Valliappa LAKSHMANAN

Work Address

Radar Research and Development Division
National Severe Storms Laboratory
120 David L. Boren Blvd, Norman OK 73072-7327
Email: lakshman@ou.edu
pdf (printable) resume pdf (printable) curriculum vitae

Summary

Employment History

Education

Research & Development Experience

Architect of the Warning Decision Support System - Integrated Information (WDSS-II), a suite of multi-sensor machine-intelligence algorithms, tools and displays for research, weather analysis and severe weather warning decision-making. Uses C++, Java, J2EE, XML, and network programming on Linux and Windows.

Developed around a hundred of the algorithms that comprise the WDSS-II product suite.

Designer and technical leader in developing a system that will pull in data from all the radar in a region and combine them for visualization and algorithm processing. This project (``OPUP''), for the Air Force Weather Service, was first deployed in 1999-2000 and represented a significant advance over current visualization and radar data handling. Uses C++, XML and Oracle. (1998-2000)

Please see publications for a more detailed list of R&D work.

Honors, Awards, Memberships

2014 Elected Chair of the Artificial Intelligence Committee of the American Meteorological Society

2013 NOAA Technology Transfer Award for ``leading the development of an on-demand, near real-time, web-based tool for tracking severe weather and hail swaths across the continental US.''

2012 Innovator Award by the University of Oklahoma Office of Technology Development for developing ``groundbreaking (WDSS-II) software [that] is used worldwide to help predict weather phenomena including hail, precipitation, mesocyclones, and tornadoes. Used by private companies, research labs, National and International governments across the globe, this technology provides users across the world with the information needed to make property and life-saving decisions in the event of hazardous weather''.

2006 Nominated by National Severe Storms Laboratory for Presidential Early Career Award for Scientists and Engineers (PECASE)

2004 NOAA Tech Award for Best Presentation in the category of Techology Transfer to Operations: "Real-time Dissemination of WSR-88D Radar Data over Internet2."

University Fellow, The Ohio State University, 1993-94.

Third in the IIT, Madras Department of Electrical Engineering (of 75 students: top 5%) in 1989-1993.

Named among the top 1% of Indian high school graduates in 1989.

Computer Skills

Research Publications

  1. V. Lakshmanan, B. Herzog, and D. Kingfield, ``A method of extracting post-event storm tracks,'' J. Appl. Meteo. Clim., vol. 0, p. Under Review, 0 2014.

  2. V. Lakshmanan, C. Karstens, J. Krause, K. Elmore, A. Ryzhkov, and S. Berkseth, ``Which polarimetric variables are important for weather/no-weather discrimination?,'' J. Atmos. Ocean. Tech., vol. 0, p. 0, 2013.

  3. L. Tang, J. Zhang, C. Langston, J. Krause, K. Howard, and V. Lakshmanan, ``A multi-sensor physically based weather/non-weather radar echo classifier using polarimetric and environmental data in a real-time national system,'' J. Atmos. Ocean. Tech., vol. 0, p. 0, 2013.

  4. K. Elmore, Z. Flamig, V. Lakshmanan, B. Kaney, V. Farmer, and L. Rothfusz, ``mPING: Crowd-sourcing weather reports for research,'' Bulletin of the American Meteorological Society, vol. 0, p. 0, 2013.

  5. V. Lakshmanan, C. Karstens, J. Krause, and L. Tang, ``Quality control of weather radar data using polarimetric variables,'' J. Atm. Ocea. Tech., vol. 31, pp. 1234-1249, 6 2014.

  6. T. Smith, J. Gao, K. Calhoun, D. Stensrud, K. Manross, K. Ortega, C. Fu, D. Kingfield, K. Elmore, V. Lakshmanan, and C. Riedel, ``Examination of a real-time 3DVAR analysis system in Hazardous Weather Testbed,'' Wea. Forecasting, vol. 39, pp. 63-77, 2014.

