Progress and challenges with Warn-on-Forecast

Atmospheric Research

Volumn 123, Issue , 2013, Pages 2-16

  Stensrud, David J ^a   Wicker, Louis J ^a   Xue, Ming ^b   Dawson, Daniel T ^a,b   Yussouf, Nusrat ^a,b   Wheatley, Dustan M ^a,b   Thompson, Therese E ^a,b   Snook, Nathan A ^b   Smith, Travis M ^a,b   Schenkman, Alexander D ^b   Potvin, Corey K ^a   Mansell, Edward R ^a   Lei, Ting ^b   Kuhlman, Kristin M ^a,b   Jung, Youngsun ^b   Jones, Thomas A ^a,b   Gao, Jidong ^a   Coniglio, Michael C ^a   Brooks, Harold E ^a   Brewster, Keith A ^b  

^a NATIONAL SEVERE STORMS LABORATORY   (United States)

^b UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

Ensemble forecasts; Real time analyses; Warnings

Indexed keywords

ASSIMILATION SYSTEM; CONVECTIVE WEATHER; CURRENT STATUS; ENSEMBLE FORECASTS; FLASH FLOOD; FORECAST SYSTEMS; LEAD TIME; MESOSCALE; MESOSCALE CONVECTIVE SYSTEM; MULTIPLE RADAR; NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION; OPERATIONAL FORECASTERS; PRODUCTION OF; PROVIDE GUIDANCES; REAL TIME ANALYSIS; SHORT RANGE ENSEMBLE FORECASTS; SUPERCELL THUNDERSTORMS; VARIATIONAL ASSIMILATION; WARNINGS; WEATHER WARNINGS;

FLOODS; METEOROLOGICAL PROBLEMS; RADAR; RESEARCH; THUNDERSTORMS;

FORECASTING;

CONVECTIVE SYSTEM; DATA ASSIMILATION; ENSEMBLE FORECASTING; FLASH FLOOD; MESOSCALE METEOROLOGY; THUNDERSTORM; WARNING SYSTEM; WEATHER FORECASTING;

EID: 84874349872     PISSN: 01698095     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosres.2012.04.004     Document Type: Review

References (50)

