Convective-scale warn-on-forecast system: A vision for 2020

Bulletin of the American Meteorological Society

Volumn 90, Issue 10, 2009, Pages 1487-1499

  Stensrud, David J ^a   Ming, Xue ^b   Wicker, Louis J ^a   Kelleher, Kevin E ^a   Foster, Michael P ^c   Schaefer, Joseph T ^c   Schneider, Russell S ^c   Benjamin, Stanley G ^d   Weygandt, Stephen S ^d   Ferree, John T ^c   Tuell, Jason P ^c  

^a NATIONAL SEVERE STORMS LABORATORY   (United States)

^b UNIVERSITY OF OKLAHOMA   (United States)

^c NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^d EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONVECTIVE STORMS; FORECAST MODEL; FORECAST SYSTEMS; HIGH RESOLUTION; INTERNAL STRUCTURE; LEAD TIME; NEAR-REAL TIME; NUMERICAL MODELS; NUMERICAL WEATHER PREDICTION MODELS; RADAR DATA; RADIAL-VELOCITY OBSERVATIONS; WARNING INFORMATIONS;

DOPPLER EFFECT; DOPPLER RADAR; FORECASTING; NUMERICAL METHODS; RADAR; SATELLITE OBSERVATORIES; THUNDERSTORMS;

MATHEMATICAL MODELS;

EID: 70450178185     PISSN: 00030007     EISSN: None     Source Type: Journal    
DOI: 10.1175/2009BAMS2795.1     Document Type: Article

References (66)

