  8. Dahl, N., H. Xue, X. Hu, and M. Xue, 2015: Coupled fire-atmosphere modeling of wildfire Spread using DEVS-FIRE and ARPS, Natural Hazards, 77, 1013-1035.
  9. Dawson, D.T., II, E. Mansell, and M. Kumjian , 2015: Does Wind Shear Cause Hydrometer Size Sorting? Journal of the Atmospheric Sciences, 72, 340-348.
  10. Dawson, D.T., II, M. Xue, J. Milbrandt, and A. Shapiro, 2015: Sensitivity of Real-Data Simulations of the 3 May 1999 Oklahoma City Tornadic Supercell and Associated Tornadoes to Multi-moment Microphysics. Part I: Storm-and Tornado-scale Numercial Forecasts. Monthly Weather Review,143, 2241-2265.
  11. Heinselman, P.L., D. LaDue, D.L. Kingfield, and R. Hoffman 2015: Tornado Warning Decisions Using Phased Array Radar Data. Weather and Forecasting, 30(1),57-78.
  12. Hou, T., F. Kong, X. Chen, H. Lei and Z. Hu, 2015: Evaluation of Radar and Automatic Weather Station Data Assimilation for Heavy Rainfall Event in Southern China. Adv. Atmos. Sci., 32, 967-978.
  13. Hu, X.-M., 2015: Air Pollution, Encyclopedia of Atmospheric Sciences (Second Edition), edited by G.R. North, J. Pyle, F. Zhang, 227-236, Academic Press, Oxford.
  14. Hu, X.-M., J.D. Fuentes, D. Toohey, and D. Wang, 2015: Chemical processeing within and above a Loblolly pine forest in North Carolina, USA, J. of Atmos. Chem., 72 (3), 235-259.
  15. Hu, Xiaoming 2015: Air Pollution Meteorology (chapter). Encyclopedia of Atmospheric Sciences (Second Edition), edited by G.R. North, 227-236, Academic Press, Oxford.
  16. Karimkashi, S. and G. Zhang 2015: Optimizing Radiation Patterns of a Cylindrical Polarimetric Phased-Array Radar for Multimissions. IEEE Trans. On Geoscience and Remote Sensing 53 (5), 2810-2818.
  17. Lei, L., G. Zhang, R. Doviak, and S. Karimkashi, 2015: Comparison of Theoretical Biases in Estimating Polarimetric Properties of Precipitation with Weather Radar Using Parabolic Reflector, or Planar and Cylindrical Arrays, IEEE Trans. On Geosci. Remote Sensing, (53) (8), 4313-4327.
  18. Li, X., J. Ming, M. Xue, Y. Wang, and K. Zhao, 2015: Implementation of a dynamic equation constraint based on the steady state moment equations within the WRF hybrid ensemble-3DVar data assimilation system and test with radar T-TREC wind assimilation for tropical cyclone, J. Geophy. Res., 120, 4017-4039.
  19. Ma, Y., Y. Yang, X.-M. Hu, R. Gan, 2015: Characteristics and Mechanisms of Sudden Warming Events in the Nocturnal Atmospheric Boundary Layer: A Case Study Using WRF, Journal of Meteorological Research, 29 (5) 747-763.
  20. Miao, Y., X.-M. Hu, S. Liu, Y. Zheng, S. Wang (2015): Seasonal variation of locat atmospheric circulations and boundary layer structure in the Beijing-Tianjin-Hebei region and implications for air quality, J. Adv. Model. Earth Syst., 7 (4) 1602-1624.
  21. Shapiro, A., E. Fedorovich, and J. A. Gibbs, 2015: An analytical verification test for numerically simulated convective flow above a thermally heterogeneous surface. Geosci. Model Dev., 8, 1809–1819.
  22. Shapiro, A., S. Rahimi, C. K. Potvin, and L. Orf, 2015: On the use of advection correction in trajectory calculations. J. Atmos. Sci., 72, 4261–4280.
  23. Snook, N. A., M. Xue, and Y. Jung, 2015: Multi-scale EnKF assimilation of radar and conventional observations and ensemble forecasting for a tornadic mesoscale convective system. Mon. Wea. Rev., 143, 1035-1057.
  24. Wang, G., W.-K. Wong, L. Liu, J. Dong, and M. Xue 2015: Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast. Atmos. Res., 154, 14-24.
  25. Xu, X., M. Xue, and Y. Wang, 2015: Mesovortices within the 8 May 2009 bow echo over central US: Analyses of the characteristics and evolution based on Doppler radar observations and a high-resolution model simulation. Mon. Wea. Rev., 143, 2266-2290.
  26. Xu, X., M. Xue, and Y. Wang, 2015: The genesis of mesovortices within a real data simulation of a bow echo system. J. Atmos. Sci.,72, 1963-1986.
  27. Zhang, G., 2015: Comments on "Describing the Shape of Raindrop Size Distributions Using Uncorrelated Raindrop Mass Spectrum Parameters". J. Appl. Meteor. Climat., 54 (9), 1970-1976.
  28. Zhang, H., Y. Wang, J. Hu, Q. Ying, X.-M. Hu, 2015: Relationships between meteorological parameters and criteria air pollutants in three megacities in China, Environmental Research, 140, 242-254.
  29. Zhu, J., F, Kong, L. Ran, and H. Lei, 2015: Bayesian Model Averaging with Stratified Sampling for Probabilistic Quantitative Precipitation Forecast in Northern China during Summer of 2010. Mon. Wea. Rev., 143, 3628-3641.
  30. Zhu, L., Y. Yang, and M. Xue, 2015: Percentile-based neighborhood precipitation verification and its application to landfalling tropical storm case with radar data assimilation. Adv. Atmos. Sci., 32, 1449-1459.

2014

  1. Cao, Q., Y. Wen, Y. Hong, J.J. Gourley, P.E. Kirstetter, 2014: Enhancing Quantitative Precipitation Estimation Over the Continental United States Using a Ground-Space Multi-Sensor Integration Approach. Geoscience and Remote Sensing Letter, IEEE, 11 (7), 1305-1309.
  2. Chen, S., J. J. Gourley, Y. Hong, P. E. Kirstetter, J. Zhang, K. W. Howard, Z. L. Flamig, J. Hu, and Y. Qi, 2014: Evaluation and uncertainty estimation of NOAA/NSSL next generation national mosaic QPE (Q2) over the Continental United States. Journal of Hydrometeorology, 14, 1308-1322.
  3. Chen S., H. Liu, Y. You, E. Mullends, J. Hu, Y. Yuan, M. Huang, L. He, Y. Luo, X. Zeng, G. Tang, Y. Hong, 2014: Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Overservations. PLoS ONE, 9(4), e89681.
  4. Chen, X.-C., K. Zhao, and M. Xue, 2014: Spatial and temporal characteristics of warm season convection over Pearl River Delta region, China based on three years of operational radar data. J. Geophy. Res., 119, 12447-12465.
  5. Cintineo, R., J. A. Otkin, M. Xue, and F. Kong, 2014: Evaluating the performance of planetary boundary layer and cloud microphysical parameterization schemes in a convection-permitting ensemble using synthetic GOES-13 satellite observations. Mon. Wea. Rev.,142, 163-182.
  6. Clark, A. J., R. G. Bullock, T. L. Jensen, M. Xue, and F. Kong, 2014: Application of object-based time-domain diagnostics for tacking precipitation systems in convection-allowing models. Wea. and Forecasting, 29, 517-542.
  7. Clark III, R., J. Gourley, Z. Flamig, Y. Hong, and E. Clark 2014: CONUS-wide evaluation of National Weather Service Flash Flood Guidance Producted. Weather and Forecasting, 29, 377-392.
  8. Dawson, D. T., II, E. R. Mansell, Y. Jung, L. J. Wicker, M. R. Kumjian, and M. Xue, 2014: Low-level ZDR signatures in supercell forward flanks: The role of size sorting and melting of hail. J. Atmos. Sci., 71, 276-299.
  9. Drobinski P., Karbou F., Bauer P., Cocquerez P., Lavaysse C., Hock T., Parson D., Robier F., Redelsperger J.-L., Venel, 2014: Driftsonde overservations to evaluate numerical weather prediction of the late 2006 African monsoon. J. Appl. Meteor. Clim., 52, 974-995.
  10. Duda, J. D., X. Wang, F. Kong, and M. Xue, 2014: Using varied microphysics to account for uncertainty in warm-season QPF in a convection-allowing ensemble. Mon. Wea. Rev., 142, 2198-2219,
  11. Gagne, D. J., II, A. McGovern, and M. Xue, 2014: Machine learning enhancement of storm scale ensemble probabilisic quantitative precipitation forecasts. Wea. Forecasting, 29, 1024–1043.
  12. Hu, X.-M., Z.Q. Ma, W.L. Lin, H.L. Zhang, J.L. Hu, Y. Wang, X.B. Xue, J.D. Fuentes, and M. Xue, 2014: Impact of the Loess Plateau on the atmospheric boundary layer structure and air quality in the North China Plan: A case study, Sci Total Environ, 499, 228-237.
  13. Huang Y., Chen S., Cao Q., Hong Y., Wu B., Huang M., Qiao L., Zhang Z., Li Z., Li W., Yang X., 2014: Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012. Water, 6, (1), 32-44.
  14. Jiang, S., Ren L., Hong Y., X. Yang, M. Ma, Y. Zhang and F. Yuan, 2014: Improvement of Multi-Satellite Real-Time Precipitation Products for Ensemble Streamflow Simulation in a Middle Latitude Basin in South China. Water Resources Management, Volume 28, Issue 8 2259-2278 .
  15. Jiang, X., H. Yuan, M. Xue, X. Chen, and X. Tan, 2014 : Analysis of a heavy rainfall event over Beijing on July 21-22, 2012 based on high resolution model analysis and forecasts, J. Meteor. Res., 28, 199-212.
  16. Jin, Ling, Fanyou Kong, Hengchi Lei, Zhaoxia Hu, 2014: A methodological study on using Weather Research and Forecasting (WRF) model outputs to drive a one-dimensional cloud model. Advances in Atmos. Sci., 31, 230-240.
  17. Johnson, A., X. Wang, M. Xue, F. Kong, G. Zhao, Y. Wang, K. Thomas, K. Brewster, and J. Gao, 2014: Multiscale characteristics and evolution of perturbations for warm season convection-allowing precipitation forecasts: Dependence on background flow and method of perturbation. Mon. Wea. Rev., 142, 1053-1073.
  18. Khan, S.I., Y. Hong, J.J. Gourley, M.U. Khattak, B. Yong, H.J. Vergara, 2014: Evaluation of Three High-Resolution Satellite Precipitation Estimates. Potential for Monsoon Monitoring over Pakistan. Advances in Space Research, Volume 54 Issue 4, 670-684.
  19. Klein, P. M., X.-M. Hu, and M. Xue, 2014: Mixing processes in the nocturnal atmospheric boundary layer and their impacts on urban ozone concentrations. Bound. Layer. Meteor., 150, 107-130.
  20. Kumjian, M.R. and A.D. Schenkman, 2014: The curious case of ice pellets in Middle Tennessee on 1 March 2014. J. Operational Meteor., 2 (17), 209-213.
  21. Li, Z., Yang D., Hong Y., Zhang J., and Qi Y. , 2014: Characterizing Spatiotemporal Variantions of Hourly Rainfall by Gauge and Radar in the Mountainous Three Gorges Region. J. Appl. Meteor. Climatology, 53, (4), 873-889.
  22. Mahale, V. N., G. Zhang, and M. Xue, 2014: Fuzzy logic classification of S-band polarimetric radar echoes to identify three-body scattering and improve data quality, J. Appl. Meteor. Clim., 53, 2017-2033.
  23. Mahale, V. N., J. Brotzge, and H. B. Bluestein, 2014: The advantages of a mixed-band radar network for severe weather operations: A case study of 13 May 2009. Wea. Forecasting.,29, 78-98.
  24. Pan, Y., K. Zhu, M. Xue, X. Wang, M. Hu, S.G. Benjamin, S.S. Weygandt, and J.S. Whitaker, 2014: A regional GSI-based EnKF-variational hybrid data assimilation system for the Rapid Refresh configuration: Results with a single, reduced resolution. Mon. Wea. Rev., 142, 3756-3780.
  25. Putnam, B. J., M. Xue, Y. Jung, N. A. Snook, and G. Zhang, 2014: The analysis and prediction of microphysical states and polarimetric variables in a mesoscale convective system using double-moment microphysics, multi-network radar data, and the ensemble Kalman filter. Mon. Wea. Rev.,142, 141-162.
  26. Schenkman, A. D., M. Xue, and M. Hu, 2014: Tornadogenesis in a high-resolution simulation of the 8 May 2003 Oklahoma City Supercell. J. Atmos. Sci., 71, 130-154.
  27. Shapiro, A., and E. Fedorovich, 2014: A boundary-layer scaling for turbulent katabatic flow. Bound.-Layer Meteor., 153, 1–17.
  28. Sun, J., M. Xue, J. W. Wilson, I. Zawadzki, J. Onvlee-Hooimeyer, S. P. Ballard, P. Joe, D. Barker, P.-H. Lee, B. Golding, M. Xu, and J. Pinto, 2014: Use of NWP for nowcasting precipitation: Recent progress and challenges. Bull. Amer. Meteor. Soc., 95, 409-426.
  29. Wainwright, C. E., D. T. Dawson, II, M. Xue, and G. Zhang, 2014: Diagnosing the intercept parameters of the exponential drop size distributions in a single-moment microphysics scheme and impact on supercell storm simulations. J. Appl. Meteor. Climatology, 53, 2072-2090
  30. Wan, Z., Hong Y., Khan S., Gourley J., Flamig Z., Kirschbaum D., and Tang G., 2014: A Cloud-based Global Flood Disaster Community Cyber-infrastructure: Development and Demonstration. Environmental Modeling & Software, 58, 86-94.
  31. Wang, M., M. Xue, K. Zhao, and J. Dong, 2014: Assimilation of T-TREC-retrieved winds from single-Doppler radar with an EnKF for the forecast of Typhoon Jangmi (2008), Mon. Wea. Rev., 142, 1892-1907.
  32. Wang, M., K. Zhao, M. Xue, G. Zhang, S. Liu, L. Wen, and G. Chen, 2014: Precipitation Microphysics Characteristics of a Typhoon Matmo (2014) Rainband after Landfall over Eastern China based on Polarimetric Radar Observations. J. Geophy. Res., 120 (20), doi: 10.1002 /2016JD02 5 307.
  33. Xue, M., M. Hu, and A. Schenkman, 2014: Numerical prediction of 8 May 2003 Oklahoma City tornadic supercell and embedded tornado using ARPS with assimilation of WSR-88D radar data. Wea. Forecasting, 29, 39-62.
  34. Yong, B.,Chen B., J.J. Gourley, L. Reng, Y. Hong, X. Chen, W. Wang, S. Chen, L. Gong, 2014: Intercomparison of t he Version-6 and Version-7 TMPA precipitation products over high and low latitues basins with independent gauge networks: Is the newer version better in both real-time and post-real-time analysis for water resources and hydrologic extremes? Journal of Hydrology, 508, 77-87.
  35. Zhang, M., Y. Qi, and X.-M. Hu 2014: Impact of East Asian Winter Monsoon on Pacific Storm Track, Meteorological Applications, 21, 873-878.

