Impact of assimilating microwave radiances with a limited-area ensemble data assimilation system on forecasts of Typhoon Morakot

Weather and Forecasting

Volumn 27, Issue 2, 2012, Pages 424-437

  Schwartz, Craig S ^a   Liu, Zhiquan ^a   Chen, Yongsheng ^b   Huang, Xiang Yu ^a  

^a NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^b YORK UNIVERSITY   (Canada)

Author keywords

Data assimilation; Model initialization; Numerical weather prediction forecasting; Regional models

Indexed keywords

DATA ASSIMILATION; ENSEMBLE ADJUSTMENT KALMAN FILTER; ENSEMBLE DATA ASSIMILATION; FORECASTING MODELS; INTENSITY FORECASTS; MICROWAVE RADIANCES; MODEL INITIALIZATION; NUMERICAL WEATHER PREDICTION; PRECIPITATION FORECAST; RADIANCE ASSIMILATION; REGIONAL MODEL; TROPICAL CYCLONE PREDICTIONS;

ERROR STATISTICS; EXPERIMENTS; HURRICANES; WEATHER FORECASTING;

WAKES;

DATA ASSIMILATION; ENSEMBLE FORECASTING; KALMAN FILTER; MICROWAVE RADIATION; NUMERICAL MODEL; TYPHOON; WEATHER FORECASTING;

EID: 84863005627     PISSN: 08828156     EISSN: None     Source Type: Journal    
DOI: 10.1175/WAF-D-11-00033.1     Document Type: Article

References (52)