  7. V. Lakshmanan and T. W. Humphrey, ``A MapReduce technique to mosaic continental-scale weather radar data in real-time,'' IEEE J. of Select Topics in Appl. Earth Obs. and Remote Sensing, vol. 7, no. 2, pp. 721-732, 2014. DOI: 10.1109/JSTARS.2013.2282040.

  8. J. Kain, M. Coniglio, J. Correia, A. Clark, P. Marsh, C. Ziegler, V. Lakshmanan, S. Miller, S. Dembek, S. Weiss, F. Kong, M. Xue, R. Sobash, R. Dean, I. Jirak, and C. Melick, ``A feasibility study for probabilistic convection initiation forecasts based on explicit numerical guidance,'' Bull. Amer. Meteor. Soc., vol. 94, pp. 1213-1225, 2013.

  9. J. Gao, T. Smith, T. Stensrud, C. Fu, K. Calhoun, K. Manross, J. Brogden, V. Lakshmanan, Y. Wang, K. Thomas, K. Brewster, and M. Xue, ``A realtime weather-adaptive 3DVAR analysis system for severe weather detections and warnings with automatic storm positioning capability,'' Wea. Forecasting, vol. 28, pp. 727-745, 2013.

  10. M. Miller, V. Lakshmanan, and T. Smith, ``An automated method for depicting mesocyclone paths and intensities,'' Wea. Forecasting, vol. 28, pp. 570-585, 2013.

  11. J. Buler, V. Lakshmanan, and D. La Puma, ``Improving weather radar data processing for biological research applications: Final report,'' Tech. Rep. G11AC20489, Patuxent Wildlife Research Center, USGS, Laurel, MD, 2012.

  12. V. Lakshmanan, M. Miller, and T. Smith, ``Quality control of accumulated fields by applying spatial and temporal constraints,'' J. Atmos. Ocean. Tech., vol. 30, pp. 745-757, 2013.

  13. V. Lakshmanan, K. Hondl, C. Potvin, and D. Preignitz, ``An improved method to compute radar echo top heights,'' Wea. Forecasting, vol. 28, no. 2, pp. 481-488, 2013.

  14. J. Sieglaff, D. Hartung, W. Feltz, L. Cronce, and V. Lakshmanan, ``Development and application of a satellite-based convective cloud object-tracking methodology: A multipurpose data fusion tool,'' J. Applied Meteorology and Clim., vol. 30, pp. 510-525, 3 2013.

  15. J. Newman, V. Lakshmanan, P. Heinselman, M. Richman, and T. Smith, ``Range-correcting azimuthal shear in doppler radar data,'' Wea. Forecasting, vol. 28, pp. 194-211, 2013.

  16. V. Lakshmanan, J. Crockett, K. Sperrow, M. Ba, and L. Xin, ``Tuning the auto-nowcaster automatically,'' Wea. Forecasting, vol. 27, no. 6, pp. 1568-1579, 2012.

  17. P. Marsh, J. Kain, , V. Lakshmanan, A. Clark, N. Hitchens, and J. Hardy, ``A method for calibrating deterministic forecasts of rare events,'' Wea. Forecasting, vol. 27, pp. 531-538, 2012.

  18. V. Lakshmanan, R. Rabin, J. Otkin, J. Kain, and S. Dembek, ``Visualizing model data using a fast approximation of a radiative transfer model,'' J. Atmos. Ocean. Tech., vol. 29, pp. 745-754, 2012.

  19. A. Zahraei, K. Hsu, S. Sorooshian, J. Gourley, V. Lakshmanan, Y. Hong, and T. Bellerby, ``Quantitative precipitation nowcasting: A lagrangian pixel-based approach,'' Atmos. Research, vol. 118, pp. 418-434, 2012.

  20. J. Cintineo, T. Smith, V. Lakshmanan, H. Brooks, and K. Ortega, ``An objective high-resolution hail climatology of the contiguous united states,'' Wea. Forecasting, vol. 27, pp. 1235-1248, 2012.

  21. V. Lakshmanan, ``Image processing of weather radar reflectivity data: Should it be done in z or dbz?,'' Elec. J. Severe Storms Meteo., vol. 7, no. 3, pp. 1-4, 2012.