1. Aksoy, A., D. C. Dowell, and. C. Snyder, 2009: A multicase comparative assessment, of the ensemble Kalman filter for assimilation of radar observations. Part. I: Storm-scale analyses. Mon. Wea. Rev., 137, 1805-1824.
2. Anderson, J. L., and. N. Collins, 2007: Scalable implementations of ensemble filter algorithms for data assimilation. J. Atmos. Oceanic Technol., 24, 1452-1463.
3. Benjamin, S. G., and Coauthors, 2004: An hourly assimilation-forecast cycle: The RUC. Mon. Wea. Rev., 132, 495-518.
4. -, and Coauthors, 2008: Implementation of the radar-enhanced RUC. 13th Conf. on Aviation, Range, and Aerospace Meteorology, New Orleans, LA, Amer. Meteor. Soc., 6.2. [Available online at http://ams.confex.com/ams/88A.nnual/ techprogram/ paper-133648.htm.]
5. Brooks, H. E., and C. A. Doswell, 2002: Deaths in the 3 May 1999 Oklahoma City tornado from a historical perspective. Wea. Forecasting, 17, 354-361. (Pubitemid 34938517)
6. Bryan, G. H., J. C. Wyngaard, and I. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131, 2394-2416.
7. Caya, A., J. Sun, and C. Snyder, 2005: A. comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation. Mon. Wea. Rev., 133, 3081-3094. (Pubitemid 41782870)
8. Crum, T. D., and R. L. Alberty, 1993: The WSR-88D and the WSR-88D Operational Support Facility. Bull. Amer. Meteor. Soc., 74, 1669-1687.
9. -, R. E. Saffle, and J. W. Wilson, 1998: An update on the NEXRAD program and future WSR-88D support, to operations. Wea. Forecasting, 13, 253-262.
10. Davis, C., and Coauthors, 2008: Prediction of landfalling hurricanes with the advanced hurricane WRF model. Mon. Wea. Rev., 136, 1990-2005.
11. Done, J., C. A. Davis, and M. L. Weisman, 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecasting (WRF) model. Atmos. Sci. Lett, 5, 110-117. (Pubitemid 43173548)
12. Dowell, D. C., and L. J. Wicker, 2009: Additive noise for storm-scale ensemble data assimilation. J. Atmos. Oceanic Technol., 26, 911-927.
13. -, F. Zhang, L. J. Wicker, C. Snyder, and N. A. Crook, 2004: Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132, 1982-2005.
14. Droegemeier, K. K., 1997: The numerical prediction of thunderstorms: Challenges, potential benefits and results from real-time operational tests. WMO Bulletin, 46, 324-336.
15. Elmore, K. L., D. J. Stensrud, and K. C. Crawford, 2002: Explicit cloud-scale models for operational forecasts: A note of caution. Wea. Forecasting, 17, 873-884.
16. Erlingis, J. M., J. J. Gourley, T. M. Smith, and K.L. Ortega, 2009: Development of a detailed database of flash flood, observations. Preprints, 23rd Conf. on Hydrology, Phoenix, AZ, Amer. Meteor. Soc., JP2.8, [Available online at http://ams.confex.com/ a.ms/89annual/techprogra.m/pape-148661.htm.]
17. Friedrich, K., M. Hagen, and T. Einfalt, 2006: A quality control concept for radar reflectivity, Polarimetrie parameters, and Doppler velocity. J. Atmos. Oceanic Technol., 23, 865-887. (Pubitemid 44227123)
18. Gao, J., and M. Xue, 2008: An efficient dual-resolution approach for ensemble data assimilation and tests with simulated Doppler radar data. Mon. Wea. Rev., 136, 945-963. (Pubitemid 351753156)
19. -, D. Stensrud, and M. Xue, 2008: Importance of environmental variability to storm-scale radar data assimilation and very short range NWP. Preprints, 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 9B.2. [Available online at http://ams.confex.com/ams/24SLS/techprogram/ paper-141814.htm.]
20. Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Wea. Rev., 132, 2610-2627.
21. Gong, L. W., and. Q. Xu, 2003: A three-step dealiasing method for Doppler velocity data quality control. J. Atmos. Oceanic Technol., 20, 1738-1748.
22. Hu, M., M. Xue, and K. Brewster, 2006: 3DVAR and cloud analysis with WSR-88D level-II data for the prediction of the Fort. Worth, Texas, tornadic thunderstorms. Part. I: Cloud analysis and its impact. Mon. Wea. Rev., 134, 675-698.
23. Jung, Y., M. Xue, G. Zhang, and J. M. Straka, 2008: Assimilation of simulated Polarimetrie radar data for a convective storm using the ensemble Kalman filter. Part II: Impact of Polarimetrie data on storm analysis. Mon. Wea. Rev., 136, 2246-2260.
24. Kain, I. S., P. R. Janish, S. I. Weiss, M. E. Baldwin, R. S. Schneider, and H. E. Brooks, 2003: Collaboration between, forecasters and research scientists at the NSSL and SPC: The spring program. Bull. Amer. Meteor. Soc., 84, 1797-1806.
25. -, S. I. Weiss, I. I. Levit, M. E. Baldwin, and D. R. Bright, 2006: Examination of convections-allowing configurations of the WRF model for the prediction of severe convective weather: The SPC/NSSL spring program 2004. Wea. Forecasting, 21, 167-181.
