Joint impact of forecast tendency and state error biases in ensemble kalman filter data assimilation of inner-core tropical cyclone observations

Monthly Weather Review

Volumn 141, Issue 9, 2013, Pages 2992-3006

  Vukicevic, Tomislava ^a   Reasor, Paul ^a   Aberson, Sim D ^a   Marks, Frank ^a   Aksoy, Altug ^b   Sellwood, Kathryn J ^b  

^a ATLANTIC OCEANOGRAPHIC AND METEOROLOGICAL LABORATORY   (United States)

^b UNIVERSITY OF MIAMI   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AIRBORNE OBSERVATIONS; ENSEMBLE DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; HIGH-RESOLUTION DATA ASSIMILATIONS; PLANETARY BOUNDARY LAYERS; SECONDARY CIRCULATION; SHORT-TERM FORECASTS; WEATHER RESEARCH AND FORECASTING;

ERRORS; HURRICANES;

WEATHER FORECASTING;

BOUNDARY LAYER; DATA ASSIMILATION; ENSEMBLE FORECASTING; ERROR ANALYSIS; HURRICANE; KALMAN FILTER; TROPICAL CYCLONE; WEATHER FORECASTING;

EID: 84884306094     PISSN: 00270644     EISSN: 15200493     Source Type: Journal    
DOI: 10.1175/MWR-D-12-00211.1     Document Type: Article

References (33)