  22. V. Lakshmanan, J. Zhang, K. Hondl, and C. Langston, ``A statistical approach to mitigating persistent clutter in radar reflectivity data,'' IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, pp. 652-662, 4 2012.

  23. A. Hobson, V. Lakshmanan, T. Smith, and M. Richman, ``An automated technique to categorize storm type from radar and near-storm environment data,'' Atmos. Research, vol. 111, no. 7, pp. 104-113, 2012.

  24. M. Zhu, V. Lakshmanan, P. Zhang, Y. Hong, K. Cheng, and S. Chen, ``Spatial verification using a true metric,'' Atmospheric Research, vol. 102, no. 4, pp. 408-419, 2011.

  25. S. McCarroll, M. Yeary, D. Hougen, V. Lakshmanan, and S. Smith, ``Approaches for compression of super-resolution WSR-88D data,'' IEEE Tran. on Geosci. and Remote Sensing Letters, vol. PP, no. 99, pp. 191-195, 2010.

  26. S. Sen Roy, V. Lakshmanan, S. Roy Bhowmik, and S. Thampi, ``Doppler weather radar based nowcasting of cyclone ogni,'' J. Earth Syst. Sci., vol. 119, no. 2, pp. 183-199, 2010.

  27. V. Lakshmanan and J. Kain, ``A Gaussian mixture model approach to forecast verification,'' Wea. Forecasting, vol. 25, no. 3, pp. 908-920, 2010.

  28. V. Lakshmanan and T. Smith, ``An objective method of evaluating and devising storm tracking algorithms,'' Wea. Forecasting, vol. 25, no. 2, pp. 721-729, 2010.

  29. V. Lakshmanan, K. Elmore, and M. Richman, ``Reaching scientific consensus through a competition,'' Bull. of Amer. Meteo. Soc., vol. 91, pp. 1423-1427, 2010.

  30. T. Smith and V. Lakshmanan, ``Real-time, rapidly updating severe weather products for virtual globes,'' Computers and Geosci., 2009. DOI: 10.1016/j.cageo.2010.03.023.

  31. V. Lakshmanan, J. Zhang, and K. Howard, ``A technique to censor biological echoes in radar reflectivity data,'' J. Applied Meteorology, vol. 49, pp. 435-462, 3 2010.

  32. V. Lakshmanan and T. Smith, ``Data mining storm attributes from spatial grids,'' J. Ocea. and Atmos. Tech., vol. 26, no. 11, pp. 2353-2365, 2009.

  33. V. Lakshmanan, K. Hondl, and R. Rabin, ``An efficient, general-purpose technique for identifying storm cells in geospatial images,'' J. Atmos. Oceanic Technol., vol. 26, no. 3, pp. 523-37, 2009.

  34. I. Adrianto, T. Trafalis, and V. Lakshmanan, ``Support vector machines for spatiotemporal tornado prediction,'' Int'l J. of General Systems, vol. 38, no. 7, pp. 759-776, 2009. DOI:10.1080/03081070601068629.

  35. V. Lakshmanan, T. Smith, G. J. Stumpf, and K. Hondl, ``The warning decision support system - integrated information,'' Wea. Forecasting, vol. 22, no. 3, pp. 596-612, 2007.

  36. V. Lakshmanan, A. Fritz, T. Smith, K. Hondl, and G. J. Stumpf, ``An automated technique to quality control radar reflectivity data,'' J. Applied Meteorology, vol. 46, pp. 288-305, Mar 2007.

  37. N. Pal, A. Mandal, S. Pal, J. Das, and V. Lakshmanan, ``Fuzzy rule-based approach for detection of bounded weak-echo regions in radar images,'' J. Appl. Meteo. and Clim., vol. 45, no. 9, pp. 1304-1312, 2006.

