薛明[南京大學大氣科學學院教授]

薛明[南京大學大氣科學學院教授]

南京大學大氣科學學院教授、博士生導師、南京大學中尺度災害性天氣教育部重點實驗室首席科學家。美國俄克拉荷馬大學氣象系Weathernews冠名講席教授,George Lynn Cross傑出科研教授,風暴分析預報中心CAPS主任,世界氣象組織THORPEX TIGGE-LAM工作組成員。

教育與工作經歷

薛明,1984年獲得南京大學氣象學學士學位 。1989年獲得英國Reading大學氣象學博士學位,師從國際著名學者,歐洲中期數值預報中心前主任Alan Thorpe教授。1989年赴美國俄克拉荷馬大學(University of Oklahoma)風暴分析預報中心(Center for Analysis and Prediction of Storms)從事博士後研究,歷任該中心研究員、高級研究員、科學主任 。

1999年起薛明教授任美國俄克拉荷馬大學氣象系助理教授、副教授、教授、Weathernews冠名講席教授,George Lynn Cross傑出科研教授。從2006年起擔任該校風暴分析預報中心主任。世界氣象組織THORPEX TIGGE-LAM工作組成員。2011年起擔任南京大學大氣科學學院教授、博士生導師,中尺度災害性天氣教育部重點實驗室首席科學家 。自2013年起薛明教授帶領其研究團隊在南京大學中尺度災害性天氣教育部重點實驗室建立了計算平台,在我國第一次實現了全中國範圍、4km格線距、對流尺度的實時天氣預報,直接給國家氣象中心預報試驗基地提供預報產品。

研究領域

薛明教授主要從事中小尺度強對流天氣動力學和機理研究,對流尺度數值天氣預報模式、高解析度遙感資料的同化理論方法和系統的研發工作。成功的氣象預報除了與大氣環流狀況有關外,天氣系統內部中小尺度系統的發展演變及結構特徵是決定“定時、定點、定量”精細化預報的關鍵。但此類中小尺度系統空間尺度小、發展速度快、持續時間短、很難利用常規手段對其進行觀測,薛明教授致力於藉助使用雷達、衛星等非常規遙感手段觀測來捕捉中小尺度系統內部結構和演變特徵,並將此類高解析度觀測資料同化套用到高精度數值預報模擬中,對各類天氣現象實現高精度數值模擬,最終改進冰雹,大風,龍捲,局地強降水,颱風等強對流災害性天氣的預報。

薛明教授領導研發的ARPS(Advanced Regional Prediction System)數值天氣預報模式是國際上第一個專門用於對流尺度天氣的數值預報和資料同化系統,後發展成通用的區域資料同化和預報系統,其解決了一系列模式設計、數值方法及資料同化方面的關鍵問題,模式在國際多個國家被廣泛套用於科研和業務預報,曾獲得美國兩項科技進步獎。

科研項目

薛明教授曾獲中國國家科學基金委傑出青年基金(B類)、中科院海外傑出青年研究基金、基金委海外重點合作項目基金、基金委重點研究項目基金,是科技部“突發性強對流天氣演變機理和監測預報技術研究”973基礎研究項目(總經費3400萬元)首席科學家 、國家自然科學基金重點項目“中國龍捲的形成機理及可預報性研究”主持人。

發表論文

薛明教授已在國際SCI期刊上發表論文240餘篇, 其中近五年發表SCI論文100餘篇。論文被引用12,000餘次(Google Scholar),H-Index為53。

以下為正式發表論文:


2018


[248] 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.

[247] 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.

[246] 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..

[245] 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.

[244] 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. Accepted..

[243] 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.

[242] 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.

[241] 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., https://doi.org/10.1002/2017JD027968.

[240] 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. https://doi.org/10.1175/JAS-D-17-0346.1.

[239] 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., Accepted.

[238] 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., Accepted.

[237] 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, https://doi.org/10.1175/WAF-D-17-0085.1.

[236] 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.