2013

  1. Adhikari, P. and Y. Hong, 2013: Will Nzoia Basin in Kenya See Water Deficiency in Coming Decades as a Result of Climate Change?. British Journal of Environment and Climate Change, Special Issue on Impact of Climate Change on Physical and Biogeochemical Processes in Hydrological Cycle.
  2. Brotzge, J., and W. Donner, 2013: The tornado warning process: A review of current research, challenges, and opportunities. Bull. Amer. Meteor. Soc., 94, 1715–1733.
  3. Brotzge, J., S. E. Nelson, R. L. Thompson, and B. T. Smith, 2013: Tornado probability of detection and lead time as a function of convective mode and environmental parameters. Wea. Forecasting, 28,1261-1276.
  4. Cao, Q., Y. Hong, Y. Qi, Y. Wen, J. Zhang, J. J. Gourley and L. Liao, 2013: Empirical Conversion of Vertical Profile of Reflectivity (VPR) from Ku-band to S-band Frequency. Journal of Geophysical Research: Atmospheres. doi: 10.1002/jgrd.50138.
  5. Cao, Q., Y. Hong, J. J. Gourley, Y. Qi, J. Zhang, Y. Wen, and P. E. Kirstetter, 2013: Statistical and physical analysis of the vertical structure of precipitation in mountainous west region of the United States using 11+ years of spaceborne observations from TRMM precipitation radar. Journal of Applied Meteorology and Climatology, 52, 408-424. doi: 10.1175/JAMC-D-12-095.1.
  6. Cao, Q., G. Zhang, and M. Xue, 2013: A variational approach for retrieving raindrop size distribution from polarimetric radar measurements in the presence of attenuation. J. Appl. Meteor. Climatology, 52, 169-185.
  7. Cavallo, S.M. and G. Hakim, 2013: The physical mechanisms of tropopause polor cyclone intensity change. J. Atmos, Sci., 70, 3359-3373.
  8. Cavallo, S.M., R. T. Torn, C. Snyder, C. Davis, W. Wang, and J. Done, 2013: Evaluation of the Advanced Hurricane WRF data assimilation system for the 2009 Atlantic Hurrican season. Mon. Wea. Rev., 141, 523-541.
  9. Chen, S., P.E. Kirstetter, Y. Hong, J.J. Gourley, Y.D. Tian, Y.C. Qi, Q. Cao, J. Zhang, K. Howard, J.J. Hu, X.W. Xue, 2013: Evaluation of Spatial Errors of Precipitation Rates and Types from TRMM Spaceborne Radar over the Southern CONUS., Journal of Hydrometeorology, Volume 14, No. 6.
  10. Chen, S., Y. Hong, Q. Cao, P.-E. Kirstetter, J. J. Gourley, Y. Qi, J. Zhang, K. Howard, J. Hu and J. Wang, 2013: Performance Evaluation of Radar and Satellite Rainfalls for Typhoon Morakot over Taiwan: Are Remote-sensing Products Ready for Gauge Denial Scenario of Extreme Events?. Journal of Hydrology. doi: 10.1016/j.jhydrol.2012.12.026.
  11. Chen, X., K. Zhao, W.-C. Lee, B. J.-D. Jou, and M. Xue, P.R. Harasti, 2013: The improvement to the environment wind and tropical cyclone circulation retrievals with modified GBVTD (MGBVTD) technique. J. Appl. Meteor. Clim, 52, 2493-2508.
  12. Clark, A. J., J. Gao, P. T. Marsh, T. Smith, J. S. Kain, J. Correia, Jr., M. Xue, and F. Kong, 2013: Tornado path length forecasts from 2010-2011 using ensemble updraft helicity. Wea. Forecasting, 28, 387-407.
  13. Cohn, S.A., Hock, T., Cocquerez, P., Wang, J., Rabier F., Parsons D., Harr P.,Wu, C., Drobinski, P., Karbou, F., Vénel, S., Vargas A., Fourrié, N., Saint-Ramond N., Guidard V., Doerenbecher A., Hsu, H., Lin, P, Chou, M., Redelsperger, J., Martin, C., Fox J., Potts N., Young, K., Cole H., 2013: Bulletin of the American Meteorological Society, 94, (Issue 11) (November 2013), 1661-1674.
  14. Dawson, D.T., II, L. J. Wicker, E. R. Mansell, Y. Jung, and M. Xue, 2013: Low-level polarimetric radar signatures in EnKF analyses and forecasts of the 8 May 2003 Oklahoma City tornadic supercell: Impact of multi-moment microphysics and comparisons with observations. Adv. Meteor., 2013, http://dx.doi.org/10.1155/2013/818394.
  15. Dong, J. and M. Xue, 2013: Assimilation of radial velocity and reflectivity data from coastal WSR-88D radars using ensemble Kalman filter for the analysis and forecast of landfalling hurricane Ike (2008). Quart. J. Roy. Meteor. Soc., 139, 467-487.
  16. Doughty, D. C., J. D. Fuentes, R. Sakai, X.-M. Hu, and K. J. Sanchez (2013), Nocturnal isoprene declines in a semi-urban environment, J. Atmos. Chem., DOI:10.1007/s10874-012-9247-0.
  17. Dresback,K.M., J.G. Fleming, C. Kaiser, J.J. Gourley, E.M. Tromble, R.A. Luettich, R.L. Kolar, Y. Hong, S. Van Cooten, H.J. Vergara, Z.L. Flamig, B.O. Blanton, H.M. Lander, K.E. Kelleher and K.L. Nemunaitis-Monroe, 2013: Skill Assessment of a Prototype Total Water Level Operational Forecast System During Hurricane Irene. Continental Shelf Research, 71, 78-94, doi:10.1016/j.csr.2013.10.007.
  18. Drobinski, P., Karbou F., Bauer, P., Cocquerez P., Lavaysse C. Hock, T., Parsons, D., Rabier, F., Redelsperger, J., Vénel S, 2013: Driftsonde Observations to Evaluate Numerical Weather Prediction of the Late 2006 African Monsoon. Journal of Applied Meteorology and Climatology, 52, Issue 4 (April 2013) 974-995.
  19. Gasperoni, N. A., M. Xue, R. D. Palmer, and J. Gao, 2013: Sensitivity of convective initiation prediction to near-surface moisture when assimilating radar refractivity: Impact tests using OSSEs. J. Atmos. Ocean. Tech., 30, 2281-2302.
  20. Gao, J., T. T. Smith, D. J. Stensrud, C. Fu, K. Calhoun, K. L. Manross, J. Brogdon, V. Lakshmanan, Y. Wang, K. W. Thomas, K. Brewster, and M. Xue, 2013: A realtime weather-adaptive 3DVAR analysis system for severe weather detections and warnings. Wea. Forecasting, 28, 727-745.
  21. Gao, J., M. Xue, and D. J. Stensrud, 2013: The development of a hybrid-3DVAR algorithm for storm-scale data assimilation. Adv. Meteor., 2013, http://dx.doi.org/10.1155/2013/512656.
  22. Ge, G., J. Gao, and M. Xue, 2013: Impact of diagnostic pressure equation constraint on the prediction of tornadic supercell thunderstorms with assimilation of radar data using a three-dimensional variational system. Adv. Meteor., 2013, http://dx.doi.org/10.1155/2013/947874.
  23. Ge, G., J. Gao, and M. Xue, 2013: Impacts of assimilating measurements of different sate variables on the analysis and forecast of a supercell storm using three dimensional variational method. Mon. Wea. Rev., 141, 2759-2777.
  24. Gourley, J. J., Y. Hong, Z. L. Flamig, A. Arthur, R. A. Clark, M. Calianno, I. Ruin, T. Ortel, M. E. Wieczorek, E. Clark, P.-E. Kirstetter, and W. F. Krajewski, 2013: A Unified Flash Flood Database over the US. Bulletin of the American Meteorological Society. doi: 10.1175/BAMS-D-12-00198.
  25. Hall, J.D., M. Xue, L. Ran and Lance M. Leslie, 2013: High-resolution modeling of typhonn Morakot (2009): Vortex Rossby waves and their and their role in extreme precipitation over Taiwan. J. Atmos. Sci., 70, 163-186.
  26. Hou, Tuanjie, Fanyou Kong, Xunlai Chen, Hengchi Lei, 2013: Impact of 3DVAR data assimilation on the prediction of heavy rainfall over Southern China. Advances in Meteorology, Vol 2013, 17p. doi:10.1155/2013/129642.
  27. Hu, X.-M., P. M. Klein, and M. Xue, 2013: Implications of the update in the YSU planetary boundary layer scheme within the WRF model for wind resource assessment and air pollution simulations. J. Geophy. Res., 118, 10490-10505.
  28. Hu, X.-M., P. M. Klein, M. Xue, J. K. Lundquist, and F. Zhang, 2013: Impact of low-level jets on the ncturnal urban heat island intensity in Oklahoma City. J. Appl. Meteor. Climatol., 52, 1779-1802.
  29. Hu, X.-M., P. Klein , M. Xue , A. Shapiro, A. Nallapareddy, 2013: Enhanced vertical mixing associated with a noctural cold front passage and its impact on near-surface temperature and ozone concentration. J. Geophy. Res., 118, 2714-2728.
  30. Hu, X.-M., P. M. Klein, M. Xue, F. Zhang, D. C. Doughty, and J. D. Fuentes, 2013: Impact of the vertical mixing-induced by low-level jet on boundary layer ozone concentration. Atmos. Environment, 70, 123-130.
  31. Jin, Ling, Hengchi Lei, Fanyou Kong, Jiefan Yang, Zhaoxia Hu, 2013: Cloud Seedability Study with a Dual-Model System. Atmospheric and Oceanic Science Letters, 6, 197-202.
  32. Johson, A., X. Wang, 2013: Object-based evaluation of a storm-scale ensemble during the 2009 NOAA Hazardous Weather Testbed Spring Experiment. Mon. Wea. Rev., 149, 1079-1098.
  33. Johnson, A., X. Wang, F. Kong, and M. Xue, 2013: Object-based evaluation of the impact of hortizontal grid spacing on convection-allowing forecasts. Mon. Wea. Rev., 141, 3413-3425.
  34. Johnson, A., X. Wang, M. Xue, F. Kong, G. Zhao, Y. Wang, K.W. Thomas, K.A. Brewster and J. Gao, 2013: Multiscale characteristics and evolution of perturbations for warm season convection-allowing precipitation forecasts: Dependence on background flow and method of perturbation. Mon. Wea. Rev., 141, 3413-3425.
  35. Kain, J. S., M. C. Coniglio, J. Correia, A. J. Clark, P. T. Marsh, C. L. Ziegler, V. Lakshmanan, S. D. Miller, S. R. Dembek, S. J. Weiss, F. Kong, M. Xue, R. A. Sobash, A. R. Dean, I. L. Jirak, and C. J. Melick, 2013: A feasibility study for probabilistic convection initiation forecasts based on explicit numerical guidance. Bull. Amer. Meteor. Soc., 94, 1213-1225.
  36. Kirstetter, P.-E., Y. Hong, J. J. Gourley, M. Schwaller, W. Petersen, and J. Zhang, 2013: Comparison of TRMM 2A25 products, version 6 and version 7, with NOAA/NSSL ground radar-based National Mosaic QPE. J. Hydrometeor., 14, 661-669. doi:10.1175/JHM-D-12-030.1
  37. Lakshmivarahan, S., J.M. Lewis and Dung Phan 2013: Data assimilation as a problem in optimal tracking: Application of Pontryagin's minimum principle. J. Atmos. Sci., 70, 1257-1277.
  38. Lee, J.-G. and M. Xue, 2013: A Study on a snowband associated with a coastal front and cold-air damming event of 3-4 February 1998 along the eastern coast of the Korean peninsula. Adv. Atmos. Sci., ADV. Atmos. Sci, 30, 263-279.
  39. Li, X., J. Ming, Y. Wang, K. Zhao, and M. Xue, 2013: Assimilation of T-TREC-retrieved wind data with WRF 3DVAR for the short-term forecasting of typhoon Meranti (2010) near landfall. J. Geophy. Res., 118, 10361-10375.
  40. Liu, C., Weiyue Li, Hangbin Wu, Ping Lu, Kai Sang, Weiwei Sun, Yang Hong, Rongxing Li, 2013: Susceptibility Evaluation and Mapping of China's Landslides Based on Multi-source Data. Natural Hazards.