  38. V. Lakshmanan, T. Smith, K. Hondl, G. J. Stumpf, and A. Witt, ``A real-time, three dimensional, rapidly updating, heterogeneous radar merger technique for reflectivity, velocity and derived products,'' Wea. Forecasting, vol. 21, no. 5, pp. 802-823, 2006.

  39. V. Lakshmanan, ``A separable filter for directional smoothing,'' IEEE Geosci. Remote Sensing Letters, vol. 1, pp. 192-195, 7 2004.

  40. V. Lakshmanan, R. Rabin, and V. DeBrunner, ``Multiscale storm identification and forecast,'' J. Atm. Res., vol. 67, pp. 367-380, July 2003.

  41. V. Lakshmanan, ``Speeding up a large scale filter,'' J. of Oc. and Atm. Tech., vol. 17, pp. 468-473, April 2000.

  42. V. Lakshmanan, ``Using a genetic algorithm to tune a bounded weak echo region detection algorithm,'' J. of Applied Meteorology, vol. 39, pp. 222-230, 2 2000.

  43. C. Marzban and V. Lakshmanan, ``On the uniqueness of gandin and murphy's equitable performance measures,'' Monthly Wea. Review, vol. 127, pp. 1134-1136, June 1999.

  44. V. Lakshmanan and A. Witt, ``A fuzzy logic approach to detecting severe updrafts,'' AI Appl., vol. 11, pp. 1-12, May 1997.

  1. V. Lakshmanan and J. Kain, ``Detecting convective initiation using radar images,'' in Proc. of 7th European Conf. on Radar in Meteo. and Hydro., (Toulousse, France), p. P198, ERAD, 2012.

  2. J. Kain, M. Coniglio, J. Correia, A. Clark, P. Marsh, C. Ziegler, V. Lakshmanan, S. Miller, S. Dembek, S. Weiss, F. Kong, M. Xue, R. Sobash, R. Dean, I. Jirak, and C. Melick, ``A feasibility study for probabilistic convection initiation forecasts based on explicit numerical guidance,'' Bull. Amer. Meteor. Soc., vol. 94, pp. 1213-1225, 2013.

  3. V. Lakshmanan, ``Should image processing of weather radar reflectivity data be done in z or in dbz?,'' in Proc. of 7th European Conf. on Radar in Meteo. and Hydro., (Toulousse, France), p. P197, ERAD, 2012.

  4. V. Lakshmanan, ``Image processing of weather radar reflectivity data: Should it be done in z or dbz?,'' Elec. J. Severe Storms Meteo., vol. 7, no. 3, pp. 1-4, 2012.

  5. V. Lakshmanan, J. Zhang, K. Hondl, and C. Langston, ``Objective method of creating a clutter bypass map,'' in Proc. of 7th European Conf. on Radar in Meteo. and Hydro., (Toulousse, France), p. P196, ERAD, 2012.

  6. V. Lakshmanan, J. Zhang, K. Hondl, and C. Langston, ``A statistical approach to mitigating persistent clutter in radar reflectivity data,'' IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, pp. 652-662, 4 2012.

  7. V. Lakshmanan, R. Rabin, J. Otkin, and J. Kain, ``Visualizing a model using synthetic visible imagery,'' in International Symposium on Earth-science Challenges: 2nd Summit between the University of Oklahoma and Kyoto University, (Norman, OK), p. 14, Sep 2011.

  8. V. Lakshmanan, R. Rabin, J. Otkin, and J. Kain, ``Approximating radiative transfer with a neural network,'' in 10th Conf. on Artificial Intelligence App. to Env. Sci., (New Orleans), p. TJ14.3, Jan 2012.

  9. V. Lakshmanan, R. Rabin, J. Otkin, J. Kain, and S. Dembek, ``Visualizing model data using a fast approximation of a radiative transfer model,'' J. Atmos. Ocean. Tech., vol. 29, pp. 745-754, 2012.

  10. V. Lakshmanan, ``Detecting convective inititation from radar,'' in International Symposium on Earth-science Challenges: 2nd Summit between the University of Oklahoma and Kyoto University, (Norman, OK), p. 13, Sep 2011.