26. Kelleher, K. E., and Coauthors, 2007: Project CRAFT: A real-time delivery system for NEXRAD level II data via the Internet. Bull. Amer. Meteor. Soc., 88, 1045-1057.
27. Kong, F., K. K. Droegemeier, and N. L. Hickmon, 2007a: Multiresolution ensemble forecasts of an observed, tornadic thunderstorm system, Part. II: Storm-scale experiments. Mon. Wea. Rev., 135, 759-782. (Pubitemid 46542135)
28. -, and Coauthors, 2007b: Preliminary analysis on the real-time storm-scale ensemble forecasts produced as a part, of the NOAA Hazardous Weather Testbed 2007 Spring Experiment. Preprints, 22nd Conf. Weather Analysis and Forecasting and 18th Conf. Numerical Weather Prediction, Salt Lake City, UT, Amer. Meteor. Soc., 3B.2. [Available online at http:// ams.coniex.com/ams/22WA. F18NWP/techprog.ram/ pape-124667.htm.]
29. -, and Coauthors, 2008: Real-time storm-scale ensemble forecast 2008 spring experiment. Preprints, 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 12.3. [Available online at http://ams.confex.com/ams/24SLS/ techprogram/ paper-141827.htm.]
30. Kuhlman, K. M., T. M. Smith, G. J. Stumpf, K. L. Ortega, and K. L. Manross, 2008: Experimental probabilistic hazard information in practice: Results from the 2008 EWP spring program. Extended Abstracts, 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 8A.2. [Available online at. http://ams. confex.com/ams/24SLS/techprogram/pape-142027. htm.]
31. -, E. Gruntfest, G.J. Stumpf, and K. A. Scharfenberg, 2009: Beyond, storm-based warnings: An advanced WASTS Workshop to study communication of probabilistic hazardous weather information. Extended Abstracts, Fourth Symp. on Policy and SocioEconomic Research, Phoenix, AZ, Amer. Meteor. Soc., 3.5. [Available online at. http://ams.confex. com/ams/89annual/techprogram/ programexpanded.-524.htm.]
32. Lakshmanan, V., A. Fritz, T. Smith, K. Hondl, and G. Stumpf, 2007a: An automated technique to quality control radar reflectivity data. J. Appl. Meteor. Climatol., 46, 288-305. (Pubitemid 46672196)
33. -, T. Smith, G. Stumpf, and K. Hondl, 2007b: The warning decision support system-integrated information. Wea. Forecasting, 22, 596-612.
34. Langston, C., J. Zhang, and K.Howard, 2007: Four-dimensional dynamic radar mosaic J. Atmos. Oceanic Technol., 24, 776-790.
35. Lewis, J., S. Lakshmivarahan, and S. Dhall, 2006: Dynamic Data Assimilation: A Least Squares Approach. Cambridge University Press, 654 pp.
36. Lilly, D. K., 1990: Numerical prediction of thunderstorms-Has its time come? Quart. J. Roy. Meteor. Soc., 116, 779-798.
37. Liu, S., Q. Xu, and P. Zhang, 2005: Quality control of Doppler velocities contaminated by migrating birds. Part. II: Bayes identification and probability tests. J. Atmos. Oceanic Technol., 22, 1114-1121, (Pubitemid 41419740)
38. Martin, W. J., and M. Xue, 2006: Sensitivity analysis of convection of the 24 May 2002 IHOP case using very large ensembles. Mon. Wea. Rev., 134, 192-207.
39. Morss, R. E., O. V. Wilhelmi, M. W. Downton, and E. Gruntfest, 2005: Flood risk, uncertainty, and scientific information for decision making: Lessons from an interdisciplinary project. Bull. Amer. Meteor. Soc., 86, 1593-1601.
40. Ortega, K. L., T. M. Smith, K. L. Manross, K. A. Scharfenberg, A. Witt, A. G. Kolodziej, and J. J. Gourley, 2009: Severe Hazards Analysis and Verification Experiment. Bull. Amer. Meteor. Soc., 90, 1519-1530.
41. Pielke, R., and R. E. Carbone, 2002: Weather impacts, forecasts, and policy: An integrated perspective. Bull. Amer. Meteor. Soc., 83, 393-403.
42. Rasmussen, E. N., and D. O. Blanchard, 1998: A. baseline climatology of sounding-derived supercell and tornado forecast parameters. Wea. Forecasting, 13, 1148-1164.
43. Schmit, T. J., W. F. Feltz, W. P. Menzel, J. Jung, A. P. Noel, J. N. Heil, J. P. Nelson, and G. S. Wade, 2002: Validation and use of GOES sounder moisture information. Wea. Forecasting, 17, 139-154.
44. Simmons, K. M., and D. Sutter, 2005: WSR-88D radar, tornado warnings, and tornado casualties. Wea. Forecasting, 20, 301-310.
45. Smith, T. L., S. G. Benjamin, J. M. Brown, S.S. Weygandt, T. Smirnova, and B. E. Schwartz, 2008: Convection forecasts from the hourly updated, 3-km High Resolution Rapid. Refresh Model. Preprints, 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 11.1. [Available online at http://ams.confex.com/ ams/24SLS/techprogram/paper-142055.htm.]
46. Snook, N., and M. Xue, 2008: Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms. Geophys. Res. Lett, 35, L24803, doi:10.1029/2008GL035866.