  41. Lei Qiao, Z. Pan, R. Herrmann and Y. Hong, 2013: Hydrological variability and uncertainty induced by climate change in the lower Missouri River Basin based on NARCCAP simulations and SWAT model. Journal of American Water Resources Association. doi: 10.1111/jawr.12126.
  42. Liu, C., and Xiao, Q., 2013: An Ensemble-Based Four Dimenstional Variational Data Assimilation Scheme. Part III: Antarctic Applications with Advanced Research WRF Using Real Data. Mon. Wea. Rev.,141, 2721-2739.
  43. Liu L., Y. Hong, J. Looper, R. Riley, B. Yong, Z. Zhang, J. Hocker and M. Shafer, 2013: Climatological Drought Analyses and Projection using SPI and PDSI: A Case Study for Arkansas Red River Basin. Journal of Hydrologic Engineering, 18 (7), 809-816. doi: 10.1061/(ASCE)HE.1943-5584.0000619.
  44. Maggioni, V., H. J. Vergara, E. N. Anagnostou, J. J. Gourley, Y. Hong, and D. Stampoulis, 2013: Investigating the applicability of error correction ensembles of satellite rainfall products in river flow simulations. Journal of Hydrometeorology, 14 (4), 1194–1211. doi: 10.1175/JHM-D-12-074.1
  45. McGovern, A., D.J. Gagne II, J.K. Williams, R.A. Brown, and J.B. Basara, 2013: Enchancing understanding and improving prediction of severe weather through spa-tiotemporal realtional learning. Machine Learning.
  46. Natenberg, E., J. Gao, M. Xue, and F. H. Carr, 2013: Multi-Doppler radar analysis and forecast of a tornadic thunderstorm using a 3D variational data assimilation technique and ARPS model. Adv. Meteor.,2013 Article ID 281695, doi:10.1155/2013/281695.
  47. Pan, Y., K. Zhu, M. Xue, X. Wang, J. S. Whitaker, S. G. Benjamin, S. S. Weygandt, and M. Hu, 2013: A regional GSI-based EnKF-variational hybrid data assimilation system for the Rapid Refresh configuration: Results with a single, reduced resolution. Mon. Wea. Rev., 141, 4118-4139.
  48. Potvin, C. K., L. J. Wicker, M. I. Biggerstaff, D. Betten, and A. Shapiro, 2013: Comparison        between dual-Doppler and EnKF storm-scale wind analyses: The 29-30 May 2004 Geary,Oklahoma, supercell thunderstorm. Mon. Wea. Rev., 141, 1612–1628.
  49. Qi, Y., J. Zhang, Q. Cao, Y. Hong, and X.-M. Hu, 2013: Correction of Radar QPE Errors for Non-Uniform VPRs in Mesoscale Convective Systems using TRMM Observations, J. Hydrometeorology, 14, 1672-1682.
  50. Rabier F., Cohn S., Cocquerez P., Hertzog A., Avallone L., Deshler T., Haase J., Hock T., Doerenbecher A., Wang J., Guidard V., Thepaut J.-N., Langlan R., Tangborn A., Balsamo G., Brun E., Parsons D., Bordereau J., Cardinali C., Danis F., Escarnot J.-P., Fourrie N., Gelara R., Genthon C., Ide K., Kalnajs L., Martin C., Meunier L.-F., Nicot J.-M., Peerrula T., Potts N., Ragazzo P., Richardson D., Sosa-Sesma S., Vargas A. 2013: The Concordiasi field experiment over Antarctica: First results from innovative atmospheric measurements, Bull. Amer. Meteor. Soc, 94, Issue 3 (March 2013), ES17-ES20 .
  51. Reeves, H.D., Dawson, D.T., II, 2013: The Dependence of QPF on the Choice of Microphysical Parameterization for Lake-Effect Snowstorms, J. Appl. Meteor. Climatol., 52, 363-377.
  52. Schumacher, R.S., A. J. Clark, M. Xue and F. Kong, 2013: Factors influencing the development and maintenance of nocturnal heavy-rain-producing covective systems in a storm-scale ensemble. Mon. Wea. Rev., 141, 2778-2801.
  53. Shapiro, A., and E. Fedorovich, 2013: Similarity models for unsteady free convection flows along a differentially cooled horizontal surface. J. Fluid Mech., 736, 444–463.
  54. Shen X., K. Mao, Y. Hong, Q. Qin and G. Zhang, 2013: Bare surface soil moisture estimation using double-angle and dual-polarization L-band radar data. IEEE Transaction on Geoscience and Remote Sensing, 51, 3931-3942.
  55. Shimose, K.., M. Xue, R. D. Palmer, J. Gao, B. L. Cheong, and D. J. Bodine, 2013: Two-dimensional variational analysis of near-surface moisture from simulated radar refractivity-related phase change observations. Adv. Atmos. Sci., 30, 291-305.
  56. Stensrud, D.J., L.J. Wicker, M.Xue, D.T. Dawson II, N. Yussouf, D.M. Wheatley, T.E. Thompson, N.A. Snook, T.M. Smith, A.D. Schenkman, C.K. Potvin, E.R. Mansell, T. Lei, K.M. Kulman, Y. Jung, T.A. Jones, J. Gao, M.C. Coniglio, H.E. Brooks, and K.A. Brewster, 2013: Progress and challenges with Warn-on-Forecast. Atmo. Res., 123, 2-16.
  57. Stratman, D. R., M. C. Coniglio, S. E. Koch, and M. Xue, 2013: Use of multiple verification methods to evaluate forecasts of convection from hot- and cold-start convection-allowing models. Wea. Forecasting, 28, 119-138.
  58. Tanamachi, R.L., L.J. Wicker, D.C. Dowell, H.B. Bluestein, and M. Xue 2013: EnKF assimilation of high-resolution, mobile Doppler radar data of the 4 May 2007 Greensburg, Kansas supercell into a numerical cloud mode. Mon. Wea. Rev., 141, 625-648.
  59. Tanamachi, R. L., H. B. Bluestein, M. Xue, W.-C. Lee, K. A. Orzel, S. J. Frasier, and R. M. Wakimoto, 2013: Near-surface vortex structure in a tornado and a tornado-like vortex observed by a mobile, W-band radar during VORTEX2. Mon. Wea. Rev., 141, 3661-3690.
  60. Tiwary, A., Namdeo, A., Fuentes, J., Dore, A., Hu, X. and Bell, M. (2013) Systems scale assessment of the sustainability implications of emerging green initiatives. Environmental Pollution. DOI 10.1016/j.envpol.2013.03.049.
  61. Wang, Y., Y. Jung, T. A. Supinie, and M. Xue, 2013: A hybrid MPI/OpenMP parallel algorithm and performance analysis for an ensemble square root filter suitable for dense observations. J. Atmos. Ocean. Tech.,30, 1382-1397.
  62. Wang, S., M. Xue, and J. Min, 2013: A four-dimensional asynchronous ensemble square-root filter (4DEnSRF) and test with simulated radar data. Quartl. J. Roy. Meteor., So., 139, 805-819.
  63. Wang, S., M. Xue, A.D. Schenkman, and J. Min, 2013: An iterative ensemble square root filter and tests with simulated radar data for storm scale data assimilation. Quart. J. Roy. Meteor. Soc., 139, 1888-1903.
  64. Wen, Y., Q. Cao, P.-E. Kirstetter, Y. Hong, J. J. Gourley, J. Zhang, G. Zhang, and B. Hong, 2013: Incorporating NASA spaceborne radar data into NOAA National Mosaic QPE system for improved precipitation measurement: A physically based VPR identification and enhancement method. Journal of Hydrometeorology.
  65. Xu X., Xue M., and Wang Y., 2013: Gravity wave momentum flux in directional shear flows over three-dimensional mountains: Linear and nonlinear numerical solutions as compared to linear analytical solutions. J. Geophy. Res., 118, 7670-7681.
  66. Xue, M., and J. Dong, 2013:, Impact of assimilating best track minimum sea level pressure data together with coastal Doppler radar data on hurricane analysis and prediction at a cloud-resolving resolution, Acta Meteorologica Sinica, 27, 379-399.
  67. Xue, M., F. Kong, K. W. Thomas, J. Gao, Y. Wang, K. A. Brewster, and K. K. Droegemeier, 2013: Prediction of convective storms at convection-resolving 1-km resolution over continental United States with radar data assimilation: An example case of 26 May 2008 and precipitation forecasts from spring 2009. Adv. Meteor., 2013, Article ID 259052, doi:10.1155/2013/259052.
  68. Xue, M., J. Schleif, F. Kong, K. K. Thomas, Y. Wang, and K. Zhu, 2013: Track and intensity forecasting of Hurricanes: Impact of cloud-resolving resolution and ensemble Kalman filter data assimilation on 2010 Atlantic season forecasts. Wea. Forecasting, 28, 1366-1384.
  69. Yong, B., L. L. Ren, Y. Hong, J. J. Gourley, X. Chen, J. Dong, W. Wang, Y. Shen, and J. Hardy, 2013: Spatial-temporal changes of water resources in a typical semi-arid basin of North China over the past 50 years and assessment of possible natural and socioeconomic causes. Journal of Hydrometeorology, 14 (4), 1009-1034. doi: 10.1175/JHM-D-12-0116.1.
  70. Yong, B., L. Ren, Y. Hong, J. Gourley, Y. Tian, G. Huffman, X. Chen, W. Wang, and Y. Wen, 2013: First evaluation of the climatological calibration algorithm in the real-time TMPA-RT precipitation estimates over two basins at high and low latitudes. Water Resources Research, 49 (5), 2461–2472. doi: 10.1002/wrcr.20246.
  71. Yussouf, N., J. Gao, D. Stensurd, and G. Ge, 2013: The Impact of Mesoscale Environmental Uncertainty on the Prediction of a Tornadic Supercell Storm using Ensemble Data Assimilation Approach. Advances in Meteorology, 2013, 731647, 15 pages.
  72. Zahraei, A., K-L. Hsu, S. Sorooshian, J. J. Gourley, Y. Hong, and A. Behrangi, 2013: Short-term quantitative precipitation forecasting using an object-based approach. Journal of Hydrology, 483, 1-15. doi: 10.1016/j.jhydrol.2012.09.052.
  73. Zhang, M., Y. Qi, and X.-M. Hu, 2013: Impact of East Asian Winter Monsoon On Pacific Storm Track, Meteorological Applications.
  74. Zhang N., Y. Hong, Q. Qin & L. Liu, 2013: VSDI: a visible and shortwave infrared drought index for monitoring soil and vegetation moisture based on optical remote sensing. International Journal of Remote Sensing, 34 (13), 4585-4609. doi: 10.1080/01431161.2013.779046.
  75. Zhang N., Y. Hong, Q. Qin & L. Zhu, 2013: Evaluation of the Visible and Shortwave Infrared Drought Index in China. International Journal of Disaster Risk Science.
  76. Zhang, Y., Y. Hong, X. Wang, J.J. Gourley, J. Gao, H. Vergara and B. Yong, 2013: Assimilation of Passive Microwave Streamflow Signals for Improving Flood Forecasting: A First Study in Okavango River Basin, Africa. IEEE Journal of Sepected Topics in Applied Earth Observations and Remote Sensing. doi: 10.1109/JSTARS.2013.2251321.
  77. Zhang N., Y. Hong, Q. Qin & L. Liu, 2013: VSDI: a visible and shortwave infrared drought index for monitoring soil and vegetation moisture based on optical remote sensing. International Journal of Remote Sensing, 34 (13), 4585-4609. doi: 10.1080/01431161.2013.779046.
  78. Zhu, J., F. Kong, and H. Lei, 2013: A Regional Ensemble Forecast System for Stratiform Precipitation Events in the Northern China Region. Part II: Seasonal Evaluation for summer 2010. Advances in Atmos. Sci., 30, 15-28.
  79. Zhu, K., Y. Pan, M. Xue, X. Wang, J.S. Whitaker, S.G. Benjamin, S.S. Weygandt, and M. Hu, 2013: A regional GSI-based EnKF system for the Rapid Refresh configuration: Results with a single, reduced resolution. Mon. Wea. Rev., 141, 4118-4139.