1. Anderson, J. L., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884-2903.
2. Anderson, J. L., 2003: A local least squares framework for ensemble filtering. Mon. Wea. Rev., 131, 634-642.
3. Anderson, J. L., T. Hoar, K. Raeder, H. Liu, N. Collins, R. Torn, and A. Arellano, 2009: The Data Assimilation Research Testbed: A community facility. Bull. Amer. Meteor. Soc., 90, 1283-1296.
4. Aravéquia, J. A., I. Szunyogh, E. J. Fertig, E. Kalnay, D. Kuhl, and E. J. Kostelich, 2011: Evaluation of a strategy for the assimilation of satellite radiance observations with the local ensemble transform Kalman filter. Mon. Wea. Rev., 139, 1932-1951.
5. Auligné, T., A. P. McNally, and D. P. Dee, 2007: Adaptive bias correction for satellite data in a numerical weather prediction system. Quart. J. Roy. Meteor. Soc., 133, 631-642.
6. Barker, D. M., W. Huang, Y.-R. Guo, A. Bourgeois, and X. N. Xio, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897-914.
7. Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He, 2010: Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part I: Description and single-observation experiments. Mon. Wea. Rev., 138, 1550-1566.
8. Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He, 2010: Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part II: One-month experiments with real observations. Mon. Wea. Rev., 138, 1567-1586.
9. Burgers, G., P. J. van Leeuwen, and G. Evensen, 1998: Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev., 126, 1719-1724.
10. Campbell, W. F., C. H. Bishop, and D. Hodyss, 2010: Vertical covariance localization for satellite radiances in ensemble Kalman filters. Mon. Wea. Rev., 138, 282-290.
11. Caplan, P., J. Derber, W. Gemmill, S. Y. Hong, H. L. Pan, and D. Parish, 1997: Changes to the 1995 NCEP operational medium-range forecast model analysis-forecast system. Wea. Forecasting, 12, 581-594.
12. Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569-585.
13. Chou, M.-D., and M. J. Suarez, 1994: An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, Vol. 3, 85 pp.
14. Dee, D. P., 2005: Bias and data assimilation. Quart. J. Roy. Meteor. Soc., 131, 3323-3343.
15. Derber, J. C., and W.-S. Wu, 1998: The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 2287-2299.
16. Evensen, G., 1994: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99, 10 143-10 162.
17. Grell, G. A., and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693, doi:10.1029/2002GL015311.
18. Hamill, T. M., J. S. Whitaker, M. Fiorino, and S. G. Benjamin, 2011: Global ensemble predictions of 2009's tropical cyclones initialized with an ensemble Kalman filter. Mon. Wea. Rev., 139, 668-688.
19. Han, Y., P. van Delst, Q. Liu, F. Weng, B. Yan, R. Treadon, and J. Derber, 2006: JCSDA Community Radiative Transfer Model (CRTM)-Version 1. NOAA Tech. Rep. NESDIS 122, 33 pp.
20. Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341.
21. Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796-811.
22. Houtekamer, P. L., H. L. Mitchell, G. Pellerin, M. Buehner, M. Charron, L. Spacek, and B. Hansen, 2005: Atmospheric data assimilation with an ensemble Kalman filter: Results with real observations. Mon. Wea. Rev., 133, 604-620.
23. Houtekamer, P. L., H. L. Mitchell, and X. Deng, 2009: Model error representation in an operational ensemble Kalman filter. Mon. Wea. Rev., 137, 2126-2143.
24. Kleist, D. T., D. F. Parrish, J. C. Derber, R. Treadon, W.-S. Wu, and S. Lord, 2009: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 1691-1705.
25. Li, J., and H. Liu, 2009: Improved hurricane track and intensity forecast using single field-of-view advanced IR sounding measurements. Geophys. Res. Lett., 36, L11813, doi:10.1029/2009GL038285.
26. Liu, H., and J. Li, 2010: An improvement in forecasting rapid intensification of Typhoon Sinlaku (2008) using clear-sky full spatial resolution advanced IR soundings. J. Appl. Meteor. Climatol., 49, 821-827.
27. Liu, H., J. Anderson, Y.-H. Kuo, and K. Raeder, 2007: Importance of forecast error multivariate correlations in idealized assimilation of GPS radio occultation data with the ensemble adjustment filter. Mon. Wea. Rev., 135, 173-185.
28. Meng, Z., and F. Zhang, 2008: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3DVAR in a real-data case study. Mon. Wea. Rev., 136, 522-540.
29. Meng, Z., and F. Zhang, 2008: Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part IV: Comparison with 3DVAR in a month-long experiment. Mon. Wea. Rev., 136, 3671-3682.
30. Meng, Z., and F. Zhang, 2011: Limited-area ensemble-based data assimilation. Mon. Wea. Rev., 139, 2025-2045.
31. Miyoshi, T., and Y. Sato, 2007: Assimilating satellite radiances with a local ensemble transform Kalman filter (LETKF) applied to the JMA global model (GSM). SOLA, 3, 37-40.
32. Miyoshi, T., Y. Sato, and T. Kadowaki, 2010: Ensemble Kalman filter and 4D-Var intercomparison with the Japanese operational global analysis and prediction system. Mon. Wea. Rev., 138, 2846-2866.
33. Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 663-16 682.
34. Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center's spectral statistical interpolation analysis system. Mon. Wea. Rev., 120, 1747-1763.
35. Rappaport, E. N., et al. 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395-419.
36. Simmons, A. J., and A. Hollingsworth, 2002: Some aspects of the improvement in skill of numerical weather prediction. Quart. J. Roy. Meteor. Soc., 128, 647-677.
37. Skamarock, W. C. et al. 2008: A description of the Advanced Research WRF, version 3. NCAR Tech. Note NCAR/TN-4751STR, 113 pp. [Available from UCAR Communications, P.O. Box 3000, Boulder, CO 80307.]
38. Szunyogh, I., E. J. Kostelich, G. Gyarmati, E. Kalnay, B. R. Hunt, E. Ott, E. Satterfield, and J. A. Yorke, 2008: A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus, 60, 113-130.
39. Tao, W.-K., and J. Simpson, 1993: The Goddard Cumulus Ensemble model. Part I: Model description. Terr. Atmos. Oceanic Sci., 4, 35-72.
40. Tao, W.-K., and J. Simpson, et al, 2003: Microphysics, radiation and surface processes in the Goddard Cumulus Ensemble (GCE) model. Meteor. Atmos. Phys., 82, 97-137.
41. Torn, R. D., 2010: Performance of a mesoscale ensemble Kalman filter (EnKF) during the NOAA high-resolution hurricane test. Mon. Wea. Rev., 138, 4375-4392.
42. Torn, R. D., and G. J. Hakim, 2009: Ensemble data assimilation applied to RAINEX observations of Hurricane Katrina (2005). Mon. Wea. Rev., 137, 2817-2829.
43. Torn, R. D., G. J. Hakim, and C. Snyder, 2006: Boundary conditions for limitedarea ensemble Kalman filters. Mon. Wea. Rev., 134, 2490-2502.
44. Warner, T. T., R. A. Peterson, and R. E. Treadon, 1997: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Meteor. Soc., 78, 2599-2617.
45. Whitaker, J. S., T. M. Hamill, X. Wei, Y. Song, and Z. Toth, 2008: Ensemble data assimilation with the NCEP Global Forecast System. Mon. Wea. Rev., 136, 463-482.
46. Xu, J., S. Rugg, L. Byerle, and Z. Liu, 2009: Weather forecasts by the WRF-ARW model with the GSI data assimilation system in the complex terrain areas of southwest Asia. Wea. Forecasting, 24, 987-1008.
47. Zapotocny, T. H., W. P. Menzel, J. A. Jung, and J. P. Nelson III, 2005: A four-season impact study of rawinsonde, GOES, and POES data in the Eta Data Assimilation System. Part II: Contribution of the components.Wea. Forecasting, 20, 178-198.
48. Zapotocny, T. H., J. A. Jung, J. F. Le Marshall, and R. E. Treadon, 2007: A twoseason impact study of satellite and in situ data in the NCEP GlobalData Assimilation System. Wea. Forecasting, 22, 887-909.
49. Zapotocny, T. H., J. A. Jung, J. F. Le Marshall, and R. E. Treadon, 2008:Atwo-season impact study of four satellite data types and rawinsonde data in the NCEP Global Data Assimilation System. Wea. Forecasting, 23, 80-100.
50. Zhang, F., Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 2105-2125.
51. Zhang, F., Y. Weng, J. A, Y.-H. Kuo, J. S. Whitaker, and B. Xie, 2010: Predicting Typhoon Morakot's catastrophic rainfall with a convectionpermitting mesoscale ensemble system. Wea. Forecasting, 25, 1816-1825.
52. Zhang, M., F. Zhang, X.-Y. Huang, and X. Zhang, 2011: Intercomparison of an ensemble Kalman filter with three- and four-dimensional variational data assimilation methods in a limited-area model over the month of June 2003. Mon. Wea. Rev., 139, 566-572.