[235] Wang, Q. and M. Xue, 2018: A high-resolution modeling study of the 19 June 2002 convective initiation case during IHOP: Localized forcing by horizontal convective rolls. Adv. Atmos. Sci., Accepted.

[234] Zhu, K., M. Xue, Y. Pan, M. H. S. G. Benjamin, S. S. Weygandt, and H. Lin, 2018: The Impact of Assimilating Polar-Orbiting Satellite Radiance Data using GSI-based Ensemble Kalman Filter and GSI 3DVar for a Rapid Refresh Configuration. J. Adv. Modeling Earth Systems, Submitted.

[233] Fu, P., K. Zhu, K. Zhao, B. Zhou, and M. Xue, 2018: The role of nocturnal low-level jet in the formation of morning precipitation peak over Dabie Mountains. Adv. Atmos. Sci., Submitted.

[232] 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., Conditinoally accepted.

[231] Liu, C., M. Xue, and R. Kong, 2018: Direct assimilation of radar reflectivity data using 3DVAR: Treatment of hydrometeor background errors and OSSE tests. Mon. Wea. Rev., Submitted.

2017

[230] Xu, X., M. Xue, Y. Wang, and H. Huang, 2017: Mechanisms of secondary convection within a mei-yu frontal mesoscale convective system in eastern China. J. Geophy. Res., 122, 47-64.

[229] 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.

[228] 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.

[227] 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.

[226] 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.

[225] 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.

[224] 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.

[223] 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.

[222] 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.

[221] Zhou, B., K. Zhu, and M. Xue, 2017: A Physically-based horizontal subgrid-scale turbulent mixing parameterization for the convective boundary layer. J. Atmos. Sci., 74, 2657-2674.

[220] 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.

[219] 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.

[218] 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.

[217] 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.

[216] 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.

[215] 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.

[214] 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, 10711-10728.

[213] 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.

[212] 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, 301-11312.

2016

[211] Schenkman, A. D., M. Xue, and D. T. Dawson, II, 2016: The cause of internal outflow surges in a high-resolution simulation of the 8 May 2003 Oklahoma City tornadic supercell. J. Atmos. Sci., 73, 353-370.

[210] Supinie, T. A., Y. Jung, M. Xue, D. J. Stensrud, M. M. French, and H. B. 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.

[209] 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.

[208] Liu, C. and M. Xue, 2016: Relationships among four-dimensional hybrid ensemble-variational aata assimilation algorithms with full and approximate ensemble covariance localization. Mon. Wea. Rev., 144, 591-606.

[207] Schenkman, A. D. and M. Xue, 2016: Bow-echo mesovortices: A review. Atmos. Res., 170, 1-13.

[206] Dawson, D. T., II, M. Xue, A. Shapiro, J. A. Milbrandt, and A. D. Schenkman, 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. J. Atmos. Sci., 73, 1039-1061.

[205] 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.

[204] Klein, P. M., X.-H. 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, 383-408.

[203] Wang, M., M. Xue, and K. Zhao, 2016: 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.

[202] Meng, Z., D. Yao, L. Bai, 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. Bull., 61, 330-337.

[201] 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.

[200] Hu, X. 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.

[199] Hu, X.-M., M. Xue, P. M. Klein, B. G. Illston, and S. Chen, 2016: Analysis of urban effects in Oklahoma City using a dense surface observing network. J. Appl. Meteor. Climatol, 55, 723-741.

[198] Iyer, E. R., A. Clark, M. Xue, and F. Kong, 2016: A comparison of 36-60 hour precipitation forecasts from convection-allowing and convection-parameterizing ensembles. Wea. Forecasting, 31, 647-661.

[197] Wen, L., K. Zhao, G. Zhang, M. Xue, B. Zhou, S. Liu, and X. Chen, 2016: Statistical characteristics of raindrop size distributions observed in east China during the Asian summer monsoon season from the 2D-video disdrometer and micro-rain radar. J. Geophy. Res., 121, 2265-2282.