 

2012

  1. Berenguer, M., M. Surcel, I. Zawadzki, M. Xue, and F. Kong, 2012: The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models. Part II: Intercomparison between numerical models and with nowcasting. Mon. Wea. Rev., 140, 2689-2705.
  2. Cavallo, S.M. and G.J. Hakim, 2012: Radiative impact on tropopause polar vortices over the Artic. Mon. Wea. Rev., 140, 1683-1702. .
  3. Clark, A. J., J. S. Kain, P. T. Marsh, J. Correia, Jr., M. Xue, and F. Kong, 2012: Forecasting tornado pathlengths using a three-dimensional object identification algorithm applied to convection-allowing forecasts. Wea. Forecasting, 27, 1090-1113.
  4. Dong, J., and M. Xue, 2012: Assimilation of radial velocity and reflectivity data from coastal WSR-88D radars using ensemble Kalman filter for the analysis and forecast of landfalling hurrican IKE (2008). Quart. J. Roy. Meteor. Soc., DOI: 10.1002/qj.1970.
  5. Drobinski P., Cocquerez P., Doerenbecher A., Hock T., Lavaysse C., Parsons D., Redelsperger J.L., Venel S., 2012: Hurricane and Monsoon Tracking with Driftsondes. Encyclopedia of Sustainability Science and Technolog, ed. Springer.
  6. Du, N., M. Xue, K. Zhao, and J. Min, 2012: Impact of assimilating airborne Doppler radar velocity data using the ARPS 3DVAR on the analysis and prediction of hurricane Ike (2008). J. Geophy. Res., 117, D18113.
  7. Gagne II, David John, A. McGovern, J. Basara, and R.A. Brown, 2012: Tornadic Supercell Environments Analyzed Using Surface and Reananlysis Data: A Spatiotemporal Relational Data Mining Approach. J. Appl. Meteor. and Climatol., 51, 2203-2217.
  8. Ge, G., J. Gao, M. Xue, and K. K. Droegemeier, 2012: Diagnostic pressure equation as a weak constraint in a storm-scale three dimensional variational radar data assimilation system. J. Atmos. Ocean. Tech., 29, 1075-1092.
  9. Gourley, J. J., J. M. Erlingis, Y. Hong and E. B. Wells, 2012:  Evaluation of Tools Used for Monitoring and Forecasting Flash Floods in the United States. Weather and Forecasting, 27(1), 158-173.
  10. Grout, T., Y. Hong, J. Basara, B. Balasundaram, Z. Kong and S. T. S. Bukkapatnam , 2012:   Significant Winter Weather Events and Associated Socioeconomic Impacts (Federal Aid Expenditures) across Oklahoma: 2000–10.   Weather, Climate, and Society, 4(1), 48-58.
  11. Heinselman, P. L., D. S. LaDue, and H. Lazrus (2012). Exploring Impacts of Rapid-Scan Radar Data on NWS Warning Decisions. Weather and Forecasting. 27(4), 1031–1044.
  12. Holland, B., and X. Wang, 2012: Effects of sequential or simultaneous assimilation of observations and localization methods on the performance of the ensemble Kalman filter. Q.J.R. Meteo. Soc.,139, 758-770.
  13. Hong, Y., S. Chen, X. Xue and G. Hodges, 2012: Global Precipitation Estimation and Applications. Multiscale Hydrologic Remote Sensing, Ni-Bin Chang and Yang Hong, Eds., Taylor & Francis, 371-386.
  14. Hong, Y., S. Khan, C. Liu, and Y. Zhang, 2012: Global Soil Moisture Estimation Using Microwave Remote Sensing. Multiscale Hydrologic Remote Sensing, Ni-Bin Chang and Yang Hong, Eds., Taylor & Francis, 399-410.
  15. Hong, Y., Z. Liao, R.F. Adler, and C. Liu (2012), “Satellite Remote Sensing for Landslide Prediction”, Book Chapter 9th in N.B. Chang (ed.) Environmental Remote Sensing and System Analysis, Taylor & Francis Group-CRC Press, ISBN 978-1-4398-7743-2, 520page, P191-208 (Links: http://www.amazon.com/Environmental-Remote-Sensing-Systems-Analysis/dp/1439877432
  16. Hu, X.-M., D. Doughty, K.J. Sanchez, E. Joseph, and J. D. Fuentes (2012), Ozone variability in the atmospheric boundary layer in Maryland and its implications for vertical transport model, Atmos. Environ.,46,354-364.
  17. Jiang, S.; L.L. Ren, Y. Hong, B. Yong, X. Yang, F. Yuan, and M. Ma, 2012: Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method.   Journal of Hydrology, 452–453, 213–225.
  18. Johnson, A., and X. Wang, 2012a: Verification and calibration of neighborhood and object-based probabilistic precipitation forecasts from a multi-model convection-allowing ensemble. Mon. Wea. Rev., 140, 3054-3077.
  19. Johnson, A., and X. Wang, 2012b: Object-based evaluation of a storm scale ensemble during the 2009 NOAA Hazardous Weather Testbed Spring Experiment. Mon. Wea. Rev., 141, 1079-1098.
  20. Jung, Y., M. Xue, and M. Tong, 2012: Ensemble Kalman filter analyses of the 29-30 May 2004 Oklahoma tornadic thunderstorm using one-and two-moment bulk microphysics schemes. Mon. Wea. Rev.,140, 1457-1475.
  21. Khan, S. I., Y. Hong, H. J. Vergara, J. J. Gourley, G. R. Brakenridge, T. De Groeve, Z. L. Flamig, F. Policelli and B. Yong,  2012:  Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins.   Geoscience and Remote Sensing Letters, IEEE, 9(4), 663-667.
  22. Klein, P., 2012: Metropolation effects on atmospheric patterns: important scales. Metropolitan sustainability: Understanding and improving the urban environment. F. Zeeman (Ed.), Woodhead Publishing Series in Energy: Number 34.
  23. Lakshmivarahan, S., and J.M. Lewis 2012: Nudging Methods: A Critical Overview. A chapter in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Vol II, edited by Seon Ki Park and L. Liang, Springer Verlag.
  24. Kirschbaum, D. B., R. Adler, Y. Hong, S. Kumar, C. Peters-Lidard and A. Lerner-Lam  2012:  Advances in landslide nowcasting: evaluation of a global and regional modeling approach. Environmental Earth Sciences, 66(6), 1683-1696.
  25. Kirstetter, P.E., Y. Hong, J.J. Gourley, S. Chen, Z. Flamig, J. Zhang, M. Schwaller, W. Petersen, and E. Amitai, 2012: Toward a Framework for Systematic Error Modeling of Spaceborne Precipitation Radar with NOAA/NSSL Ground Radar-based National Mosaic QPE. Journal of Hydrometeorology, 13(4), 1285-1300.
  26. Lei, L., G. Zhang, R.J. Doviak, R.D. Palmer, B.L. Cheong, M. Xue, Q. Cao, and Y. Li, 2012: Multi-lag correlation estimators for polarimetric radar measurements in the presence of noise. J. Atmos. Ocean Tech., 29, 772-795.
  27. Lewis, J.M. and S. Lakshmivarahan 2012: A Question of Adequacy of observations in Variational Data Assimilation. A chapter in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Vol II, edite by Seon Ki Park and L. Liang, Springer Verlag.
  28. Li, Y., X. Wang, and M. Xue 2012: Assimilation of Radar Radial Velocity Data with the WRF Hybrid Ensemble-3DVAR System for the Prediction of Hurricane Ike (2008). Mon. Wea. Rev., 140, 3507-3524.
  29. Liao, Z., Y. Hong, D. Kirschbaum and C. Liu  2012:  Assessment of shallow landslides from Hurricane Mitch in central America using a physically based model.   Environmental Earth Sciences, 66(6), 1697-1705.
  30. Liu, L., Y. Hong, C. Bednarczyk, B. Yong, M. Shafer, R. Riley and J. Hocker  2012:  Hydro-Climatological Drought Analyses and Projections Using Meteorological and Hydrological Drought Indices: A Case Study in Blue River Basin, Oklahoma.   Water Resources Management, 26(10), 2761-2779.
  31. Liu, L., Y. Hong, J. E. Hocker, M. Shafer, L.M. Carter, J.J. Gourley, C.N. Bednarczyk, B. Yong, and P. Adhikari, 2012: Analyzing projected changes and trends of temperature and precipitation in the southern USA from 16 downscaled global climate models. Theoretical and Applied Climatology, 109(3-4), 345-360.
  32. Mahale, V., J. Brotzge, and H. Bluestein, 2012: An analysis of vortices embedded within a quasi-linear convective system using X-band polarimetric radar. Wea. Forecasting, 27, 1520-1537.
  33. Ni-Bin Chang and Yang Hong (2012), Book “Multiscale Hydrologic Remote Sensing: Prospects and Applications”, Taylor & Francis Group-CRC Press, ISBN 978-1-4398-7745-6, 550 Page (Link: http://www.amazon.com/Multiscale-Hydrologic-Remote-Sensing-Perspectives/dp/1439877459), Adopted as textbook for Remote Sensing Hydrology Course.
  34. Ni-Bin, Chang. and Y. Hong, 2012: Toward Multiscale Hydrologic Remote Sensing for Creating Integrated Hydrologic Observatories. Multiscale Hydrologic Remote Sensing, Ni-Bin Chang and Yang Hong, Eds., Taylor & Francis, 1-6.
  35. Potvin, C. K., A. Shapiro, and M. Xue, 2012: Impact of a vertical vorticity constraint in variational dual-Doppler wind analysis: Tests with real and simulated supercell data. J. Atmos. Oceanic Technol., 29, 32-49.
  36. Potvin, C.K., L.J. Wicker, and A. Shapiro, 2012: Assessing errors in a variational dual-Doppler wind syntheses of supercell thunderstorms ovserved by storm-scale mobile radars. J. Atmos. Oceanic Technol. 29, 1009-1025.
  37. Qiu, L., M. Gan, K. Wang, J. Deng, Y. Hong, J. Xu, and W. Zhu , 2012: Source Identification of soil Cu, Zn, Pb, AND Cd from anthropogenic activities by decision tree analysis in Fuyang County, China." Fresenius Environmental Bulletin, 21(6), 1390-1398.
  38. Sadiq, K., Y. Hong and J. Wang, 2012: Multispectral Satellite Data for Flood Monitoring and Inundation Mapping. Multiscale Hydrologic Remote Sensing, Ni-Bin Chang and Yang Hong, Eds., Taylor & Francis, 251-268.
  39. Schenkman, A., M. Xue, and A. Shapiro, 2012: Tornadogenesis in a simulated mesovortex within a real-data-initialized mesoscale convective system. J. Atmos. Sci, 69, 3372-3390.
  40. Shapiro, A., B. Burkholder, and E. Fedorovich, 2012: Analytical and numerical investigation of two-dimensional katabatic flow resulting from local surface cooling. Bound.-Layer Meteor., 145, 249-272.
  41. Shapiro, A., and E. Fedorovich, 2012: Secularly growing oscillations in a stratified rotating fluid. Phys. Fluids, 24, 054107.
  42. Shen, X.; Q. Qin, Y. Hong, and G. Zhang 2012:  A matrix inversion approach of computing T-matrix for axially symmetrical particles of extreme shape and dielectrically large dimension. Radio Science, 47(5), RS5005.
  43. Snook, J., M. Xue, and Y. Jung, 2012: Ensemble probabilistic forecasts of a tornadic mesoscale convective system from ensemble Kalman filter analyses using WSR-88D and CASA radar data. Mon. Wea. Rev., 140, 2126-2146.
  44. Snow, J.T., Zeng X., Klein, P., Ebelt Sarnat, S., Shepherd M., Stanley E.M., 2012: Scoping the Problem, Defining the Needs. Board on Atmospheric Sciences and Climate; Division on Earth and Life Sciences; National Research Countil. Urban Meteorology: Forecasting, Monitoring and Meeting Users' Needs, National Academies of Sciences, ISbn 978-0-309-25217-1, 190 pp.
  45. Tanamachi, R.L., H.B. Bluestein, J.B. Houser, S.J. Frasier, and K.M. Hardwick, 2012: Mobile, X-band, polarimetric Doppler radar observations of the 4 May 2007 Greensburg, Kansas tornadic supercell. Mon. Wea. Rev., 140, 2103-2125.
  46. Thompson, E.T., L.J. Wicker and X. Wang 2012: Impact from a volumetric radar sampling operator for radial velocity observations within EnKF supercell assimilaion. J. Atmos. Oceanic Technol., 29, 1417-1427.
  47. Wang, Q.-W. and M.Xue, 2012: Convective initation on 19 June 2002 during IHOP: High-resolution simulations and analysis of the mesoscale structures and convection initiations. J. Geophy. Res., 117, D12107.
  48. Wang, S., M. Xue, and J. Min, 2012: A four-dimensional asynchronous ensemble square-root filter (4DEnSRF) and tests with simulated radar data. Quart. J. Roy. Meteor. Soc., DOI:10.1002/qj.1987.
  49. Wang, M., K. Zhao, W.-C. Lee, B.J.-D. Jou, and M. Xue, 2012: The gradient velocity track display (GrVTD) technique for retrieveing tropical cyclone primary circulation from aliased velocities measured by single Doppler radar. J. Atmos. Ocean. Tech., 29, 1026,1041.
  50. Wu, H.; R.F. Adler, Y. Hong, Y. Tian, and F. Policelli, 2012:  Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model.   Journal of Hydrometeorology, 13(4), 1268–1284.
  51. Wurman, J., D. Dowell, Y. Richardson, P. Markowski, D. Burgess, L. Wicker, and H. Bluestein 2012: The Second Verification of the Origins of Rotation in Tornadoes Experiment: VORTEX2. Bull. Amer. Meteor. Soc., 93, 1147-1170.
  52. Xu, X., Y. Wang, and M. Xue, 2012: Momentum flux and flux divergence of gravity waves in directional shear flows over three-dimensional mountains. J. Atmos. Sci., 69, 3733-3744.
  53. Yong, B.; Y. Hong, L.L. Ren, J.J. Gourley, G.J. Huffman, X. Chen, W. Wang, and S.I.Khan,  2012:  Assessment of evolving TRMM-based multisatellite real-time precipitation estimation methods and their impacts on hydrologic prediction in a high latitude basin.   Journal of Geophysical Research, 117(D9), D09108.
  54. Yong, B.; L.L. Ren, Y. Hong, J.J. Gourley, X. Chen, Y.J. Zhang, X.L. Yang, Z.X. Zhang, and W.G. Wang, 2012:  A novel multiple flow direction algorithm for computing the topographic wetness index.   Hydrology Research, 43(1-2), 135-145.
  55. Zahraei, A.; K-L. Hsu, S. Sorooshian, J.J. Gourley, V.  Lakshmanan, Y. Hong, and T. Bellerby, T.,  2012:  Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach.   Atmospheric Research, 118, 418–434.
  56. Zhao, K., X. Li, M. Xue, B.J.-D. Jou, and W.-C. Lee, 2012: Short-term forecasting through intermittent assimilation of data from Taiwan and Mainland China coastal radars for typhoon Meranti (2010) at landfall. J. Geophy. Res., 117, D06108.
  57. Zhao, K., M. Xue, and W.-C. Lee, 2012: Assimilation of GBVTD-retrieved winds from single-Doppler radar for short-term forecasting of Super Typhoon Saomai (0608) at landfall. Quart. J. Roy. Meteor. Soc., 138, 1055–1071.
  58. Zhu, J., F. Kong, and H. Lei, 2012: A regional ensemble forecast system for stratiform precipitation events in Northern China Region. Part I: A case study. Advances in Atmos. Sci., 29, 201-216.
    Zhu, Meijun and Dou, J., 2012: Two dimensional Lp Minkowski problem and nonlinear equations with negative exponents. Adv. Mat. 230, 1209-1221.

2011

  1. Bodine, D., Michaud, D., R.D. Palmer, P.L. Heinselman, J. Brotzge, N. Gasperoni, B.L. Cheong, M. Xue, and J. Gao, 2011: Understanding radar refractivity: Sources of uncertainty. J. Atmos. Ocean Tech., 50,2543-2560.
  2. Brotzge, J., S. Erickson and H. Brooks, 2011: A five-year climatology of tornado false alarms. Wea. Forecasting, 26, 534-544.
  3. Clark, A.J., J.S. Kain, P.T. Marsh, J. Correia, Jr., M. Xue and F. Kong, 2011: Forecasting Tornado Pathlengths Using a Three-Dimensional Object Identification Algorithm Applied to Convection-Allowing Forecasts. Wea. Forecasting, 27, 1090 - 1113.
  4. Clark, A.J., J.S. Kain, D.J. Stensrud, M. Xue, F. Kong, M.C. Coniglio, K.W. Thomas, Y. Wang, K. Brewster, J. Gao, X. Wang, S.J. Weiss, D. Bright, and J. Du, 2011: Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble. Mon. Wea. Rev., 139, 1410-1418.
  5. Clark, A.J., S.J. Weiss, J.S. Kain, I.L. Jirak, M. Coniglio, C.J. Melick, C. Siewert, R.A. Sobash, P.T. March, A.R., Dean, M. Xue, F. Kong, K.W. Thomas, Y. Wang, K. Brewster, J. Gao, X. Wang, J. Du, D.R. Novak, F.E. Barthold, M.J. Bodner, J.J. Levit, C.B. Entwistle, T.L. Jensen, J. Correia, J., 2011: An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment. Bull. Amer. Meteor. Soc., 93, 55-74.
  6. Dong, J., M. Xue, and K.K. Droegmeier, 2011: The analysis and impact of simulated high-resolution surface observations in addition to radar data for convective storms with an ensemble Kalman filter. Meteor, Atmos., Phy., 112, 41-61.
  7. Hoekstra, S.K. Klockow, R. Butterworth, J. Brotzge, S. Erickson, and H. Brooks, 2011: A social perspective of warn on forecast: Ideal tornado warning lead time and the general public's perceiptions of weather risks. Weather, Climate, and Society, 3, 128-140.
  8. Hu, X.-M., F. Zhang, G. Yu, J.D. Fuentes, and L. Wu, 2011: Contribution of mixed-phase boundary layer clouds to the termination of ozone depletion events in the Arctic, Geophys. Res. Lett 38, L21801, doi:1029/2011GL049229.
  9. Johnson, A., X. Wang, F. Kong, and M. Xue, 2011a: Hierarchical cluster analysis of a convection-allowing ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part I: Development of object-oriented cluster analysis method for precipitation fields. Mon. Wea. Rev., 139, 3673-3693.
  10. Johnson, A., X. Wang, F. Kong, and M. Xue, 2011b: Hierarchical cluster analysis of a cinvection-allowing ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part II: Season-long ensemble clustering and implication for implication for optimal ensemble design. Mon. Wea. Rev., 139, 3694-3710.
  11. Limpasuvan, V., M. Alexander, Y. Orsolini, D. Wu, M. Xue, J. Richter, and C. Yamashita, 2011: Mesoscale simulations of gravity waves during the 2009 major stratospheric suddent warming., J. Geophy. Res., In press.
  12. Nallapareddy, A., A. Shapiro, and J.J. Gourley, 2011: A climatology of nocturnal warming events associated with colf front passages in Oklahoma. J. Appl. Meteor. Climatol.,50,2042-2061.
  13. Potvin, C.K., A. Shapiro, M. Biggerstaff, and J. Wurman, 2011: The VDAC technique: A variational method for detecing and characterizing convective vortices in multiple-Dopper radar data. Mon. Wea. Rev., 139, 2593-2613.
  14. Potvin, C.K., A. Shapiro, and M. Xue, 2011: Impact of a vertical vorticity constraint in variational dual-Doppler wind analysis: Tests with real and simulated supercell data. J. Atmos. Oceanic Technol. ,139, 2593-2613.
  15. Shapiro, A., K.M. Willingham, and C.K. Potvin, 2010: Spatially variable advection correction of radar data. Part I: Theoretical considerations. J. Atmos. Sci., 67, 3445-3456.
  16. Shapiro, A., K. M. Winningham, and C.K. Potvin, 2010: Spatially variable advection correction of radar data. Part II: Test result. J. Atmos. Sci., 67, 3457-3470.
  17. Schenkman, A., M. Xue, A. Shapiro, K. Brewster, and J. Gao, 2011: Impact of CASA radar and Oklahoma mesonet data assimilation on the analysis and prediction of tornadic mesovortices in a MCS. Mon. Wea. Rev., 139, 3422-3445
  18. Schenkman, A., M. Xue, A. Shapiro, K. Brewster, and J. Gao, 2011: The analysis and prediction of the 8-9 May 2007 Oklahoma tornadic mesoscale convective system by assimilating WSR-88D and CASA radar data using 3DVAR. Mon. Wea. Rev., 139, 224-246.
  19. Snook, N., M. Xue, and J. Jung, 2011: Analysis of a tornadic mesoscale convective vortex based on Ensemble Kalman Filter assimliation of CASA X-band and WSR-88D radar data, Mon., Wea. Rev., 139, 3446-3468.
  20. Zhang, G., S. Luchs, A.V. Ryzhkov, M. Xue, L. Ryzhkova, and Q. Cao, 2011: Winter precipitation microphysics characterized by polarimetric radar and video disdrometer observations in central Oklahoma. J. Appl., Meteor. Climatol., 50, 1558-1570.
  21. Zhao, K., M. Xue, and W.-C. Lee, 2011: Assimilation of GBVTD-retrieved winds from single-Doppler radar for short-term forecasting of Super Typhoon Saomai (0608) at landfall,Quart. J. Roy. Meteor. Soc., DOI: 10.1002/qj.975.