1. Anderson J.L. An ensemble adjustment Kalman filter for data assimilation. Mon. Weather Rev. 2001, 129:2884-2903.
2. Scalable implementations of ensemble filter algorithms for data assimilation. J. Atmos. Oceanic Technol. 2007, 24:1452-1463.
3. Anderson J.L., Hoar T., Raeder K., Liu H., Collins N., Torn R., Avellano A. The data assimilation research testbed: a community facility. Bull. Amer. Meteor. Soc. 2009, 90:1283-1296.
4. Benjamin S.G., Devenyi D., Weygandt S.S., Brundage K.J., Brown J.M., Grell G.A., Kim D., Schwartz B.E., Smirnova T.G., Smith T.L. An hourly assimilation-forecast cycle: The RUC. Mon. Weather Rev. 2004, 132:495-518.
5. Bluestein H.B. The formation and early evolution of the Greensburg, Kansas, tornadic supercell on 4 May 2007. Weather Forecast. 2009, 24:899-920.
6. Brooks H.E. Tornado warning performance in the past and future: a perspective from signal detection theory. Bull. Amer. Meteor. Soc. 2004, 85:837-843.
7. Brooks H.E., Doswell C.A. Deaths in the 3 May 1999 Oklahoma City tornado from a historical perspective. Weather Forecast. 2002, 17:354-361.
8. Coniglio M.C., Stensrud D.J., Wicker L.J. Effects of upper-level shear on the structure and maintenance of strong quasi-linear mesoscale convective systems. J. Atmos. Sci. 2006, 63:1231-1252.
9. Crum T.D., Alberty R.L. The WSR-88D and the WSR-88D operational support facility. Bull. Amer. Meteor. Soc. 1993, 74:1669-1687.
10. Dawson D.T., Wicker L.J., Mansell E.R., Tanamachi R.L. Impact of the environmental low-level wind profile on ensemble forecasts of the 4 May 2007 Greensburg, KS tornadic storm and associated mesocyclones. Mon. Weather Rev. 2012, 140:696-716.
11. Elmore K.L., Stensrud D.J., Crawford K.C. Explicit cloud-scale models for operational forecasts: a note of caution. Weather Forecast. 2002, 17:873-884.
12. Evensen G. Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 1994, 99(C5):10 143-10 162.
13. Evensen G. Advanced data assimilation for strongly nonlinear dynamics. Mon. Weather Rev. 1997, 125:1342-1354.
14. Gao J., Stensrud D.J. Assimilation of reflectivity data in a convective-scale, cycled 3DVAR framework with hydrometeor classification. J. Atmos. Sci. 2012, 69:1054-1065.
15. Gao J., Xue M., Brewster K., Carr F., Droegemeier K.K. New development of a 3DVAR system for a nonhydrostatic NWP model. Preprints, 15th Conf. Num. Wea. Prediction, 19th Conf. Wea. Anal. Forecasting, San Antonio, TX, Amer. Meteor. Soc 2002, 339-341.
16. Gao J., Xue M., Brewster K., Carr F. A 3DVAR method for Doppler radar wind assimilation with recursive filter. Preprints, 31st Conf. Radar Meteor., Seatle, WA, Amer. Meteor. Soc., Paper P1C.4 2003.
17. Gao J., Xue M., Brewster K., Droegemeier K.K. A three-dimensional variational data assimilation method with recursive filter for single-Doppler radar. J. Atmos. Oceanic. Technol. 2004, 21:457-469.
18. Gilmore M.S., Straka J.M., Rasmussen E.N. Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme. Mon. Weather Rev. 2004, 132:2610-2627.
19. Hu M., Xue M. Impact of configurations of rapid intermittent assimilation of WSR-88D radar data for the 8 May 2003 Oklahoma City tornadic thunderstorm case. Mon. Weather Rev. 2007, 135:507-525.
20. Hu M., Xue M., Brewster Keith 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. Weather Rev. 2006, 134:675-698.
21. Hunt B.R., Kostelich E.J., Szunyogh I. Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D 2007, 230:112-126.
22. Jones, T.A., Stensrud, D.J., in press. Assimilating AIRS temperature and mixing ratio profiles using an Ensemble Kalman Filter approach for convective-scale forecasts. Wea. Forecasting. doi:10.1175/WAF-D-11-00090.1.
23. Jung, Y., Xue, M., Tong, M., in press. 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. doi:10.1175/MWR-D-11-00032.1.
24. Kuhlman K.M., Smith T.M., Gao J., Manross K.L., Ortega K.L., Stumpf G.J. Real-Time 3DVAR Analyses and Forecaster Evaluation During the 2011 Hazardous Weather Testbed Experimental Warning Program. Preprints, 16th Symp. on Integrated Obs. and Assimilation Systems for the Atmos., Oceans, and Land Surface (IOAS-AOLS), New Orleans, LA., Amer. Meteor. Soc., Paper 3.6 2012.
25. Lakshmanan V., Smith T., Stumpf G., Hondl K. The warning decision support system-integrated information. Weather Forecast. 2007, 22:596-612.
26. Lei T., Xue M., Yu T. Multi-scale analysis and prediction of the 8 May 2003 Oklahoma City tornadic supercell storm assimilating radar and surface network data using EnKF. Extended abstract, 13th Conf. of IOAS-AOLS, AMS Meetings 2008, Paper 6.4 2009.
27. Lemon L.R., Umscheid M. The Greensburg, KS tornadic storm: a storm of extremes. Extended abstract, 24th Conference on Severe Local Storms, Savannah, Georgia, American Meteorological Society 2008.