  11. V. Lakshmanan, ``Extrapolating radar images using a gaussian mixture model,'' in Preprints, Sixth European Conf. on Radar in Meteorology and Hydrology, (Sibiu), National Meteorological Administration, Romania, Sep 2010.

  12. V. Lakshmanan and J. Kain, ``Model verification using gaussian mixture models,'' in 20th Conf. on Probability and Statistics in the Atmospheric Sciences, (Atlanta, GA), p. 6.4, Amer. Meteor. Soc., Jan 2010.

  13. V. Lakshmanan and J. Kain, ``A Gaussian mixture model approach to forecast verification,'' Wea. Forecasting, vol. 25, no. 3, pp. 908-920, 2010.

  14. V. Lakshmanan and J. Zhang, ``Censoring biological echoes in wea. radar images,'' in 6th International Conf. on Fuzzy Systems and Knowledge Discovery, (Tianjin, China), IEEE, IEEE Computer Press, Aug. 2009.

  15. V. Lakshmanan and T. Smith, ``Evaluating a storm tracking algorithm,'' in 26th Conf. on IIPS for Meteo., Ocean. and Hydr., (Atlanta, GA), p. 8.2, Amer. Meteor. Soc., Jan 2010.

  16. V. Lakshmanan and T. Smith, ``An objective method of evaluating and devising storm tracking algorithms,'' Wea. Forecasting, vol. 25, no. 2, pp. 721-729, 2010.

  17. V. Lakshmanan, ``Predicting turbulence using partial least squares regression and an artificial neural network,'' in 7th Conf. on Artificial Applications to the Environmental Sciences, (Atlanta, GA), p. 3.3, Amer. Meteor. Soc., Jan 2010.

  18. V. Lakshmanan and T. Smith, ``Data mining storm attributes from spatial grids,'' J. Ocea. and Atmos. Tech., vol. 26, no. 11, pp. 2353-2365, 2009.

  19. V. Lakshmanan, ``Tuning an algorithm for identifying and tracking cells,'' in Southern Thunder 2009 Workshop, (Cocoa Beach, FL), p. CD, Nat. Aero. Space Admin., July 2009.

  20. V. Lakshmanan and T. Smith, ``Lighting warning and prediction using observations and models,'' in 4th Conf. on the Meteorological Applications of Lightning Data, (Phoenix), p. 6.4, Amer. Meteor. Soc., Jan 2009.

  21. V. Lakshmanan, ``An overview of radar data compression,'' in SPIE Optics + Photonics: Satellite Data Compression, Communications and Archiving III, no. 07 in 6683, (San Diego, CA), SPIE, Aug. 2007.

  22. V. Lakshmanan and K. Ortega, ``A technique for creating probabilistic spatio-temporal forecasts,'' in 8th Int'l Conf. on Adv. in Patt. Recogn., (Kolkota), IEEE, Jan 2007.

  23. V. Lakshmanan, I. Adrianto, T. Smith, and G. Stumpf, ``A spatiotemporal approach to tornado prediction,'' in Int'l Joint Conf. on Neural Networks, (Montreal), p. CDROM 1072, July 2005.

  24. V. Lakshmanan, K. Hondl, G. Stumpf, and T. Smith, ``Quality control of wea. radar data using texture features and a neural network,'' in 5th Int'l Conf. on Adv. in Patt. Recogn., (Kolkota), IEEE, Dec 2003.

  25. V. Lakshmanan, V. DeBrunner, and R. Rabin, ``Nested partitions using texture segmentation,'' in Southwest Symposium on Image Analysis and Interpretation, (Santa Fe, New Mexico), IEEE, IEEE Computer Press, Apr. 2002.

  26. V. Lakshmanan, V. DeBrunner, and R. Rabin, ``Texture-based segmentation of satellite weather imagery,'' in Int'l Conf. on Image Processing, (Vancouver), pp. 732-735, Sept. 2000.