2010

  1. Axelsen, S. L., A. Shapiro, E. Fedorovich, and H. van Dop, 2010: Analytical solution for katabatic flow induced by an isolated cold strip. Env. Fluid Mech., 10, 387-414.
  2. Brotzge, J., and S. Erickson, 2010: Tornadoes with no NWS warning.  Wea. Forecasting, 25, 159-172.
  3. Brotzge, J., K. Hondl, B. Philips, L. Lemon, E. Bass, D. Rude, and D. Andra, Jr., 2010: Evaluation of Distributed Collaborative Adaptive Sensing for detection of low-level circulations and implications for severe weather warning operations.  Wea. Forecasting, 25, 173-189.
  4. Burkholder, B., E Fedorovich, and A. Shapiro, 2010: Evaluating sub-grid scale models for large-eddy simulation of turbulent katabatic flow. In Quality and Reliability of Large- Eddy Simulations II, Springer, 149-160.
  5. Clark, A. J., W. A. Gallus Jr., M. Xue, and F. Kong, 2010: Growth of spread in convection-allowing and convection-parameterizing ensembles Wea. Forecasting, 25, 594-612.
  6. Clark, A.J., W.A. Gallus Jr., M. Xue, and F. Kong, 2010: Convection-allowing and convection-parameterizing ensemble forecasts of a mescoscale convective vortex and associated severe weather. Wea. Forecasting, 25, 1052-1081.
  7. Coniglio, M. C., K. L. Elmore, J. S. Kain, S. Weiss, and M. Xue, 2010: Evaluation of WRF model output for severe-weather forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment. Wea. Forecasting, 25, 408-427.
  8. Dawson, D. T., II, M. Xue, J. A. Milbrandt, and M. K. Yau, 2010: Comparison of evaporation and cold pool development between single-moment and multi-moment bulk microphysics schemes in idealized simulations of tornadic thunderstorms. Mon. Wea. Rev., 138, 1152-1171..
  9. Ge, G., J. Gao, K. Brewster, and M. Xue, 2010: Impacts of beam broadening and earth curvature on 3D variational radar data assimilation with two Doppler radars. J. Atmos. Ocean Tech., 27, 617-636.
  10. Hacker, J.P., S.-Y. Ha, C. Snyder, J. Berner, F.A. Eckel, E. Kuchera, M. Pocernich, S. Rugg, J. Schramm, and X. Wang, 2010: The U.S. Air Forece Weather Agency's mesoscale ensemble: Scientific description and performance resulst. Tellus, in press,
  11. LaDue, D., Heinselman, P., Newman, Jennifer, 2010: Strengths and Limitations of Current Radar Systems for Two Stakeholder Groups in Southern Plains. Bull. Am.Meteor. Soc., 91, 899-910.
  12. Jung, Y., M. Xue, and G. Zhang, 2010: Simultaneous estimation of microphysical parameters and atmospheric state using simulated polarimetric radar data and ensemble Kalman filter in the presence of observation operator error, Mon. Wea. Rev., 138, 539-562.
  13. Jung, Y., M. Xue, and G. Zhang, 2010: Simulations of polarimetric radar signatures of a supercell storm using a two-moment bulk microphysics scheme. J. Appl. Meteor. Climatol., 49, 146-163.
  14. Kain, J. S., M. Xue, M. C. Coniglio, S. J. Weiss, F. Kong, T. L. Jensen, B. G. Brown, J. Gao, K. Brewster, K. W. Thomas, Y. Wang, C. S. Schwartz, and J. J. Levit, 2010: Assessing advances in the assimilation of radar data within a collaborative forecasting-research environment. Wea. Forecasting, 25, 1510-1521.
  15. Karanl, H., P. J. Fitzpatrick, C.M. Hill, Y. Li, Q. Xiao, E. Lim, 2010: The Formation of Multiple Squall Lines and the Impact of WSR-88D Radial Winds in a WRF simulation Northern Gulf Institute. Weather and Forecast, 25, 242-262.
  16. Schenkman, A., M. Xue, A. Shapiro, K. Brewster, and J. Gao, 2010: Impact of radar data assimilation on the analysis and prediction of the 8-9 May 2007 Oklahoma tornadic mesoscale convective system, Part II: Sub-storm-scale mesovortices on a 400 m Grid. Mon. Wea. Rev.,139, 224-246.
  17. Schwartz, C. S., J. S. Kain, S. J. Weiss, M. Xue, D. R. Bright, F. Kong, K. W. Thomas, J. J. Levit, M. C. Coniglio, M. S. Wandishim, 2010: Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Weather and Forecasting, 25, 263-280.
  18. Shapiro, A., and E. Fedorovich, 2010: Analytical description of a nocturnal low-level jet. Q. J. Roy. Met. Soc., 136, 1255-1262.
  19. Xue, M., Y. Jung, and G. Zhang, 2010: State estimation of convective storms with a two-moment microphysics scheme and ensemble Kalman filter: Experiments with simulated radar data Q. J. Roy. Meteor. Soc, 136, 685-700..
  20. Wang, X., 2010: Incorporating ensemble covariance in the Gridpoint Statistical Interpolation (GSI) variational minimization: a mathematical framework. Mo. Wea.Rev., 138, 2990-2995.

2009

  1. Bodine, D., P. M. Klein, S. C. Arms, and A. Shapiro, 2009: Variability of surface air temperature over gently-sloped terrain. J. Appl. Meteor. Climatol., 48, 1117–1141.
  2. Brewster, K.A.,  F.H. Carr, J. Gao, W. Lapenta, G. Jedlovic, 2009:  Impact of the Assimilation of AIRS Soundings and AMSR-E Rainfall on Short Term Forecasts of Mesoscale Weather, Final Report to NASA Grant NNG04GM66G, 36 pp.
  3. Brewster, K.A., K.C. Crawford, J.E. Hocker, R. McPherson, W.G. McPherson, Jr., K.L. Nemunaitis, M. Sumpor, and contributors.  K.C. Crawford Project Director, 2009: DHMZ Modernization Project: Final Report for the Meteorological and Hydrological Service of the Republic of Croatia.  410 pp.
  4. Brotzge, J., and S. Erickson, 2009: NWS tornado warnings with zero or negative lead times.  Wea. Forecasting, 24, 140-154.
  5. Burkholder, B., A. Shapiro, and E. Fedorovich, 2009: Katabatic flow induced by a cross-slope band of surface cooling. Acta Geophys., 57, 923–949.
  6. Carbone, R.E., J. Block, S. E. Boselly, G. R. Carmichael, F. H. Carr, V. Chandrasekar, E. Gruntfest, R. M. Hoff, W. F. Krajewski, M. A. LeMone, J. F. W. Purdom, T. W. Schlatter, E. S. Takle, and J. Titlow, 2009: "Observing Weather and Climate from the ground up: A Nationwide Network of Networks". The National Academies Press, Washington, D.C. 234 pp.
  7. Clark, A. J., W. A. Gallus, Jr., M. Xue, and F. Kong, 2009: A comparison of precipitation forecast skill between small near-convection-permitting and large convection-parameterizing ensembles. Wea. and Forecasting, 24, 1121-1140.
  8. Dunning, T. H., Jr., K. Schulten, J. Tromp, J. P. Ostriker, K. K. Droegemeier, M. Xue, and P. Fussell, 2009: Science and engineering in the petascale era. Computing Sci. Engineering, 11, 28-36.
  9. Fedorovich, E., and A. Shapiro, 2009: Structure of numerically simulated katabatic and anabatic flows along steep slopes. Acta Geophys. 57, 981–1010.
  10. Fedorovich, E. and A. Shapiro, 2009: Turbulent natural convection along a vertical plate immersed in a stably stratified fluid. J. Fluid Mech., 636, 41–57.
  11. Fedorovich, E., and A. Shapiro, 2009: Turbulence and waves in numerically simulated slope flows. Mécanique et Industries, 10, 175–179.
  12. Gagne, D.J., A. McGovern, and J. Brotzge 2009: Classification of convective areas using decision trees. J. Atmos. Ocean. Technol., 26, 140-154.
  13. McLaughlin, D., D. Pepyne, V. Chandrasekar, B. Philips, J. Kursoe, et al., 2009: Short-wavelength technology and the potential for distributed networks of small radar systems. Bull. Amer. Meteor. Soc., 90, 1797-1817.
  14. McPherson, R., K. Brewster, K.C. Crawford, J. Hocker, L. Lemon, W.G. McPherson, Jr., 2009: Needs Assessment for the Meteorological and Hydrological Service Modernization Project of the Republic of Croatia.  97 pp.
  15. Schwartz, C., J. Kain, S. Weiss, M. Xue, D. Bright, F. Kong, K. Thomas, J. Levit, and M. Coniglio, 2009: Next-day convection-allowing WRF model guidance: A second look at 2 vs. 4 km grid spacing. Mon. Wea. Rev., 137, 3351-3372
  16. Sheng, C., M. Xue, and S. Gao, 2009: The structure and evolution of sea breezes during Qingdao Olympics sailing test event in 2006. Adv. Atmos. Sci., 26, 132–142.
  17. Shapiro, A., P. M. Klein, S. C. Arms, D. Bodine and M. Carney, 2009: The Lake Thunderbird Micronet Project, Bull. Amer. Meteor. Soc., 90, 811–823.
  18. Shapiro, A., and E. Fedorovich, 2009: Nocturnal low-level jet over a shallow slope, Acta Geophys., 57, 950–980.
  19. Shapiro, A., C. K. Potvin, and J. Gao, 2009: Use of a vertical vorticity equation in variational dual-Doppler wind analysis, J. Atmos. Oceanic Technol., 26, 2089–2106.
  20. Stensrud, D. J., M. Xue, L. Wicker, K. Kelleher, M. Foster, J. Schaefer, R. Schneider, S. Benjamin, J. Ferree, J. Tuell, and J. Hayes, 2009: Convective-scale Warn on Forecast: A vision for 2020. Bull. Am. Meteor. Soc., Bull. Am. Meteor. Soc., 90, 1487-1499.
  21. Potvin, C. K., A. Shapiro, T.-Y. Yu, J. Gao, and M. Xue, 2009: Using a low-order model to characterize and detect tornadoes in multiple-Doppler radar data. Mon. Wea. Rev., 137, 1230–1249.
  22. Wang, X., T. M. Hamill, J. S. Whitaker, C. H. Bishop, 2009: A comparison of the hybrid and EnSRF analysis schemes in the presence of model error due to unresolved scales. Mon. Wea. Rev.,137, 3219-3232.
  23. Xue, M., M. Tong, and G. Zhang, 2009: Simultaneous state estimation and attenuation correction for thunderstorms with radar data using an ensemble Kalman filter: Tests with simulated data. Quart. J. Royal Meteor. Soc., 135, 1409-1423.
  24. Zhao, K. and M. Xue, 2009: Assimilation of coastal Doppler radar data with the ARPS 3DVAR and cloud analysis for the prediction of Hurricane Ike (2008). Geophy. Res. Letters, 36, L12803, doi:10.1029/2009GL038658.

2008

  1. Cheong, B. L., R. D. Palmer, and M. Xue, 2008: A time-series weather radar simulator based on high-resolution atmospheric models. J. Atmos. Ocean. Tech., 25, 230-243.
  2. Gao, J. and M. Xue, 2008: An efficient dual-resolution approach for ensemble data assimilation and tests with assimilated Doppler radar data. Mon. Wea. Rev., 136, 945-963.
  3. Gao, J., K. Brewster, and M. Xue, 2008: Sensitivity of radio reflectivity to moisture and temperature and its influnce on radar ray path. Adv. Atmos. Sci.,  25, 1098-1106.
  4. Gao, S., S. Yang, M. Xue, and C. Cui, 2008: The total deformation and its role in heavy precipitation events associated with deformation-dominant flow patterns. Adv. Atmos. Sci., 25, 11-23.
  5. Jung, Y., G. Zhang, and M. Xue, 2008: Assimilation of simulated polarimetric radar data for a convective storm using ensemble Kalman filter. Part I: Observation operators for reflectivity and polarimetric variables. Mon. Wea. Rev., 136, 2228–2245.
  6. Jung, Y., M. Xue, G. Zhang, and J. Straka, 2008: Assimilation of simulated polarimetric radar data for a convective storm using ensemble Kalman filter. Part II: Impact of polarimetric data on storm analysis. Mon. Wea. Rev., 136, 2246–2260.
  7. Kain, J. S., S. J. Weiss, D. R. Bright, M. E. Baldwin, J. J. Levit, G. W. Carbin, C. S. Schwartz, M. Weisman, K. K. Droegemeier, D. Weber, and K. W. Thomas, 2009: Some practical considerations for the first generation of operational convection-allowing NWP: How much resolution is enough? Wea. Forecasting, 23, 931–952.
  8. Liu, C., Q. Xiao, and B. Wang, 2008: An Ensemble-Based Four Dimensional Variational Data Assimilation Scheme: Part I: Technical Formulation and Prelimary Test. Mon. Wea. Rev., 136, 3363-3373.
  9. Liu, C., Q. Xiao, and B. Wang, 2008: An Ensemble-Based Four Dimensional Variational Data Assimilation Scheme: Part II: Observing System Simulation Experiments with Advanced Research WRF (ARW). Mon. Wea.Rev., 137, 1687-1704.
  10. Liu, H. and M. Xue, 2008: Prediction of convective initiation and storm evolution on 12 June 2002 during IHOP. Part I: Control simulation and sensitivity experiments. Mon. Wea. Rev., 136, 2261-2283.
  11. Loftus, A., D. Weber, and C. A. Doswell, III, 2008: Parameterized mesoscale forcing mechanisms for initiating numerically-simulated isolated multicellular convection. Mon. Wea. Rev., 136, 2408–2421.
  12. Shapiro, A., and E. Fedorovich, 2008: Coriolis effects in homogeneous and inhomogeneous katabatic flows. Q. J. Roy. Met. Soc., 134, 353–370.
  13. McLaughlin, D., D. Pepyne, V. Chandrasekar, B. Philips, J. Kurose, M. Zink, K. Droegemeier, S. Cruz-Pol, F. Junyent, J. Brotzge, D. Westbrook, N. Bharadwaj, Y. Wang, E. Lyons, K. Hondl, Y. Liu, E. Knapp, M. Xue, A. Hopf, K. Kloesel, A. DeFonzo, P. Kollias, K. Brewster, R. Contreras, T. Djaferis, E. Insanic, S. Frasier, and F. Carr, 2009: Short-wavelength technology and the potential for distributed networks of small radar systems. Bull. Amer. Meteor. Soc.,Bull. Amer. Meteor. Soc., 90, 1797-1817.
  14. Proud, J. L., K. K. Droegemeier, V. T. Wood, and R. A. Brown, 2009: Sampling Strategies for Tornado and Mesocyclone Detection Using Dynamically Adaptive Doppler Radars: A Simulation Study. J. Atmos. Ocean. Tech., 26, 492-507.
  15. Tanamachi, R. L., W. Feltz, and M. Xue, 2008: Observations and numerical simulation of a water vapor oscillation event during the International H2O Project (IHOP_2002). Mon. Wea. Rev., 136, 3106-3120.
  16. Tong, M. and M. Xue, 2008: Simultaneous estimation of microphysical parameters and atmospheric state with radar data and ensemble Kalman filter. Part I: Sensitivity analysis and parameter identifiability. Mon. Wea. Rev., 136, 1630-1648.
  17. Tong, M. and M. Xue, 2008: Simultaneous estimation of microphysical parameters and atmospheric state with radar data and ensemble Kalman filter. Part II: Parameter estimation experiments. Mon. Wea. Rev., 136, 1649-1668.
  18. Wang, X., D. Barker, C. Snyder, T.M. Hamill, 2008: A hybrid ETKF-3DVAR data assimilation scheme for the WRF model. Part I: observing system simulation experiement. Mon. Wea. Re., 136, 5116-5131.
  19. Wang, X., D. Barker, C. Snyder, T.M. Hammill, 2008: A hybrid ETKF-3DVAR data assimilation scheme for the WRF model Part II: real observation experiments. Mon. Wea. Rev., 136, 5132-5147.
  20. Wang, Y., T.-Y. Yu, M. Yeary, A. Shapiro, S. Nemati, M. Foster, D. L. Andra, Jr. and M. Jain, 2008: Tornado detection using a neuro-fuzzy system to integrate shear and spectral signatures. J. Atmos. Oceanic Technol., 25, 1136–1148.
  21. White, L., A. Shapiro, and F. White, 2008: Radar placement based on a geometric uncertainty multiplier reduction criterion. Comput. Optim. Appl., 41, 61–80.
  22. Xu, Q., H. Lu, S. Gao, M. Xue, and M. Tong, 2008: Time-expanded sampling for ensemble Kalman filter: Assimilation experiments with simulated radar observations. Mon. Wea. Rev., 136, 2651-2667.
  23. Zhang, G., M. Xue, Q. Cao, and D. Dawson, 2008: Diagnosing the intercept parameter for exponential raindrop size distribution based on video disdrometer observations. J. Appl. Meteor. Climatol., 47, 2983-2992.