[196] Duda, J. D., X. Wang, F. Kong, M. Xue and Judith Berner, 2016: Impact of a stochastic kinetic energy backscatter scheme on warm season convection-allowing ensemble forecasts. Mon. Wea Rev., 144, 1887-1908.

[195] Byrd, A. D., I. R. Ivic, R. D. Palmer, B. M. Isom, B. L. Cheong, A. Schenkman, and M. Xue, 2016: A weather radar simulator for the evaluation of polarimetric phased array performance. IEEE Trans. Geosci. Remote Sensing, 54, 4178-4189.

[194] Snook, N., Y. Jung, J. Brotzge, B. Putnam, and M. Xue, 2016: Prediction and ensemble forecast verification of hail in the supercell storms of 20 May 2013. Wea. Forecasting, Wea. Forecasting, 31, 811-825.

[193] Roberts, B., M. Xue, A. D. Schenkman, and I. Daniel T. Dawson, 2016: The role of surface friction in tornadogenesis within an idealized supercell simulation. J. Atmos. Sci., 73, 3371-3395.

[192] 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 Meteor., 161, 145-163.

[191] Ren, D. and M. Xue, 2016: Retrieval of land surface model state variables through assimilating screen-level atmospheric humidity and temperature measurements. Adv. Meteor., DOI: 10.1155/2016/1905076.

[190] Dahl, N. and M. Xue, 2016: 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.

[189] Wang, Q., M. Xue, and Z. Tan, 2016: Convective initiation by topographically induced convergence forcing over Dabie Mountains on 24 June 2010. Adv. Atmos. Sci., 33, 1120-1136.

[188] 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.

[187] 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.

[186] Zhu, K. and M. Xue, 2016: Evaluation of WRF-based Convection-Permitting Multi-Physics Ensemble Forecasts over China for the July 21, 2012 Beijing Extreme Rainfall Event. Adv. Atmos. Sci., 33, 1240-1258.

[185] Xue, M., K. Zhao, M. J. Wang, Z. H. Li, Y. G. Zheng, 2016: Recent significant tornadoes in China. Adv. Atmos. Sci., 33, 1209-1217.

[184] Wang, M., M. Xue, and K. Zhao, 2016: An investigation on how inner-core structures obtained through radar data assimilation affect track forecasting of typhoon Jangmi (2008) near Taiwan Island. J. Geophy. Res., 121, 10601-10616.

[183] Wang, M., K. Zhao, M. Xue, G. Zhang, S. Liu, L. Wen, and G. Chen, 2016: Precipitation Microphysics Characteristics of a Typhoon Matmo (2014) Rainband after Landfall over Eastern China based on Polarimetric Radar Observations. J. Geophy. Res., 121, 12, 415-12, 433.

[182] Mahale, V. N., G. Zhang, and M. Xue, 2016: Characterization of the 14 June 2011 Norman, Oklahoma, downburst through dual-polarization radar observations and hydrometeor classification. J. Appl. Meteor. Climatol., 55, 2635-2655.

[181] Sun, X., M. Xue, J. Brotzge, R. McPherson, X.-M. Hu, and X.Q. Yang, 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. Geophy. Res., 121, 13801-13826.

2015

[180] 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.

[179] 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.

[178] Wang, G., W.-K. Wong, Y. Hong, 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.

[177] 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.

[176] 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.

[175] 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.

[174] Dawson, D. T., II, M. Xue, A. Shapiro, and J. A. Milbrandt, 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 numerical forecasts. Mon. Wea. Rev., 143, 2241-2265.

[173] Zhu, K., Y. Yang, and M. Xue, 2015: Percentile-based neighborhood precipitation verification and its application to a landfalling tropical storm case with radar data assimilation. Adv. Atmos. Sci., 32, 1449-1459.

[172] 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.

[171] Miao, Y., X.-M. Hu, S. Liu, T. Qian, M. Xue, Y. Zheng, and S. Wang, 2015: Seasonal variation of local atmospheric circulations and boundary layer structure in the Beijing-Tianjin-Hebei region and implications for air quality. J. Adv. Modeling Earth Systems, 7, 1602-1626.