  27. V. Lakshmanan and A. Witt, ``Detecting rare signatures,'' in Artificial Neural Networks in Engineering ANNIE '97, (St. Louis, MO), pp. 521-526, ASME Press, 1997.

  28. V. Lakshmanan and A. Witt, ``A fuzzy logic classifier for the detection of bounded weak echo regions in meteorological images,'' in Artificial Neural Networks in Engineering ANNIE '96, (St. Louis, MO), pp. 513-518, ASME Press, 1996.

  29. V. Lakshmanan and A. Witt, ``Detection of bounded weak echo regions in meteorological images,'' in 13th Int'l Conf. on Pattern Recognition, (Vienna), pp. 895-899, International Association of Pattern Recognition, 1996.

  30. V. Lakshmanan and A. Witt, ``A fuzzy logic scheme for the detection of bounded weak echo regions in meteorological images,'' in IAPR Workshop on Machine Perception Applications, (Graz, Austria), pp. 185-198, International Association of Pattern Recognition, 1996.

  31. V. Lakshmanan and A. Witt, ``Classification of skewed distributions: Detecting severe updrafts,'' in Artificial Intelligence and Soft Computing, (Banff, Canada), pp. 37-40, International Association of Science and Technology for Development, 1997.

  32. V. Lakshmanan, ``The simpler the better,'' in 6th Conf. on Artificial Applications to the Environmental Sciences, (Phoenix, AZ), p. 3.5, Amer. Meteor. Soc., Feb 2009.

  33. V. Lakshmanan, J. Gourley, Z. Flamig, and S. Giangrande, ``A simple data-driven model for streamflow prediction,'' in 6th Conf. on Artificial Applications to the Environmental Sciences, (Phoenix, AZ), p. J6.2, Amer. Meteor. Soc., Jan 2009.

  34. V. Lakshmanan, T. Smith, and R. Rabin, ``Automated real-time extraction of storm properties from gridded fields,'' in Preprints, Fifth European Conf. on Radar in Meteorology and Hydrology, (Helsinki), Finnish Meteorological Institute, June 2008.

  35. V. Lakshmanan, J. Zhang, and C. Langston, ``Quality control of canadian radar reflectivity data,'' in Preprints, Fifth European Conf. on Radar in Meteorology and Hydrology, (Helsinki), Finnish Meteorological Institute, June 2008.

  36. V. Lakshmanan, E. Ebert, and S. Haupt, ``The 2008 artificial intelligence competition,'' in 6th Conf. on Artificial Intelligence Applications to Environmental Science, (New Orleans), p. 2.1, Amer. Meteor. Soc., Jan 2008.

  37. V. Lakshmanan and R. Rabin, ``Preprints, nowcasting of thunderstorms from GOES infrared and visible imagery,'' in 5th GOES Users' Conf., (New Orleans), p. P1.73, Amer. Meteor. Soc., Jan 2008.

  38. V. Lakshmanan and K. Hondl, ``A polar-coordinate real-time three-dimensional rapidly updating merger technique for phased array radar scanning strategies,'' in 33rd Conf. on Radar Meteorology, (Cairns, Australia), p. 7.4, Amer. Meteor. Soc., Aug. 2007.

  39. V. Lakshmanan, K. Ortega, and T. Smith, ``Creating spatio-temporal tornado probability forecasts using fuzzy logic and motion variability,'' in 5th Conf. on Artificial Intelligence Appl. to Environ. Science, (San Antonio, TX), Amer. Meteor. Soc., 2007.

  40. V. Lakshmanan, T. Smith, K. Cooper, J. Levit, K. Hondl, G. Stumpf, and D. Bright, ``High-resolution radar data and products over the continental united states,'' in Preprints, 22th Int'l Conf. on Inter. Inf. Proc. Sys. (IIPS) for Meteor., Ocean., and Hydr., (Atlanta), Amer. Meteor. Soc., Feb 2006.

  41. V. Lakshmanan and G. Stumpf, ``A real-time learning technique to predict cloud-to-ground lightning,'' in Preprints, Fourth Conf. on Artificial Intelligence Applications to Environmental Science, (San Diego), p. J5.6, Amer. Meteor. Soc., Jan 2005.