28. Martin W.J., Xue M. Initial condition sensitivity analysis of a mesoscale forecast using very-large ensembles. Mon. Weather Rev. 2006, 134:192-207.
29. McLaughlin D., Pepyne D., Chandrasekar V., Philips B., Kurose J., Zink M., Droegemeier K., Cruz-Pol S., Junyent F., Brotzge J., Westbrook D., Bharadwaj N., Wang Y., Lyons E., Hondl K., Liu Y., Knapp E., Xue M., Hopf A., Kloesel K., DeFonzo A., Kollias P., Brewster K., Contreras R., Dolan B., Djaferis T., Insanic E., Frasier S., Carr F. Short-wavelength technology and the potential for distributed networks of small radar systems. Bull. Amer. Meteor. Soc. 2009, 90:1797-1817.
30. Ortega K.L., Smith T.M., Manross K.L., Scharfenberg K.A., Witt A., Kolodziej A.G., Gourley J.J. The severe hazards analysis and verification experiment. Bull. Amer. Meteor. Soc. 2009, 90:1519-1530.
31. Pielke R., Carbone R.E. Weather impacts, forecasts, and policy: an integrated perspective. Bull. Amer. Meteor. Soc. 2002, 83:393-403.
32. Potvin C.K., Shapiro A., Xue M. Impact of a vertical vorticity constraint in variational dual-Doppler wind analysis: tests with real and simulated supercell data. J. Atmos. Oceanic Technol. 2012, 29:32-49.
33. Purser R.J., Wu W.-S., Parrish D., Roberts N.M. Numerical aspects of the application of recursive filters to variational statistical analysis. Part II: spatially inhomogeneous and anisotropic general covariances. Mon. Weather Rev. 2003, 131:1536-1548.
34. Romine G.S., Burgess D.W., Wilhelmson R.B. A dual-polarization-radar-based sssessment of the 8 May 2003 Oklahoma City area tornadic supercell. Mon. Weather Rev. 2008, 136:2849-2870.
35. Schenkman A., Xue M., Shapiro A., Brewster K., Gao J. The analysis and prediction of the 8-9 May 2007 Oklahoma tornadic mesoscale convective system by assimilating WSR-88D and CASA radar data using 3DVAR. Mon. Weather Rev. 2011, 139:224-246.
36. Shapiro A., Potvin C.K., Gao J. Use of a vertical vorticity equation in variational dual-Doppler wind analysis. J. Atmos. Oceanic Technol. 2009, 26:2089-2106.
37. Simmons K.M., Sutter D. WSR-88D radar, tornado warnings, and tornado casualties. Weather Forecast. 2005, 20:301-310.
38. Simmons K.M., Sutter D. Economic and societal impacts of tornadoes. Amer. Meteor. Soc 2011, 282 pp.
39. Skamarock W.C., Klemp J.B., Dudhia J., Gill D.O., Barker D.M., Duda M.G., Huang X.-Y., Wang W., Powers J.G. A description of the Advanced Research WRF version 3. NCAR Tech Note NCAR/TN-475+STR 2008, 113 pp. [Available from UCAR Communications, P. O. Box 3000, Boulder, CO 80307.].
40. Smith T.S., Kulman K.M., Ortega K.L., Manross K.L., Burgess D.W., Gao J., Stensrud D.J. A survey of real-time 3DVAR analyses conducted during the 2010 Experimental Warning Program spring experiment. Extended abstract, 25th Conference on Severe Local Storms, Denver, CO, USA, AMS, P5.7 2010.
41. Snook N., Xue M. Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstorms. Geophys. Res. Lett. 2008, 35:L24803. doi:10.1029/2008GL035866.
42. Snook N., Xue M., Jung J. Analysis of a tornadic meoscale convective vortex based on ensemble Kalman filter assimilation of CASA X-band and WSR-88D radar data. Mon. Weather Rev. 2012, 139:3446-3468.
43. Snook, N., Xue, M., Jung, Y., in press. Ensemble probabilistic forecasts of a tornadic mesoscale convective system from ensemble Kalman filter analyses using WSR-88D and CASA radar data. Mon. Wea. Rev. doi:10.1175/MWRD-11-00117.1.
44. Stensrud D.J. Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models 2007, Cambridge University Press, 459 pp.
45. Stensrud D.J., Xue M., Wicker L.J., Kelleher K.E., Foster M.P., Schaefer J.T., Schneider R.S., Benjamin S.G., Weygandt S.S., Ferree J.T., Tuell J.P. Convective-scale warn on forecast: a vision for 2020. Bull. Amer. Meteor. Soc. 2009, 90:1487-1499.
46. Tong M., Xue M. Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS Experiments. Mon. Weather Rev. 2005, 133:1789-1807.
47. Tong M., Xue M. 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. Weather Rev. 2008, 136:1630-1648.
48. Vasiloff S.V., Seo D.J., Howard K.W., Zhang J., Kitzmiller D.H., Mullusky M.G., Krajewski W.F., Brandes E.A., Rabin R.M., Berkowitz D.S., Brooks H.E., McGinley J.A., Kuligowski R.J., Brown B.G. Improving QPE and very short term QPF: an initiative for a community-wide integrated approach. Bull. Amer. Meteor. Soc. 2007, 88:1899-1911.
49. Whitaker J.S., Hamill T.M. Ensemble data assimilation without perturbed observations. Mon. Weather Rev. 2002, 132:1913-1924.
50. Xue M., Wang D.-H., Gao J.-D., Brewster K., Droegemeier K.K. The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteor. Atmos. Physics 2003, 82:139-170.