| The warning decision support system–integrated information V Lakshmanan, T Smith, G Stumpf, K Hondl Weather and Forecasting 22 (3), 596-612, 2007 | 409 | 2007 |
| Multi-Radar Multi-Sensor (MRMS) severe weather and aviation products: Initial operating capabilities TM Smith, V Lakshmanan, GJ Stumpf, KL Ortega, K Hondl, K Cooper, ... Bulletin of the American Meteorological Society 97 (9), 1617-1630, 2016 | 250 | 2016 |
| An automated technique to quality control radar reflectivity data V Lakshmanan, A Fritz, T Smith, K Hondl, G Stumpf Journal of applied meteorology and climatology 46 (3), 288-305, 2007 | 233 | 2007 |
| An objective high-resolution hail climatology of the contiguous United States JL Cintineo, TM Smith, V Lakshmanan, HE Brooks, KL Ortega Weather and Forecasting 27 (5), 1235-1248, 2012 | 228 | 2012 |
| Multiscale storm identification and forecast V Lakshmanan, R Rabin, V Debrunner Atmospheric research 67, 367-380, 2003 | 203 | 2003 |
| A real-time, three-dimensional, rapidly updating, heterogeneous radar merger technique for reflectivity, velocity, and derived products V Lakshmanan, T Smith, K Hondl, GJ Stumpf, A Witt Weather and Forecasting 21 (5), 802-823, 2006 | 194 | 2006 |
| An efficient, general-purpose technique for identifying storm cells in geospatial images V Lakshmanan, K Hondl, R Rabin Journal of Atmospheric and Oceanic Technology 26 (3), 523-537, 2009 | 178 | 2009 |
| MPING: Crowd-sourcing weather reports for research KL Elmore, ZL Flamig, V Lakshmanan, BT Kaney, V Farmer, HD Reeves, ... Bulletin of the American Meteorological Society 95 (9), 1335-1342, 2014 | 159 | 2014 |
| Machine learning design patterns V Lakshmanan, S Robinson, M Munn O'Reilly Media, 2020 | 143 | 2020 |
| A feasibility study for probabilistic convection initiation forecasts based on explicit numerical guidance JS Kain, MC Coniglio, J Correia, AJ Clark, PT Marsh, CL Ziegler, ... Bulletin of the American Meteorological Society 94 (8), 1213-1225, 2013 | 124 | 2013 |
| An objective method of evaluating and devising storm-tracking algorithms V Lakshmanan, T Smith Weather and Forecasting 25 (2), 701-709, 2010 | 118 | 2010 |
| Data mining storm attributes from spatial grids V Lakshmanan, T Smith Journal of Atmospheric and Oceanic Technology 26 (11), 2353-2365, 2009 | 88 | 2009 |
| A real-time weather-adaptive 3DVAR analysis system for severe weather detections and warnings J Gao, TM Smith, DJ Stensrud, C Fu, K Calhoun, KL Manross, J Brogden, ... Weather and Forecasting 28 (3), 727-745, 2013 | 83 | 2013 |
| Unlocking the potential of NEXRAD data through NOAA’s Big Data Partnership S Ansari, S Del Greco, E Kearns, O Brown, S Wilkins, M Ramamurthy, ... Bulletin of the American Meteorological Society 99 (1), 189-204, 2018 | 80 | 2018 |
| An automated method for depicting mesocyclone paths and intensities ML Miller, V Lakshmanan, TM Smith Weather and forecasting 28 (3), 570-585, 2013 | 78 | 2013 |
| Quality control of weather radar data using polarimetric variables V Lakshmanan, C Karstens, J Krause, L Tang Journal of Atmospheric and Oceanic Technology 31 (6), 1234-1249, 2014 | 77 | 2014 |
| A separable filter for directional smoothing V Lakshmanan IEEE Geoscience and Remote Sensing Letters 1 (3), 192-195, 2004 | 76 | 2004 |
| A physically based precipitation–nonprecipitation radar echo classifier using polarimetric and environmental data in a real-time national system L Tang, J Zhang, C Langston, J Krause, K Howard, V Lakshmanan Weather and Forecasting 29 (5), 1106-1119, 2014 | 75 | 2014 |
| An improved method for estimating radar echo-top height V Lakshmanan, K Hondl, CK Potvin, D Preignitz Weather and Forecasting 28 (2), 481-488, 2013 | 61 | 2013 |
| Quantitative precipitation nowcasting: A Lagrangian pixel-based approach A Zahraei, K Hsu, S Sorooshian, JJ Gourley, V Lakshmanan, Y Hong, ... Atmospheric Research 118, 418-434, 2012 | 57 | 2012 |
Kevin L ManrossResearch Associate III CIRA/Colorado State Univ. and NOAA Global Systems Laboratory在 noaa.gov 的电子邮件经过验证