2007

  1. Brotzge, Jerry; Droegemeier, Kelvin, 2006: CASA and LEAD: Adaptive CyberInfrastructure for Real-Time Multiscale Weather Forecasting, IEEE Computer Society, 66-74.
  2. Chu, K., Z.-M. Tan, and M. Xue, 2007: Impact of four-dimensional variational assimilation of rainfall data on precpitation forecast of mesoscale convective systems in a meiyu heavy rainfall event. Adv. Atmos. Sci., 24, 281-300
  3. Hu, M. and M. Xue, 2007: Impact of configurations of rapid intermittent assimilation of WSR-88D radar data for the 8 May 2003 Oklahoma City tornadic thunderstorm case. Mon. Wea. Rev., 135, 507–525.
  4. Hu, M. and M. Xue, 2007: Initializing convection using cloud analysis and radar data in grid-point statistical interpolation (GSI) system and impact on the forecast of advanced research WRF. Geophy. Res. Letters. 34, L07808, doi:10.1029/2006GL028847.
  5. Keith, R. and S. M. Leyton, 2007: An experiment to measure the value of statistical probability forecasts for airports.  Wea. Forecasting. 22, 928-935.
  6. Kelleher, K., K.K. Droegemeier and co-authors, 2007:  Project CRAFT:  Technical Aspects of a Real Time Delivery System for NEXRAD Level II Data via the Internet.  Bull. Amer. Meteor. Soc., 88, 1045-1057.
  7. Kong, F., K.K. Droegemeier and N.L. Hickmon, 2007:  Multiresolution ensemble forecasts of an observed tornadic thunderstorm system, Part II.  Mon. Wea. Rev., 135, 759-782.
  8. Limpasuvan, V., D. L. Wu, M. J. Alexander, M. Xue, M. Hu, S. Pawson, and J. R. Perkins, 2007: The ARPS stratospheric gravity wave simulation over Greenland during 24 January 2005. J. Geo. Res., 112, D10115, doi:10.1029/2006JD007823.
  9. Liu, S., M. Xue, and Q. Xu, 2007: Using wavelet analysis to detect tornadoes from Doppler radar radial-velocity observations. J. Atmos. Ocean Tech., 24, 344-359.
  10. Liu, H., M. Xue, R. J. Purser, and D. F. Parrish, 2007: Retrieval of moisture from GPS slant-path water vapor observations using 3DVAR with isotropic and anisotropic recursive filters. Mon. Wea. Rev., 135, 1506–1521.
    Martin, W. J., and A. Shapiro, 2007:  Discrimination of bird and insect radar echoes in clear-air using high-resolution radars.  J. Atmos. and Oceanic Technol., 24, 1215-1230.
  11. May, R. M., M. I. Biggerstaff, and M. Xue, 2007: A Doppler radar emulator with an application to the detectability of tornadic signatures. J. Atmos. Ocean Tech., 1973-1996.
  12. Richardson, Y.P., K.K. Droegemeier and R.P. Davies-Jones, 2007:  The influence of horizontal environmental variability on numerically-simulated convective storms, Part I:  Variations in vertical shear.  Mon. Wea. Rev., 135, 3429-3455.
  13. Shapiro, A., and E. Fedorovich, 2007:  Katabatic flow along a differentially-cooled sloping surface.  J. Fluid Mech., 571, 149-175.
  14. Wang, X., T. M. Hammill, and C.H. Bishop, 2007: A comparison of hybrid ensemble transform Kalman filter-OI and ensemble square-root filter analysis schemes. Mon. Wea. Rev., 135, 1055-1076.
  15. Wang, X., C. Snyder, and T.M. Hammill, 2007: On the theoretical equivalence of differently proposed ensemble/3D-Var hybrid analysis schemes. Mon. Wea. Rev., 135, 222-227.
  16. White, L., and A. Shapiro, 2007:  Radar network scanning coordination based on ensemble transform Kalman filtering variance optimization.  Applied Mathematics and Computation, 188, 1285-1309.
  17. White, L., and A. Shapiro, 2007:  Optimization of radar scanning strategies using an ensemble relative error criterion.  Applied Mathematics and Computation, 188, 693-712.
  18. Xue, M., K. K. Droegemeier, and D. Weber, 2007: Numerical prediction of high-impact local weather: A driver for petascale computing. In Petascale Computing: Algorithms and Applications, D. Bader, Ed., Taylor & Francis. 103-124.
  19. Xue, M., Y. Jung, and G. Zhang, 2007: Error modeling of simulated reflectivity observations for ensemble Kalman filter data assimilation of convective storms. Geophys. Res. Letters, 34, L10802, doi:10.1029/2007GL029945.
  20. Xue, M., S. Liu, and T. Yu, 2007: Variational analysis of over-sampled dual-Doppler radial velocity data and application to the analysis of tornado circulations. J. Atmos. Ocean Tech., 24, 403–414.
  21. Yu, T.-Y., Y. Wang, A. Shapiro, M. Yeary, D. Zrnic, and R. J. Doviak, 2007:  Characterization of tornado spectral signatures using higher order spectra.  J. Atmos. and Oceanic Technol., 24, 1997-2013.
  22. Zrnic, D. S., J. F. Kimpel, D. E. Forsyth, A. Shapiro, G. Crain, R. Ferek, J. Heimmer, W. Benner, T. J. McNellis, and R. J. Vogt, 2007:  Agile beam phased array radar for weather observations.  Bull. Amer. Meteor. Soc., 88, 1753-1766.

2006

  1. Brotzge, Jerry; Droegemeier, Kelvin, 2006: CASA and LEAD: Adaptive CyberInfrastructure for Real-Time Multiscale Weather Forecasting, IEEE Computer Society, 66-74.
  2. Brotzge, J., K.K. Droegemeier, and D.J. McLaughlin, 2006:  Collaborative Adaptive Sensing of the Atmosphere (CASA): New radar system for improving analysis and forecasting of surface weather conditions.  J. Transport. Res. Board, No. 1948, 145-151.
  3. Chow, F. K., A. P. Weigel, R. L. Street, M. W. Rotach, and M. Xue, 2006: High-resolution large-eddy simulations of flow in a steep Alpine valley. Part I: Methodology, verification and sensitivity experiments. J. Appl. Meteor., 45, 63-86.
  4. Dawson, D. T., II and M. Xue, 2006: Numerical forecasts of the 15-16 June 2002 Southern Plains severe MCS: Impact of mesoscale data and cloud analysis. Mon. Wea. Rev., 134, 1607-1629.
  5. Gao, J., K. Brewster, and M. Xue, 2006: A comparison of the radar ray path equations and approximations for use in radar data assimilation. Adv. Atmos. Sci., 32, 190-198.
  6. Gao, J., M. Xue, S. Y. Lee, K. K. Droegemeier, and A. Shapiro, 2006: A three-dimensionl variational method for velocity retrievals from single-Doppler radar observations on supercell storms. Meteo. Atmos. Phys., 94, 11-26.
  7. Hu, M., M. Xue, and Keith Brewster, 2006: 3DVAR and cloud analysis with WSR-88D Level-II data for the prediction of the Fort Worth tornadic thunderstorms. Part I: Cloud analysis and its impact. Mon. Wea. Rev., 134, 675-698.
  8. Hu, M., M. Xue, J. Gao and K. Brewster, 2006: 3DVAR and cloud analysis with WSR-88D Level-II data for the prediction of the Fort Worth tornadic thunderstorms. Part II: Impact of radial velocity analysis via 3DVAR. Mon. Wea. Rev., 134, 699-721
  9. Kong, F., K. K. Droegemeier, and N. L. Hickmon, 2006: Multi-resolution ensemble forecasts of an observed tornadic thunderstorm system, Part I: Comparison of coarse and fine-grid experiments. Mon. Wea. Rev., 134, 807-833.
  10. Liu, H. and M. Xue, 2006: Retrieval of moisture from slant-path water vapor observations of a hypothetical GPS network using a three-dimensional variational scheme with anisotropic background error. Mon. Wea. Rev., 134, 933-949.
  11. Martin, W. J. and M. Xue, 2006: Initial condition sensitivity analysis of a mesoscale forecast using very-large ensembles. Mon. Wea. Rev., 134, 192–207.
  12. Nascimento, E. and K.K. Droegemeier, 2006:  Dynamic adjustment in a numerically simulated mesoscale convective system:  Impact of the wind field.  J. Atmos. Sci., 63, 2246-2268.
  13. Plale, B., D. Gannon, J. Brotzge, K.K. Droegemeier and Co-Authors, 2006:  CASA and LEAD:  Adaptive cyberinfrastructure for real-time multiscale weather forecasting.  IEEE Computer, 39, 66-74.
  14. Shapiro, A. 2006: An analytical solution of the Navier-Stokes equations for unsteady backward stagnation-point flow with injection or suction. Zamm-Zeitschrift Fur Angewandte Mathematik Und Mechnik, 86, 281-290.
  15. Shapiro, A., 2006:  An analytical solution of the Navier-Stokes equations for unsteady backward stagnation-point flow with injection or suction.  J. Appl. Math. Mech. (ZAMM), 86, 281-290.
  16. Shapiro, A and E. Fedorovich, 2006: Natural convection in a stably stratified fluid along vertical plates and cylinders with temporally periodic surface temperature variations. J. Fluid Mech., 546, 295-311.
  17. Sheng, C., S. Gao, and M. Xue, 2006: Short-term prediction of a heavy precipitation event by assimilating Chinese CINRAD radar reflectivity data using complex cloud analysis. Meteor. Atmos. Phy., 94, 167-183.
  18. Wei, M., Z. Toth, R. Wobus, Y. Zhu, C.H. Bishop and W. Wang, 2006: Ensemble transform Kalman filter-based ensemble perturbations in an operational global prediction system at NCEP. Tellus, 58A, 28-44.
  19. Weigel, A. P., F. K. Chow, M. W. Rotach, R. L. Street, and M. Xue, 2006: High-resolution large-eddy simulations of flow in a steep Alpine valley. Part II: Flow structure and heat budgets. J. Appl. Meteor., 45, 87-107.
  20. Xu, Q., S. Liu, and M. Xue, 2006: Background error covariance functions for vector wind analysis using Doppler radar radial-velocity observations. Quart. J. Roy. Meteor. Soc., 132, 2887-2904.
  21. Xue, M. and W. Martin, 2006: A high-resolution modeling study of the 24 May 2002 case during IHOP. Part I: Numerical simulation and general evolution of the dryline and convection. Mon. Wea. Rev., 134, 149–171.
  22. Xue, M. and W. Martin, 2006: A high-resolution modeling study of the 24 May 2002 case during IHOP. Part II: Horizontal convective rolls and convective initiation. Mon. Wea. Rev., 134, 172–191.
  23. Xue, M., M. Tong, and K. K. Droegemeier, 2006: An OSSE framework based on the ensemble square-root Kalman filter for evaluating impact of data from radar networks on thunderstorm analysis and forecast. J. Atmos. Ocean Tech., 23, 46–66.
  24. Yeary, M., Y. Zhai, T.-Y. Yu, S. Nematifar, and A. Shapiro, 2006:  Spectral calculations and target tracking for remote sensing,  IEEE Transactions on Instrumentation and Measurement, 55, (4), 1430-1442.

2005

  1. Adlerman, E. J. and K. K. Droegemeier, 2005: The dependence of numerically simulated cyclic mesocyclogenesis upon environmental vertical wind shear. Mon. Wea. Rev. , 133, 3595-3623.
  2. Chow, F. K., R. L. Street , M. Xue, and J. H. Ferziger, 2005: Explicit filtering and reconstruction turbulence modeling for large-eddy simulation of neutral boundary layer flow. J. Atmos. Sci. , 62, 2058-2077.
  3. Dabberdt, W. F., T. W. Schlatter, F. H. Carr, E. W. Joe Friday, D. Jorgensen, S. Koch, M. Pirone, F. M. Ralph, J. Sun, P. Welsh, J. W. Wilson, and X. Zou, 2005: Multifunctional mesoscale observing networks. Bull. Amer. Meteor. Soc., 86, 961-982.
  4. Droegemeier, K. K., K. Brewster, M. Xue, D. Weber, D. Gannon, B. Plale, D. Reed, L. Ramakrishnan, J. Alameda, R. Wilhelmson, T. Baltzer, B. Domenico, D. Murray, M. Ramamurthy, A. Wilson, R. Clark, S. Yalda, S. Graves, R. Ramachandra, J. Rushing, E. Joseph, and V. Morris, 2005: Service-oriented environments for dynamically interacting with mesoscale weather. Computing in Science and Engineering, 7, 12-27.
  5. Gonzalez-Espada, W. and D. S. Zaras, 2005: Evaluation of the Impact of the NWC REU program compared with other undergraduate research experiences. J. Geosci. Edu., 54, 541-549.
  6. Martin, W. J., and A. Shapiro, 2005: Impact of radar tilt and ground clutter on wind measurements in clear air. J. Atmos. and Oceanic Technol., 22, 649-663.
  7. Shapiro, A., 2005: Drag-induced transfer of horizontal momentum between air and raindrops. J. Atmos. Sci., 62, 2205-2219.
  8. Shapiro, A., and E. Fedorovich, 2005: Analytical and numerical study of natural convection in a stably stratified fluid along vertical plates and cylinders with temporally-periodic surface temperature variations. Progress in Computational Heat and Mass Transfers, Vol. 1, R. Bennacer, A. A. Mohamad, M. El Ganaoui, J. Sicard, Eds., Lavoisier, 77-82.
  9. Smedsmo, J. L., E. Foufoula-Georgious, V. Vuruputur, F. Kong, and K. K. Droegemeier, 2005: On the vertical structure of modeled and observed clouds: Insights for rainfall retrieval and microphysical parameterization. J. Appl. Meteor., 44, 1866-1884.
  10. Tong, M. and M. Xue, 2005: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSSE Experiments. Mon. Wea. Rev., 133, 1789-1807.
  11. Wang, X., and C.H. Bishop, 2005: Improvement of ensemble reliability with a new dressing kernal. Q.J.R. Meteo. Soc., 131, 965-986.
  12. White, L., and A. Shapiro, 2005: Optimization of wind field retrieval procedures. Applied Math. Computation. 171, 25-52.
  13. Xiao, Y., M. Xue, W. J. Martin, and J. Gao, 2005: Development of an adjoint for a complex atmospheric model, the ARPS, using TAF. In Automatic Differentiation: Applications, Theory, and Implementations, H. M. Bücker, G. F. Corliss, P. Hovland, U. Naumann, and B. Norris, Eds., Springer, 263-272.

2004

  1. Brotzge, J.A., 2004: A two-year comparison of the surface water and energy budgets between two OASIS sites and NCEP-NCAR reanalysis data. J. Hydrometeor., 5,311-326.
  2. Gao, J. and K. K. Droegemeier, 2004: A variational technique for dealising Doppler radial velocity data. J. Appl. Meteor. , 42, 934-940.
  3. Gao, J.-D., K. K. Droegemeier, J.-D. Gong, and Q. Xu, 2004: A method for retrieving mean horizontal wind profiles from single-Doppler radar observations contaminated by aliasing. Mon. Wea. Rev. , 132, 1399-1409.
  4. Gao, J.-D., M. Xue, K. Brewster, and K. K. Droegemeier, 2004: A three-dimensional variational data analysis method with recursive filter for Doppler radars. J. Atmos. Ocean . Tech. , 21, 457-469.
  5. Nutter, P., D. Stensrud, and M. Xue, 2004: Effects of coarsely-resolved and temporally-interpolated lateral boundary conditions on the dispersion of limited-area ensemble forecasts. Mon. Wea. Rev. , 132, 2358-2377.
  6. Nutter, P., M. Xue, and D. Stensrud, 2004: Application of lateral boundary condition perturbations to help restore dispersion in limited area ensemble forecasts. Mon. Wea. Rev. , 132, 2378-2390.
  7. Plale, B., J. Alameda, R. Wilhelmson, D. Gannon, S. Hampton, A. Rossi, and K.K. Droegemeier, 2004:  User-oriented active management of scientific data with my LEAD.  IEEE Internet Computing, 9, 27-34.
  8. Ren, D. and M. Xue, 2004: A revised force-restore model for land-surface modeling. J. App. Meteor. , 43, 1768-1782.
  9. Ren, D., M. Xue, and A. Henderson-Sellers, 2004: The effects of hydraulic lift in simulating superficial soil moisture for vegetated surfaces under dry conditions. J. Hydrometero. , 5, 1181-1191.
  10. Shapiro, A. and E. Fedorovich, 2004: Unsteady convectively driven flow along a vertical plate immersed in a stably stratified fluid. J. Fluid Mech., 498, 333-352.
    11. Shapiro, A. and E. Fedorovich, 2004: Prandtl number dependence of unsteady natural convection along a vertical plate in a stably stratified fluid. Int. J. Heat Mass Transfer. 47, 4911-4927.
  11. Sharif, H. O., F. L. Ogden, W. F. Krajewski, and M. Xue, 2004: Statistical analysis of radar-rainfall error propagation. J. Hydrometero. , 5, 199-212.
  12. Spencer, P. L. and J. Gao, 2004: Can gradient information be used to improve variational objective analysis? Mon. Wea. Rev. , 132, 2977-2994.
  13. Wang, X., C.H. Bishop, and Simon J. Julier, 2004: Which is better, an ensemble of positive-negative pairs or a centered spherical simplex ensemble? Mon. Wea. Rev., 132, 1590-1605.