1. Aberson, S. D., 2010: 10 years of hurricane synoptic surveillance (1997-2006). Mon. Wea. Rev., 138, 1536-1549.
2. Aberson, S. D., M. L. Black, R. A. Black, R. W. Burpee, J. J. Cione, C. W. Landsea, and F. D. Marks Jr., 2006: Thirty years of tropical cyclone research with the NOAA P-3 aircraft. Bull. Amer. Meteor. Soc., 87, 1039-1055.
3. Aksoy, A., S. Lorsolo, T. Vukicevic, K. J. Sellwood, S. D. Aberson, F. Zhang, 2012: The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for high-resolution data: The impact of airborne Doppler radar observations in an OSSE. Mon. Wea. Rev., 140, 1843-1862.
4. Aksoy, A., S. D. Aberson, T. Vukicevic, K. J. Sellwood, S. Lorsolo, X. Zhang, 2013: Assimilation of high-resolution tropical cyclone observations with an ensemble Kalman filter using NOAA/AOML/HRD's HEDAS: Evaluation of the 2008-11 vortex-scale analyses. Mon. Wea. Rev., 141, 1842-1865.
5. Bao, J.-W., S. G. Gopalakrishnan, S. A. Michelson, F. D. Marks, M. T. Montgomery, 2012: Impact of physics representations in the HWRFX on simulated hurricane structure and pressure-wind relationships. Mon. Wea. Rev., 140, 3278-3299.
6. Berg, R. J., L. A. Avila, 2011: Atlantic hurricane season of 2009. Mon. Wea. Rev., 139, 1049-1069.
7. Bui, H. H., K. R. Smith, M. T. Montgomery, J. Peng, 2009: Balanced and unbalanced aspects of tropical-cyclone intensification. Quart. J. Roy. Meteor. Soc., 135, 1715-1731.
8. Davis, C., Coauthors, 2008: Prediction of landfalling hurricanes with the Advanced Hurricane WRF Model. Mon. Wea. Rev., 136, 1990-2005.
9. Gall, R., J. Franklin, F. Marks, E. N. Rappaport, F. Toepfer, 2013: The Hurricane Forecast Improvement Project. Bull. Amer. Meteor. Soc., 94, 329-343.
10. Gamache, J. F., 1997: Evaluation of a fully three-dimensional variational Doppler analysis technique. Preprints, 28th Conf. on Radar Meteorology, Austin, TX, Amer.Meteor. Soc., 422-442.
11. Gaspari, G., S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125, 723-757.
12. Gopalakrishnan, S.G.,Coauthors, 2002: An operationalmultiscale hurricane forecasting system. Mon. Wea. Rev., 130, 1830-1847.
13. Gopalakrishnan, S.G., N. Surgi, R. Tuleya, Z. Janjic, 2006: NCEP's two-wayinteractive- moving-nest NMM-WRF modeling system for hurricane forecasting. Preprints, 27th Conf. on Hurricanes and Tropical Meteorology, Monterey, CA, Amer. Meteor. Soc., 7A.3. [Available online at https://ams.confex.com/ams/ 27Hurricanes/techprogram/paper_107899.htm.]
14. Gopalakrishnan, S.G., F. Marks Jr., X. Zhang, J.-W. Bao, K.-S. Yeh, R. Atlas, 2011: The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Mon. Wea. Rev., 139, 1762-1784.
15. Hamill, T. M., J. S. Whitaker, M. Fiorino, S. J. Benjamin, 2011a: Predictions of 2010's tropical cyclones using the GFS and ensemble-based data assimilation methods. Mon. Wea. Rev., 139, 3243-3247.
16. Hamill, T. M., J. S. Whitaker, D. T. Kleist, M. Fiorino, S. J. Benjamin, 2011b: Global ensemble predictions of 2009's tropical cyclones initialized with an ensemble Kalman filter. Mon. Wea. Rev., 139, 668-688.
17. Janjic, Z. I., 2003: A nonhydrostatic model based on a new approach. Meteor. Atmos. Phys., 82, 271-285.
18. Janjic, Z. I., R. Gall, M. E. Pyle, 2010: Scientific documentation of the NMM solver. NCAR Tech. Note NCAR/TN-4771STR, 210 pp. [Available from the National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000.]
19. Lorenz, E., 1969: The predictability of a flow which possesses many scales of motion. Tellus, 21, 289-307.
20. Montgomery, M., S. K. Smith, 2011: Paradigms for tropicalcyclone intensification. Quart. J. Roy. Meteor. Soc., 137, 1-31.
21. Poterjoy, J., F. Zhang, 2011: Dynamics and structure of forecast error covariance in the core of a developing hurricane. J. Atmos. Sci., 68, 1586-1606.
22. Rappaport, E. N., 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395-419.
23. Reasor, P. D., M. D. Eastin, J. F. Gamache, 2009: Rapidly intensifying Hurricane Guillermo (1997). Part I: Lowwavenumber structure and evolution. Mon. Wea. Rev., 137, 603-631.
24. Rogers, R., S. Lorsolo, P. Reasor, J. Gamache, F. Marks, 2012: Multiscale analysis of tropical cyclone kinematic structure from airborne Doppler radar composites. Mon.Wea. Rev., 140, 77-99.
25. Rotunno, R., C. Snyder, 2008: A generalization of Lorenz's model for the predictability of flows with many scales of motion. J. Atmos. Sci., 65, 1063-1076.
26. Shapiro, L. J., H. E. Willoughby, 1982: The response of balanced hurricanes to local sources of heat and momentum. J. Atmos. Sci., 39, 378-394.
27. Snyder, C., F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 1663-1677.
28. Weng, Y., F. Zhang, 2012: Assimilating airborne Doppler radar observations with an ensemble Kalman filter for convectionpermitting hurricane initialization and prediction: Katrina (2005). Mon. Wea. Rev., 140, 841-859.
29. Whitaker, J. S., T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations.Mon. Wea. Rev., 130, 1913-1924.
30. Xiao, Q., Z. Zhang, C. Davis, J. Tuttle, G. Holland, P. J. Fitzpatrick, 2009: Experiments of hurricane initialization with airborne Doppler radar data for the Advanced Research Hurricane WRF (AHW) model. Mon. Wea. Rev., 137, 2758- 2777.
31. Zhang, F., Y. Weng, J. F. Gamache, F. D. Marks, 2011: Performance of convection-permitting hurricane initialization and prediction during 2008-2010 with ensemble data assimilation of inner-core airborne Doppler radar observations. Geophys. Res. Lett., 38, L15810, doi:10.1029/2011GL048469.
32. Zhang, J. A., R. F. Rogers, D. S. Nolan, F. D. Marks, 2011: On the characteristic height scales of the hurricane boundary layer. Mon. Wea. Rev., 139, 2523-2535.
33. Zhang, X., T. Quirino, K.-S. Yeh, S. Gopalakrishnan, F. Marks, S. Goldenberg, S. Aberson, 2011: HWRFx: Improving hurricane forecasts with high-resolution modeling. Comput. Sci. Eng., 13, 13-21, doi:10.1109/MCSE.2010.121.