  42. V. Lakshmanan, G. Stumpf, and A. Witt, ``A neural network for detecting and diagnosing tornadic circulations using the mesocyclone detection and near storm environment algorithms,'' in Preprints,21st Int'l Conf. on Information Processing Systems, (San Diego), p. J5.2, Amer. Meteor. Soc., Jan 2005.

  43. V. Lakshmanan, K. Hondl, D. MacGorman, and G. Stumpf, ``Preprints, the use of lightning mapping array data in WDSS-II,'' in 22nd Conf. on Severe Local Storms, (Hyannis, MA), p. P14.3, Amer. Meteor. Soc., 2004.

  44. V. Lakshmanan and M. Valente, ``Quality control of radar reflectivity data using satellite data and surface observations,'' in 20th Int'l Conf. on Inter. Inf. Proc. Sys. (IIPS) for Meteor., Ocean., and Hydr., (Seattle), p. 12.2, Amer. Meteor. Soc., Jan 2004.

  45. V. Lakshmanan, K. Hondl, G. Stumpf, and T. Smith, ``Quality control of WSR-88D data,'' in 31st Radar Conf., (Seattle), pp. 522-525, Amer. Meteor. Soc., Aug 2003.

  46. V. Lakshmanan, ``Motion estimator based on hierarchical clusters,'' in 19th Int'l Conf. on Inter. Inf. Proc. Sys. (IIPS) for Meteor., Ocean., and Hydr., (Long Beach, CA), Amer. Meteor. Soc., Feb. 2003.

  47. V. Lakshmanan, ``An extensible, multi-source meteorological algorithm development interface,'' in 21st Conf. on Severe Local Storms, (San Antonio, TX), Amer. Meteor. Soc., 2002.

  48. V. Lakshmanan, ``Statistical clustering for hierarchical storm identification,'' in 21st Conf. on Severe Local Storms, (San Antonio, TX), Amer. Meteor. Soc., 2002.

  49. R. Lynn and V. Lakshmanan, ``Virtual radar volumes: Creation, algorithm access and visualization,'' in 21st Conf. on Severe Local Storms, (San Antonio, TX), Amer. Meteor. Soc., 2002.

  50. V. Lakshmanan, ``Real-time merging of multisource data,'' in 21st Conf. on Severe Local Storms, (San Antonio, TX), Amer. Meteor. Soc., 2002.

  51. V. Lakshmanan, ``Real-time merging of multi-source data,'' in 19th Int'l Conf. on Inter. Inf. Proc. Sys. (IIPS) for Meteor., Ocean., and Hydr., (Long Beach, CA), Amer. Meteor. Soc., Feb. 2003.

  52. V. Lakshmanan, R. Rabin, and V. DeBrunner, ``Multiscale storm identification and forecast,'' J. Atm. Res., vol. 67, pp. 367-380, July 2003.

  53. V. Lakshmanan, ``Lossless coding and compression of radar reflectivity data,'' in 30th International Conf. on Radar Meteorology, (Munich), pp. 50-52, American Meteorological Society, July 2001.

  54. V. Lakshmanan, R. Rabin, and V. DeBrunner, ``Segmenting radar reflectivity data using texture,'' in 30th International Conf. on Radar Meteorology, (Munich), pp. 50-52, American Meteorological Society, July 2001.

  55. V. Lakshmanan, R. Rabin, and V. DeBrunner, ``Identifying and tracking storms in satellite images,'' in Second Artificial Intelligence Conf., (Long Beach, CA), pp. 90-95, American Meteorological Society, 2000.

  56. V. Lakshmanan and A. Witt, ``Detecting bounded weak echo regions,'' in 28th International Conf. on Radar Meteorology, (Austin, TX), American Meteorological Society, 1997.

Non-refereed presentations as second author or higher omitted.

Panels, working groups, Invited Talks, etc.



Lakshman : lakshman@nssl.noaa.gov