2003

  1. Brewster, Keith A. 2003: Phase-Correcting Data Assimilation and Application to Storm-Scale Numerical Weather Prediction. Part I: Method Description and Simulation Testing. Monthly Weather Review: Vol. 131, No. 3, pp. 480-492.
  2. Brewster, Keith A. 2003: Phase-Correcting Data Assimilation and Application to Storm-Scale Numerical Weather Prediction. Part II: Application to a Severe Storm Outbreak. Monthly Weather Review: Vol. 131, No. 3, pp. 493-507.
  3. Brooks, H., C. Doswell III, D. Dowell, R. Holle, R. Johns, D. Jorgensen, D. Schultz, D. Stensrud, S. Weiss, L. Wicker, and D. S. Zaras, 2003: Severe Thunderstorms and Tornadoes. Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, T. D. Potter and B. R. Colman, Eds., Wiley-Interscience, 575-619.
  4. Brotzge, J.A., and K.C. Crawford, 2003: Examination of the surface energy budget as observed from OASIS (eddy correlation) and ARM (Bowen ratio) measurement systems., J. Hydrometeor., 4, 160-178.
  5. Brotzge, J.A., and S. J. Richardson, 2003: Spatial and temporal correlation among Oklahoma Mesonet and OASIS surface-layer measurements. J. Meteor., 42, 5-19.
  6. Dowell, D. C., and A. Shapiro, 2003: Stability of an iterative dual-Doppler wind synthesis in Cartesian coordinates. J. Atmos. and Oceanic Technol., 20, 1552-1559.
  7. Fiebrich, C.J., Martinez, J. Brotzge, and J. Basara, 2003: The Oklahoma Mesonet's skin temperature network. J. Atmos. Ocean. Tech., 20, 1496-1504.
  8. Shapiro, A., P. Robinson, J. Wurman, and J. Gao, 2003: Single-Doppler velocity retrieval with rapid scan radar data. J. Atmos. and Oceanic Technol., 20, 1758-1775.
  9. Souto, M. J., Balseiro, C. F., Pérez-Muñuzuri, V., Xue, M., Brewster, K. 2003: Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain. Journal of Applied Meteorology: Vol. 42, No. 1, pp. 129-140.
  10. Wang, X., and C.H. Bishop, 2003: A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci, 60, 1140-1158.
  11. Xue, M., D.-H. Wang, J.-D. Gao, K. Brewster, and K. K. Droegemeier, 2003: The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteor. Atmos. Physics, 82, 139-170.

2002

  1. Adlerman, E.J. and K.K. Droegemeier, 2002: The sensitivity of numerically-simulated cyclic mesocyclogenesis to variations in model physical and computational parameters. Monthly Weather Review: Vol. 130, No. 11, pp. 2671-2691.
  2. Brotzge, J.A., and D. Weber, 2002: Land-surface scheme validation using the Oklahoma Atmospheric Surface-layer Instrumentation Syste (OASIS) and Oklahoma Mesonet data: Preliminary results. Meteor. Atmos. Phys., 80, 189-206.
  3. Lazarus, Steven M., Ciliberti, Carol M., Horel, John D., Brewster, Keith A. 2002: Near-Real-Time Applications of a Mesoscale Analysis System to Complex Terrain. Weather and Forecasting: Vol. 17, No. 5, pp. 971-1000.
  4. Mewes, J. J., and A. Shapiro, 2002: On the use of the vorticity equation in dual-Doppler Analysis of the vertical velocity field. J. Atmos. And Oceanic Technol., 19, 543-567.
  5. Shapiro, A. and K. M. Kanak, 2002: Vortex formation in ellipsoidal bubbles. J. Atmos. Sci., 59, 2253-2269.
  6. Sharif, H. O., F. L. Ogden, W. F. Krajewski, and M. Xue, 2002: Numerical simulations of radar-rainfall error propagation. Water Resources Research, 38, 15-1 to 15-14.
  7. Sridhar, V., R.L. Elliott, F. Chen, and J. Brotzge, 2002: Validation of the NOAH-OSU land surface model using surface flux measurements in Oklahoma. J. Geophys. Res., 107, 4418-4436.
  8. Weygandt, S. S., A. Shapiro and K. K. Droegemeier, 2002: Retrieval of initial forecast Fields from single-Doppler observations of a supercell thunderstorm. Part I Single-Doppler velocity retrieval. Mon. Wea. Rev., 130, 433-453.
  9. Weygandt, S.S., A. Shapiro and K.K. Droegemeier, 2002: Retrieval of initial forecast fields from single-Doppler observations of a supercell thunderstorm. Part II: Thermodynamic retrieval and numerical prediction. Mon. Wea. Rev., 130, 454-476.
  10. Xue, M., 2002: Density currents in shear flows: Effects of rigid lid and cold-pool Internal circulation, and application to squall line dynamics. Quart. J. Roy. Met. Soc., 128, 47-74.

2001

  1. Anthes, R., O. Brown, K. Droegemeier, and J. Fellows, 2001: UCAR and NCAR at 40. Bull. Amer. Meteor. Soc., 82, 1139-1149.
    Gao, J., M. Xue, A. Shapiro, Q. Xu, and K. K. Droegemeier, 2001: Three-dimensional simple adjoint velocity retrievals from single Doppler radar. J. Atmos. Ocean Tech., 18, 26-38.
  2. Harris, D., E. Foufoula-Georgiou, K.K. Droegemeier, and J. Levit, 2001: Multi-scale statistical properties of a high-resolution precipitation forecast. J. Hydromet., 4, 406-418.
  3. Hou, D., E. Kalnay, and K.K. Droegemeier, 2001: Objective verification of the SAMEX '98 ensemble forecasts. Mon. Wea. Rev., 129, 73-91.
  4. Lazarus, S., A. Shapiro, and K.K. Droegemeier, 2001: Application of the Gal-Chen/Zhang velocity retrieval to a deep convective storm. J. Atmos. Sci., 58, 998-1016.
  5. MacGorman, D.R., J.M. Straka, and C.L. Ziegler, 2001; A lightning parameterization for numerical cloud models. J. Appl. Met. 40, 459-478.
  6. Shapiro, A., 2001: Solid-body-type vortex solutions of the Euler equations. J. Fluid Mech., 444, 99-115.
  7. Shapiro, A., 2001: A centrifugal wave solution of the Euler and Navier-Stokes Equations. J. Appl. Math. Phys. (ZAMP), 52, 913-923.
  8. Shapiro, A., 2001: Flow of an inviscid rotating liquid into an elevated sink. Quart. J. Mech. Appl. Math., 54, 243-256.
  9. Xue, M., K. K. Droegemeier, V. Wong, A. Shapiro, K. Brewster, F. Carr, D. Weber, Y. Liu, and D.-H. Wang, 2001: The Advanced Regional Prediction System (ARPS) - A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Physics, 76, 143-165.
  10. Xue, M., and S.-J. Lin, 2001: Numerical equivalence of advection in flux and advective forms and quadratically conservative high-order advection schemes. Mon. Wea. Rev., 129, 561-565.

2000

  1. Brotzge, J.A., and K.C. Crawford, 2000: Estimating sensible heat flux from the Oklahoma Mesonet. J. App;. Meteor., 39, 102-116.
  2. Brotzge, J.A., and C.E. Duchon, 2000: A field comparison among a domeless net radiometer, two 4-component ned radiometers, and a domed net radiometer. J. Atmos. Ocean. Tech., 17, 1569-1582.
  3. Doyle, J.D., D. R. Durran, B.A. Colle, C. Chen, M. Georgelin, V. Grubisic, W.R. Hsu, C.Y. Huang, D. Landau, Y.L. Lin, G.S. Poulos, W.Y. Sun, D.B. Weber, M.G. Wurtele, and M. Xue, 2000: An intercomparison of model-predicted wave breaking for the 11 January 1972 Boulder windstorm. Mon. Wea. Rev., 128, 901-914.
  4. Droegemeier, K.K. and Co-authors, 2000: Hydrological aspects of weather prediction and flood warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program. Bull. Amer. Meteor. Soc., 81, 2665-2680.
  5. Foufoula-Georgiou, E., J. Zepeda-Arce, and K.K. Droegemeier, 2000: Space-time rainfall organization and its role in validating quantitative precipitation forecasts. J. Geophys. Res., 105, 10129-10146.
  6. Kalnay E., S. Park, Z. Pu and J. Gao, 2000: Application of the quasi-inverse method to accelerate 4-D VAR. Mon. Wea. Rev., 128, 864-875.
  7. Park, S.-K. and K.K. Droegemeier, 2000: Sensitivity analysis of a 3-D convective storm: Implications for variational data assimilation and forecast error. Mon. Wea. Rev., 128, 140-159.
  8. Rasmussen, E.N., S. Richardson, J.M. Straka, P.M. Markowski, and D.O. Blanchard, 2000: The association of significant tornadoes with a baroclinic boundary on 2 June 1995. Mon. Wea. Rev., 128, 174-191.
  9. Straka, J.M., D. S. Zrnic, and A. V. Ryzhkov, 2000; Bulk hydrometeor classification and quantification using multi-parameter radar data. Synthesis of relations. J. Applied Meteor. , 39, 1341-1372.
  10. Ware, R.H., D.W. Fulker, S.A. Stein, D.N. Anderson, S.K. Avery, R.D. Clark, K.K. Droegemeier, J.P. Kuettner, J. Minster, and S. Sorooshian, 2000: Real-time national GPS networks: Opportunities for atmospheric sensing. Earth Planets Space, 52, 901-905.
  11. Ware, R.H., D.W. Fulker, S.A. Stein, D.N. Anderson, S.K. Avery, R.D. Clark, K.K. Droegemeier, J.P. Kuettner, J.B. Minster, and S. Sorooshian, 2000: SuomiNet: A real-time national GPS network for atmospheric research and education. Bull. Amer. Meteor. Soc., 84, 677-694.
  12. Xue, M., 2000: Density current in two-layer shear flows. Quart. J. Roy. Met. Soc., 126, 1301-1320.
  13. Xue, M., 2000: High-order monotonic numerical diffusion and smoothing. Mon. Wea. Rev., 128, 2853-2864.
  14. Xue, M., K. K. Droegemeier, and V. Wong, 2000: The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75, 161.

1999

  1. Adlerman, E.J., K.K. Droegemeier, and R-P. Davies-Jones 1999: Numerical simulation of cyclic mesocyclogenesis. J. Atmos. Sci., 56, 2045-2069.
  2. Gao, J., M. Xue, A. Shapiro, and K. K. Droegemeier, 1999: A variational method for the retrieval of three-dimensional mesoscale wind fields from two Doppler radars. Mon. Wea. Rev., 127, 2128-2142.
  3. Lazarus, S., A. Shapiro, and K.K. Droegemeier, 1999: Analysis of the Gal-Chen/Zhang single-Doppler velocity retrieval. J. Atmos. and Oceanic Tech., 16, 5-18.
  4. Markowski, P.M., and J.M. Straka, 1999: Some observations of rotating updrafts in a low-buoyancy, highly sheared environment. Mon. Wea. Rev., 128, 449-461.
  5. Park, S.K., and K.K. Droegemeier, 1999: Sensitivity analysis of a moist 1-D Eulerian cloud model using automatic differentiation. Mon. Wea. Rev., 127, 2180-2196.
  6. Park, S.K., 1999: Nonlinearity and predictability of convective rainfall associated with water vapor perturbations in a numerically simulated storm. J. Geophys. Res., 104, 31575-31588.
  7. Rao, P.A., H.E. Fuelberg, and K.K. Droegemeier, 1999: High resolution modeling of the Cape Canaveral area land/water circulations and associated features. Mon. Wea. Rev., 56, 1808-1821.
  8. Shapiro, A. and J. Mewes, 1999: New formulations of dual-Doppler wind analysis. J. Atmos. and Oceanic Technol., 16, 782-792
  9. Shapiro, A. and P. Markowski, 1999: Dynamics of elevated vortices. J. Atmos. Sci., 56, 1101-1122.
  10. Vivekanandan, J., D.S. Zrnic’, S.M. Ellis, D. Oye, A.V. Ryzhkov, and J.M. Straka, 1999: Cloud Physics Retrieval Using S-band Dual-Polarization Radar Measurements. Bull. Amer. Meteor. Soc. 80, 381-388.
  11. Xu, Q., and J. Gao, 1999: Generalized adjoint for physical processes with parameterized discontinuities: Minimization problems in multidimensional space. J. Atmos. Sci., 56, 994-1002.

1998

  1. Carpenter, R.L. Jr., K.K. Droegemeier, and A.M. Blyth, 1998a: Entrainment and detrainment in numerically simulated cumulus congestus clouds, Part I: General results and comparison with observations. J. Atmos. Sci, 55, 3417-3432.
  2. Carpenter, R.L. Jr., K.K. Droegemeier, and A.M. Blyth, 1998b: Entrainment and detrainment in numerically simulated cumulus congestus clouds, Part II: Cloud budgets. J. Atmos. Sci, 55, 3433-3439.
  3. Carpenter, R.L. Jr., K.K. Droegemeier, and A.M. Blyth, 1998c: Entrainment and detrainment in numerically simulated cumulus congestus clouds, Part III: Detailed parcel analyses and conceptual model. J. Atmos. Sci, 55, 3440-3455.
  4. Lilly, D.K., G.M. Bassett, K.K. Droegemeier, and P. Bartello, 1998: Stratified turbulence in the atmospheric mesoscales. Theoretical and Comp. Fluid Dyn, 11, 139-153.
  5. Markowski, P.M., E.N. Rasmussen, J.M. Straka, 1998: The occurrence of tornadoes and supercells interacting with boundaries during VORTEX 1995. Wea. and Forecasting. 13, 852-859.
  6. Markowski, P.M., E.N. Rasmussen, J.M. Straka, D.C. Dowell, 1998: Observations of low-level baroclinicity generated by anvil shadows. Mon. Wea. Rev., 126, 2942-2958.
  7. Markowski, P, J.M. Straka, E.N. Rasmussen, and D.O. Blanchard, 1998: Variability of storm-relative helicity during VORTEX. Mon. Wea. Rev., 126, 2959-2971.
  8. Rasmussen, E. N., and J. M. Straka, 1998: Variations in supercell morphology. Part I. Observations of the Role of Upper-Level Storm Relative Flow. Mon. Wea. Rev., 126, 2406-2421.
  9. Wang, D.Z., K.K. Droegemeier, and L. White, 1998: The adjoint Newton algorithm for large-scale unconstrained optimization in meteorology applications. Comput. Opt. and Appl., 10, 281-318.
  10. Xu, Q., J. Gao, and W. Gu, 1998: Generalized adjoint for discretized physical processes with parameterized discontinuities, Part V: Coarse-grain adjoint and problems in gradient check. J. Atmos. Sci., 55, 2130-2135.
  11. Xu, Q, W. Gu and J. Gao, 1998: Baroclinic Eady wave and fronts. Part I: Viscous semigeostrophy and the impact of boundary condition. J. Atmos. Sci., 55, 3598-3615.