[170] Chen, X.-C., K. Zhao, M. Xue, B. Zhou, and W. Xu, 2015: Radar observed diurnal cycle and propagation of convection over the Pearl River Delta during Mei-Yu season. J. Geophy. Res., 120, 12557-12575.

2014

[169] 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.

[168] 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.

[167] 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.

[166] 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.

[165] 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.

[164] Klein, P. M., X.-M. Hu, and M. Xue, 2014: Impacts of mixing processes in nocturnal atmospheric boundary layer on urban ozone concentrations. Bound. Layer. Meteor., 150, 107-130.

[163] 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.

[162] 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.

[161] 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.

[160] 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.

[159] 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

[158] 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.

[157] Gagne, D. J., II, A. McGovern, and M. Xue, 2014: Machine learning enhancement of storm scale ensemble probabilisic quantitative precipitation forecasts. Mon. Wea. Rev., 29, 1024-1043.

[156] 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 .

[155] 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.

[154] 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.

[153] 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.

[152] Hu, X.-M., Z.-Q. Ma, W.-L. Lin, H.-L. Zhang, J.-L. Hu, Y. Wang, X.-B. Xu, 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 Plain: A case study. Sci. Total Env., 499, 228-237.

2013

[151] 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.

[150] 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.

[149] Hall, J. D., M. Xue, L. Ran and Lance M. Leslie, 2013: High-resolution modeling of typhoon Morakot (2009): Vortex Rossby waves and their role in extreme precipitation over Taiwan. J. Atmos. Sci., 70, 163-186.

[148] 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 model. Mon. Wea. Rev., 141, 625-648.

[147] 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., 30, 263-279.

[146] 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..

[145] Stensrud, D. J., L. J. Wicker, M. Xue, D. Dawson, N. Yussouf, D. Wheatley, T. E. Thompson, N. A. Snook, T. M. Smith, A. D. Schenkman, C. K. Potvin, E. R. Mansell, T. Lei, K. M. Kuhlman, 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. Atmos. Res., 123, 2-16.

[144] Wang, S., M. Xue, and J. Min, 2013: A four-dimensional asynchronous ensemble square-root filter (4DEnSRF) and tests with simulated radar data. Quart. J. Roy. Meteor. Soc., 139, 805-819.

[143] 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.

[142] 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.

[141] 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.

[140] 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.

[139] 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.

[138] Schumacher, R. S., A. J. Clark, M. Xue and F. Kong, 2013: Factors influencing the development and maintenance of nocturnal heavy-rain-producing convective systems in a storm-scale ensemble. Mon. Wea. Rev., 141, 2778-2801.

[137] 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.

[136] 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.

[135] 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.

[134] 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.

[133] 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.

[132] 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.

[131] Johnson, A., X. Wang, F. Kong, and M. Xue, 2013: Object-based evaluation of the impact of horizontal grid spacing on storm-scale forecasts. Mon. Wea. Rev., 141, 3413-3425.

[130] 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.

[129] 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.

[128] 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.

[127] Hu, X.-M., P. M. Klein, and M. Xue, 2013: Evaluation of the updated YSU Planetary Boundary Layer Scheme within WRF for Wind Resource and Air Quality Assessments. J. Geophy. Res., 118, 10490-10505.

[126] Hu, X.-M., P. Klein , M. Xue , A. Shapiro, A.Nallapareddy, 2013: Enhanced vertical mixing associated with a nocturnal cold front passage and its impact on near-surface temperature and ozone concentration. J. Geophy. Res., 118, 2714-2728.

[125] 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.

[124] 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.

[123] 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. App. Meteor. Clim., 52, 2493-2508.

[122] 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.

[121] 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.

[120] 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.

[119] Natenberg, E., J. Gao, M. Xue, and F. H. Carr, 2013: Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model. Adv. Meteor., 2013, Article ID 281695, doi:10.1155/2013/281695.