47. Snyder, C., and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 1663-1677. (Pubitemid 37124296)
48. Stumpf, G. J., T. M. Smith, K. L. Manross, and D. Andra, 2008: The Experimental Warning Program 2008 spring experiment at the NOAA Hazardous Weather Testbed. Extended Abstracts, 24th Conf. on Severe Local Storms, Savannah, GA, Amer, Meteor. Soc., 8A.1. [Available online at. http://ams.confex.com/ ams/24SLS/techprogram/paper-141712.htm.]
49. Sun, J., and Y. Zhang, 2008: Analysis and prediction of a squall line observed, during IHOP using multiple WSR-88D observations. Mon. Wea. Rev., 136, 2364-2388.
50. Thompson, R. L., R. Edwards, J. A. Hart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea. Forecasting, 188, 1243-1261.
51. Tong, M., and M. Xue, 2005: Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments. Mon. Wea. Rev., 133, 1789-1807. (Pubitemid 41235939)
52. -, and -, 2008: Simultaneous estimation of microphysical parameters and atmospheric state with simulated radar data and ensemble square root Kalman filter. Part I: Sensitivity analysis and parameter identifiability. Mon. Wea. Rev., 136, 1630-1648.
53. Wandishin, M. S., D. J. Stensrud, S. L. Mullen, and L. J. Wicker, 2008: On the predictability of mesoscale convective systems: Two-dimensional simulations. Wea. Forecasting, 23, 773-785.
54. Weisman, M. L., and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112, 2479-2498.
55. -, C. Davis, W. Wang, K. W. Manning, and J. B. Klemp, 2008: Experiences with 0-36-h explicit, convective forecasts with the WRF-ARW model. Wea. Forecasting, 23, 407-437.
56. Weygandt, S. S., S. G. Benjamin, T. G. Smirnova, and J. M. Brown, 2008: Assimilation of radar reflectivity data using a diabatic digital filter within the Rapid Update Cycle. Preprints, 12th Conf on IOAS-AOLS, New Orleans, LA, Amer. Meteor. Soc., 8.4. [Available online at http://ams.confex.com/ams/ 88Annual/ techprogram/paper-134081.htm.]
57. Xue, M., and Coauthors, 1996: The 1996 CAPS spring operational forecasting period: Realtime stormscale NWP, Part II: Operational summary and sample cases. Preprints, 11th Conf. on Numerical Weather Prediction. Norfolk, VA, Amer. Meteor. Soc., 297-300.
58. -, D. Wang, J. Gao, K. Brewster, and K. K. Droegemeier, 2003: The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteor. Atmos. Phys., 82, 139-170.
59. -, M. Tong, and K. K. Droegemeier, 2006: An OSSE framework based on the ensemble square root Kalman filter for evaluating the impact of data from radar networks on thunderstorm analysis and forecasters. J. Atmos. Oceanic Technol., 23, 46-66,
60. -, K. K. Droegemeier, and D. Weber, 2007a: Numerical prediction of high-impact local weather: A driver for petascale computing. Petascale Computing: Algorithms and Applications, D. A. Bader, Ed., Chapman and Hall, 103-124.
61. -, and Coauthors, 2007b: CAPS realtime stormscale ensemble and high-resolution forecasts as part of the NOAA Hazardous Weather Testbed 2007 Spring Experiment. Preprints, 22nd Conf. on Weather Analysis and Forecasting and 18th Conf. on Numerical Weather Predictions, Park City, UT, Amer. Meteor. Soc., 3B.1. [Available online at http:// ams.confex.com/ams/22WAF18NWP/techprogra.m/ paper-124587.htm.]
62. -, and Coauthors, 2008: CAPS realtime storm-scale ensemble and high-resolution forecasts as part of the NOAA Hazardous Weather Testbed 2008 spring experiment. Extended Abstracts, 24th Conf. Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 12.2. [Available online at http://ams.co.nfex.com/ a.ms/24SLS/techprogram/paper-142036.htm.]
63. -, and Coauthors, 2009: CAPS realtime 4-km multi-model convection-allowing ensemble and 1-km convection-resolving forecasts for the NOAA Hazardous Weather Testbed 2009 spring experiment. Preprints, 23rd Conf. on Weather Analysis and Forecasting, and 19th Conf. on Numerical Weather Predictions, Omaha, NE, Amer. Meteor. Soc., 16A.2. [Available online at. http://ams.confex.com/ ams/23WAF19NWP/techprogram/paper-154323. htm.]
64. Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convectivescale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238-1253.
65. Zhang, P., S. Liu, and Q. Xu, 2005: Quality control of Doppler velocities contaminated by migrating birds. Part. I: Feature extraction and quality control parameters. J. Atmos. and Oceanic Technol., 22, 1105-1113. (Pubitemid 41419739)
66. Zrnić, D. S., and Coauthors, 2007: Agile-beam phased array radar for weather observations. Bull. Amer. Meteor. Soc., 88, 1753-1766.