1997

  1. Droegemeier, K.K., 1997: The numerical prediction of thunderstorms: Challenges, potential benefits, and results from real-time operational tests. WMO Bulletin, 46, 324-336.
  2. Park, S.K., K.K. Droegemeier, 1997: The validity of the tangent linear approximation in a moist convective cloud model. Mon. Wea. Rev., 125, 3320-3340.
  3. Sathye, A., M. Xue, G. Bassett, K.K. Droegemeier, 1997: Parallel weather modeling with the Advanced Regional Prediction System, Parallel Computing 23 (1997) 2243-2256.
  4. Wang, Z., K.K. Droegemeier, L. White, and I.M. Navon, 1997: Application of a new adjoint Newton algorithm to the 3-D ARPS storm scale model using simulated data. Mon. Wea. Rev., 125, 1460-1478.
  5. Xue, M., Q. Xu, and K.K. Droegemeier, 1997: A theoretical and numerical study of density currents in non-constant shear flows. J. Atmos. Sci., 54, 1998-2019.
  6. Zhao, Q., and F. Carr, 1997: A prognostic cloud scheme for operational NWP models. Amer. Meteor. Soc., 125, 1931-1953.

1996

  1. Gallus, W., Jr., and M. Rancic, 1996: A nonhydrostatic version of the NMC's regional eta model. Quart. J. Roy. Meteor. Soc., 122, 495-513.
  2. Kogan, Y.L. and A. Shapiro, 1996: The simulation of a convective cloud in a 3-D model with explicit microphysics, Part II: dynamical and microphysical aspects of cloud merger. J. Atmos. Sci., 53, 2525-2545.
  3. Park, S.K., K.K. Droegemeier, and C. Bischof, 1996: Automatic differentiation as a tool for sensitivity analysis of a convective storm in a 3-D cloud model. Chapter 18 in Computational Differentiation: Techniques, Applications, and Tools, M. Berz, C. Bischof, G. Corliss, and A. Griewank, Eds., SIAM, Philadelphia, PA, 205-214.
  4. Sathye, A.G. Bassett, K.K. Droegemeier, M. Xue, K. Brewster, 1996: Experiences using high performance computing for operational storm scale weather prediction. Concurrency: Practice and Experience, 8, 731-740.
  5. Shapiro, A., 1996: Nonlinear shallow-water oscillations in a parabolic channel: Exact solutions and trajectory analyses. J. Fluid Mech., 318, 49-76.
  6. Xu, Q., 1996: Generalized adjoint for physical processes with parameterized discontinuities - Part I: Basic issues and heuristic examples. J. Atmos. Sci., 53, 1123-1142.
  7. Xu, Q., 1996: Generalized adjoint for physical processes with parameterized discontinuities - Part II: Vector formulations and matching conditions. J. Atmos. Sci., 53, 1143-1155.
  8. Xu, Q., M. Xue, and K. K. Droegemeier, 1996: Numerical simulations of density currents in sheared environments within a vertically confined channel. J. Atmos. Sci., 53, 770-786.
  9. Zhang, J., and T. Gal-Chen, 1996: Single Doppler wind retrieval in the moving frame of reference. J. Atmos. Sci., 53, 2609-2623.
  10. Zong, J., and Q. Xu, 1996: The dynamics of cold fronts passing over a quasi-two dimensional isolated mountain ridge. Tellus (1997), 49A, 559-576.

1995

  1. Carr, F.H., P.L. Spencer, C.A. Doswell. III, and J. D. Powell, 1995: A comparison of two objective analysis techniques for profiler time-height data. Mon. Wea. Rev., 123, 2165-2180.
  2. Droegemeier, K.K., M. Xue, K. Johnson, M. O'Keefe, A. Sawdey, G. Sabot, S. Wholey, K. Mills, and N.-T. Lin, 1995: Weather prediction: A scalable storm-scale model. Chapter 3 (p. 45-92) in High Performance Computing, Addison-Wesley, Reading, Massachusetts, 246 pp.
  3. Emanuel, K., D. Raymond, A. Betts, L. Bosart, C. Bretherton, K. Droegemeier, B. Farrell, J.M. Fritsch, R. House, M. LeMone, D. Lilly, R. Rotunno, M. Shapiro, R. Smith, and A. Thorpe, 1995: Report of the first Prospectus Development Team of the U.S. Weather Research Program to NOAA and the NSF. Bull. Amer. Meteor. Soc., 76, 1194-1208.
  4. Rancic, M., 1995: An efficient, conservative, monotonic remapping for semi-Lagrangian transport algorithms. Mon. Wea. Rev., 123, 1213-1217.
  5. Shapiro, A., S. Ellis, and J. Shaw, 1995: Single-Doppler velocity retrievals with Phoenix II data: Clear-air and microburst wind retrievals in the planetary boundary layer. J. Atmos. Sci., 52, 1265-1287.

1994

  1. Angevine, W.M., R.J. Doviak, and Z. Sorbjan, 1994: Remote sensing of vertical velocity variance and surface heat flux in a convective boundary layer. J. Appl. Meteor. 33, 977-983.
  2. Bluestein, H.B., S.D. Hrebenach, C-F. Change, and E.A. Brandes, 1994: Synthetic dual-Doppler analysis of mesoscale convective systems. Mon. Wea. Rev., 122, 2105-2124.
  3. Johnson, K.W., J. Bauer, G.A. Riccardi, K.K. Droegemeier, and M. Xue, 1994: Distributed processing of a regional prediction model. Mon. Wea. Rev., 122, 2558-2572.
  4. Kogan, Y.L., D.K. Lilly, Z.N. Kogan, and V.V. Filyushkin, 1994: The effect of CCN regeneration on the evolution of sratocumulus cloud layers. Atmos. Res. 33, 137-150.
  5. Lee, J.T., and R. Crane, 1994: Aeronautical Meteorology. In McGraw-Hill Encyclopedia of Science and Technology, 8th Ed., 151-154
  6. Lin, S.-J., W.C. Chao, Y.C. Sud, and G.K. Walker, 1994: A class of the van Leer-type transport schemes and its application to moisture transport in a general circulation model. Mon. Wea. Rev., 122, 1575-1593.
  7. Qiu, C., and Q. Xu, 1994: A spectral simple adjoint method for retrieving low-altitude winds from single-Doppler data. J. Atmos. Oceanic Technology, 11, 927-936.
  8. Rajasethupathy, K.S. G.-M. Thio, S.K. Dhall, and S. Lakshmivarahan, 1994: Tridiagonalizing a real symmetric matrix: A parallel direct approach using Givens' transformation. Parallel Algorithms and Applications, 2, 305-313.
  9. Rasmussen, E.N., J.M. Straka, R. Davies-Jones, C.A. Doswell III, F.H. Carr, M.D. Eilts, and D.R. MacGorman, 1994: Verification of the origins of rotation in tornadoes experiment: VORTEX. Bull. Amer. Meteor. Soc., 75, 995-1017.
  10. Scotti, A., C. Meneveau and D.K. Lilly, 1994: Generalized Smagorinsky model for anisotropic grids. Phys. Fluids A, 5, 2306-2308.
  11. Shapiro, A., and Y. Kogan, 1994: On vortex formation in multicell convective clouds in a shear-free environment. Atmos. Res. 33, 125-136.
  12. Song, C.G., J.-S. Jwo, S. Lakshmivarahan, S.K. Dhall, J.M. Lewis, and C.S. Velden, 1994: An experiment in hurricane track prediction using parallel computing methods. Parallel Algorithms and Applications, 2, 315-332.
  13. Straka, J.M., 1994: Representing moisture processes in mesoscale numerical models. AMS Monograph on Mesoscale Modeling of the Atmosphere. Eds., R.A. Pielke and R. Pearce, 25, 29-38.
  14. Sun, J., 1994: Fitting a Cartesian prediction model to radial velocity data from single-Doppler radar. J. Atmos. Oceanic Tech., 11, 200-204.
  15. Sun, J., , and A. Crook, 1994: Wind and thermodynamic retrieval from single-Doppler measurements of a gust front observed during Phoenix-II. Mon. Wea. Rev., 122, 1075-1091.
  16. Weygandt, S.S., and N.L. Seaman, 1994: Quantification of predictive skill for mesoscale and synoptic-scale meteorological features as a function of horizontal grid resolution. Mon. Wea. Rev., 122, 57-71.
  17. Wong, V.C. and D.K. Lilly, 1994: A comparison of two dynamic subgrid closure methods for turbulent thermal convection. Phys. Fluid A, 6, 1016-1022.
  18. Xu, Q., and C.J. Qiu, 1994: Simple adjoint methods for single-Doppler wind analysis with a strong constraint of mass conservation. J. Atmos. & Oceanic Tech., 11, 289-298.
  19. Xu, Q. , C.J. Qiu, and J.X. Yu, 1994: Adjoint-method retrievals of low-altitude wind fields from single-Doppler reflectivity measured during Phoenix II. J. Atmos. & Oceanic Tech., 11, 275-288.
  20. Xu, Q., C.J. Qiu, and J.X. Yu, 1994: Adjoint-method retrievals of low-altitude wind fields from single-Doppler wind data. J. Atmos. & Oceanic Tech., 11, 579-585.

1993

  1. Droegemeier, K.K., 1993: Weather forecasting and prediction. McGraw-Hill Yearbook of Science and Technology, McGraw Hill, 476-480.
  2. Droegemeier, K.K., Lazarus, S.M., and R. Davies-Jones, 1993: The influence of helicity on numerically-simulated convective storms. Mon. Wea. Rev, 121, 2005-2029.
  3. Filyushkin, V.V. and D.K. Lilly, 1993: Application of a 3D delta-Eddington radiative transfer model to calculation of solar heating and photolysis rates in a stratocumulus cloud layer. Atmos. Radiation, 2049, 56-66.
  4. Johnson, J.T., M.D. Eilts, and K.K. Droegemeier, 1993: Investigation of outflow strength variability in Florida downburst producing storms. FAA Final Report DOT/FAA/NR-93/5/111 p.
  5. Kogan, Z.N., D.K. Lilly, Y.L. Kogan, and V. Filyushkin, 1993: Evaluation of radiation parameterization using an explicit cloud microphysical model. Atmos. Res., 32.
  6. Lakshmivarahan, S., Jun-Sing Jwo, and S.K. Dhall, 1993: Analysis of symmetry in interconnection networks based on cayley graphs of permutation groups: a survey. J. Parallel Computing, 19, 361-407.
  7. Li, Y. and K.K. Droegemeier, 1993: The influence of diffusion on the adjoint data assimilation technique. Tellus, 45A, 435-448.
  8. Shapiro, A., 1993: On use of an exact solution of the Navier-Stokes equations in a validation test of a three-dimensional non-hydrostatic numerical model. Mon. Wea. Rev. 121, 2420-2425.
  9. Straka, J.M., R.B. Wilhelmson, L.J. Wicker, J.R. Anderson, and K.K. Droegemeier, 1993: Numerical solutions of a non-linear density current: A benchmark solution and comparisons. Int. J. Num. Meth. in Fluids, 17, 1-22.
  10. Xu, M., and T. Gal-Chen, 1993: A study of the convective boundary-layer dynamics using single Doppler radar measurements. J. Atmos. Sci., 50, 3641-3662.

1992

  1. CAPS, 1992: ARPS Version 3.0 User's Guide. Center for Analysis and Prediction of Storms, University of Oklahoma, 183pp.
  2. Dietachmayer, G. and K. Droegemeier, 1992: Application of continuous dynamic grid adaption techniques to meteorological modeling, Part I: Basic formulation and accuracy. Mon. Wea. Rev., 120, 1675-1706.
  3. Jwo, J.-S., S. Lakshmivarahan, S.K. Dhall, and J.M. Lewis, 1992: Comparison of performance of three parallel versions of the block cyclic reduction algorithm for solving linear elliptic partial differential equations. J. Appl. Math. and Comp., 24, No 5/6, 83-101.
  4. Lilly, D.K., 1992: A proposed modification of the Germano subgrid-scale closure method, American Institute of Physics, Phys. Fluids A, 4, 633-635.
  5. Lilly, D.K., , 1992: Meteorology, 1992 Science Year, The World Book Annual Science Supplement, pp. 311-313.
  6. Qiu, C.-J. and Q. Xu, 1992: A simple adjoint method of wind analysis for single-Doppler data. J. Atmos. Oceanic Technol., 9, 588-598.
  7. Rancic, M., 1992: Semi-Lagrangian piecewise biparabolic scheme for two-dimensional horizontal advection of a passive scalar. Mon. Wea. Rev., 120, 1394-1406.
  8. Shapiro, A., 1992: A hydrodynamical model of shear flow over semi-infinite barriers with application to density currents. J. Atmos. Sci., 49, 2293-2305.
  9. Skamarock, W.R., and J.B. Klemp, 1992: The stability of time-split numerical methods for the hydrostatic and the nonhydrostatic elastic equations. Mon. Wea. Rev., 120, 2109-2127.
  10. Wong, V.C., 1992: A proposed statistical-dynamic closure method for the linear or nonlinear subgridscale stresses. Phys. Fluids A, 4, 1080.
  11. Wu, W., D.K. Lilly, and R.M. Kerr, 1992: Helicity and thermal convection with shear, J. Atmos. Sci., 49, 1800-1809.

1991

  1. Lilly, D.K., 1991: Thunderstorm. 1991 McGraw-Hill Yearbook of Science and Technology. McGraw-Hill, Inc., New York, pp. 425-427.
  2. Sun, J., D.W. Flicker, and D.K. Lilly, 1991: Recovery of three-dimensional wind and temperature fields from simulated single-Doppler radar data. J. Atmos. Sci., 48, 876-890.

1990

  1. Carpenter, R.L., K.K. Droegemeier, P.R. Woodward, and C.E. Hane, 1990: Application of the piecewise parabolic method (PPM) to meteorological modeling. Mon. Wea. Rev., 118, 586-612.
  2. Kogan, Y.L., 1990: The simulation of a convective cloud in a 3-D model with explicit microphysics. Part I: Model description and sensitivity experiments. J. Atmos. Sci., 48, 1160-1189.
  3. Lilly, D.K. and T. Gal-Chen, 1989: Can dryline mixing create buoyancy? J. Atmos. Sci., 47, 1170-1171.
  4. Lilly, D.K. and B.F. Jewett, 1990: Momentum and kinetic energy budgets of simulated supercell thunderstorms. J. Atmos. Sci., 47, 707-726.
  5. Lilly, D.K., 1990: Numerical prediction of thunderstorms--has its time come? Symons Memorial Lecture. Quart. J. Roy. Meteor. Soc. 116, 779-798.
  6. Robertson, M. and K.K. Droegemeier, 1990: NEXRAD and the broadcast weather industry: Preparing to share the technology. Bull. Amer. Meteor. Soc. 71, 14-18.
  7. White, L., and J.T. Oden, 1990: Dynamics and control of viscoelastic solids with contact and friction effects. J. Nonlinear Analysis and Appl., 4, 459-474..
  8. Xue, M., and A.J. Thorpe, 1990: A mesoscale numerical model using the nonhydrostatic sigma coordinate equations, Part I: model experiments with dry mountain flows. Mon. Wea. Rev., 119, 1168-1185.

1989

  1. Carr, F.H., R.L. Wobus, and R.A. Petersen, 1989: Synoptic evaluation of normal mode initialization experiments with the NMC Nested Grid Model. Mon. Wea. Rev. 117, 2753-2771.