[118] 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.

2012

[117] 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. Ocean. Tech., 29, 32-49.

[116] 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.

[115] Clark, A. J., S. J. Weiss, J. S. Kain, I. L. Jirak, M. Coniglio, C. J. Melick, C. Siewert, R. A. Sobash, P. T. Marsh, A. R. Dean, M. Xue, F. Kong, K. W. Thomas, Y. Wang, K. Brewster, J. Gao, X. Wang, J. Du, D. R. Novak, F. Barthold, M. J. Bodner, J. J. Levit, C. B. Entwistle, T. L. Jensen, and J. James Correia, 2012: An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment. Bull. Amer. Meteor. Sci., 93, 55-74.

[114] 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, with verification against polarimetric radar data. Mon. Wea. Rev., 140, 1457-1475.

[113] Wang, Q.-W. and M. Xue, 2012: Convective initiation on 19 June 2002 during IHOP: High-resolution simulations and analysis of the mesoscale structures and convection initiations. J. Geophy. Res., 117, D12107.

[112] 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.

[111] Snook, N., M. Xue, and J. 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.

[110] 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.

[109] 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.

[108] Wang, M., K. Zhao, W.-C. Lee, B. J.-D. Jou, and M. Xue, 2012: The gradient velocity track display (GrVTD) technique for retrieving tropical cyclone primary circulation from aliased velocities measured by single Doppler radar J. Atmos. Ocean. Tech., 29, 1026-1041.

[107] 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.

[106] Li, Y., X. Wang, and M. Xue, 2012: Assimilation of radar radial velocity data with the WRF ensemble-3DVAR hybrid system for the prediction of hurricane Ike (2008). Mon. Wea. Rev., 140, 3507-3524.

[105] 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.

[104] Gagne, D. J., II, A. McGovern, and M. Xue, 2012: Machine learning enhancement of storm scale ensemble precipitation forecasts. Conference on Intelligent Data Understanding (CIDU 2012) 8pp (referred conference paper).

[103] 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.

[102] 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.

[101] 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.

2011

[100] Schenkman, A., M. Xue, A. Shapiro, K. Brewster, and J. Gao, 2011: Theanalysis 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.

[99] 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.

[98] Dong, J., M. Xue, and K. K. Droegemeier, 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.

[97] 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.

[96] Johnson, A., X. Wang, F. Kong, and M. Xue, 2011: Hierarchical cluster analysis of a convection- allowing ensemble during the Hazardous Weather Testbed 2009 Spring Experiment. Part I: Development of the object-oriented cluster analysis method for precipitation fields. Mon. Wea. Rev., 139, 3673-3693.

[95] Johnson, A., X. Wang, F. Kong, and M. Xue, 2011: Hierarchical cluster analysis of a convection- allowing ensemble during the Spring Experiment of the Hazardous Weather Testbed in 2009. Part II: Ensemble clustering over the whole experiment period. Mon. Wea. Rev., 139, 3694-3710.

[94] 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.

[93] 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 sudden warming. J. Geophy. Res., 116, D17104.

[92] Snook, N., M. Xue, and J. Jung, 2011: Analysis of a tornadic mesoscale convective vortex based on ensemble Kalman filter assimilation of CASA X-band and WSR-88D radar data. Mon. Wea. Rev., 139, 3446-3468.

[91] 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.

2010

[90] Lan, W., J. Zhu, M. Xue, J. Gao, and T. Lei, 2010: Storm-scale ensemble Kalman filter assimilation experiments with simulated Doppler radar data: Part I: The perfect model case. Chinese J. Atmos. Sci., 34(3), 640-652.

[89] Lan, W., J. Zhu, M. Xue, T. Lei, and J. Gao, 2010: Storm-scale ensemble Kalman filter assimilation experiments with simulated Doppler radar data: Part II: The case with model error. Chinese J. Atmos. Sci., 34(4), 737-753.

[88] 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.J. Appl. Meteor. Climatol., 49, 146-163.

[87] Jung, Y., M. Xue, and G. Zhang, 2010: Simutaneous estimation of microphysical parameters and atmospheric state using simulated polarimetric radar data and an ensemble Kalman filter in the presence of an observation operator error. Mon. Wea. Rev., 138, 539-562.

[86] Xue, M., Y. Jung, and G. Zhang, 2010: State estimation of convective storms with a two-moment microphysics scheme and an ensemble Kalman filter: Experiments with simulated radar data Q. J. Roy. Meteor. Soc, 136, 685-700.

[85] 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.

[84] Ge, G., J. Gao, K. Brewster, and M. Xue, 2010: Impacts of beam broadening and earth curvature on 3D variational radar data assimilation radial velocity with two Doppler radars. J. Atmos. Ocean Tech., 27, 617-636.

[83] 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.

[82] 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, and M. S. Wandishin, 2010: Toward improved convection-allowing ensembles: model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Wea. Forecasting, 25, 263-280..

[81] Clark, A. J., W. A. Gallus, M. Xue, and F. Kong, 2010: Growth of spread in convection-allowing and convection-parameterizing ensembles Wea. Forecasting, 25, 594-612..

[80] Clark, A. J., W. A. Gallus, Jr., M. Xue, and F. Kong, 2010: Convection-allowing and convection-parameterizing ensemble forecasts of a mesoscale convective vortex and associated severe weather. Wea. Forecasting, 25, 1052-1081.

[79] 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.

[78] Srivastava, K., J. Gao, K. Brewster, S. K. R. Bhowmik, M. Xue, and R. Gadi, 2010: Assimilation of Indian radar data with ADAS and 3DVAR techniques for simulation of a small-scale tropical cyclone using ARPS model Natural hazards, DOI: 10.1007/s11069-010-9640-4.

2009

[77] 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.

[76] 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.

[75] 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.

[74] 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.

[73] 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.

[72] 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.

[71] Clark, A. J., W. A. Gallus, Jr., M. Xue, and F. Kong, 2009: A comparison of precipitation forecast skill between small convection-permitting and large convection-parameterizing ensembles. Wea. and Forecasting, 24, 1121-1140.

[70] 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, B. Dolan, 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.

[69] Stensrud, D. J., M. Xue, L. J. Wicker, K. E. Kelleher, M. P. Foster, J. T. Schaefer, R. S. Schneider, S. G. Benjamin, S. S. Weygandt, J. T. Ferree, and J. P. Tuell, 2009: Convective-scale Warn on Forecast System: A vision for 2020. Bull. Am. Meteor. Soc., Bull. Am. Meteor. Soc., 90, 1487-1499.

2008

[68] 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.

[67] 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.

[66] 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.

[65] 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.

[64] 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.

[63] 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.

[62] 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.

[61] 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.

[60] 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.

[59] Gao, J., K. Brewster, and M. Xue, 2008: Variation of radio reflectivity with respect to moisture and temperature and influnce on radar ray path. Adv. Atmos. Sci., 1098-1106.

[58] 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.

[57] Snook, N. and M. Xue, 2008: Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms. Geophy. Res. Letters, 35, L24803, doi:10.1029/2008GL035866.

[56] 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

[55] 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.

[54] 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.

[53] 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.

[52] 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.

[51] 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.

[50] 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.

[49] 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.

[48] 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.

[47] 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.

[46] 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., 24, 1973-1996.

2006

[45] 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.

[44] 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.

[43] 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.

[42] 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.

[41] 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.

[40] 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.

[39] 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.

[38] 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.

[37] 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.

[36] 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.

[35] 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.

[34] Gao, J., M. Xue, S. Y. Lee, A. Shapiro, Q. Xu, K. K. Droegemeier, 2006:: A three-dimensional variational single-Doppler velocity retrieval method with simple conservation equation constraint. Meteo. Atmos. Phys., 94, 11-26.

[33] 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.

[32] 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.


2000-2005


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