Satellite Data Assimilation of Upper-Level Sounding Channels in HWRF with Two Different Model Tops

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  • Corresponding author: ZOU Xiaolei
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Supported by the NOAA Hurricane Forecast Improvement Program (HFIP) and National Natural Science Foundation of China(91337218).

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  • The Advanced Microwave Sounding Unit-A (AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) MetOp-A, the hyperspectral Atmospheric Infrared Sounder (AIRS) onboard Aqua, the High resolution In-fraRed Sounder (HIRS) onboard NOAA-19 and MetOp-A, and the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting (HWRF) system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.
  • Gustafsson, N., X. Y. Huang, X. Yang, et al., 2012: Four-dimensional variational data assimilation for a limited area model. Tellus, 64A, 14985, doi: 0.3402/tellusa.v64i0.14985.
    Tang, B., and K. Emanuel, 2010: Midlevel ventilations constraint on tropical cyclone intensity. J. Atmos. Sci., 67, 1817-1830.
    Han, Y, F. Weng, Q. Liu, et al., 2007: A fast radiative transfer model for SSMIS upper atmosphere sound-ing channels. J. Geophys. Res., 112, D11121, doi: 10.1029/2006JD008208.
    Kleist, D. T., D. F. Parrish, J. C. Derber, et al., 2009: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 1691-1705.
    Kurihara, Y., M. A. Bender, and R. J. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev., 121, 2030-2045.
    D-Var. Quart. J. R. Meteor. Soc., 135, 2100-2109.
    Leroux, M.-D., M. Plu, D. Barbary, et al., 2013: Dynamical and physical processes leading to tropical cyclone intensification under upper-level trough forcing. J. Atmos. Sci., 70, 2547-2565.
    Liu, Q., F. Weng, and S. J. English, 2011: An improved fast microwave water emissivity model. IEEE Trans. Geosci. Remote Sens., 49, 1238-1250.
    Marin, J., D. Raymond, and G. Raga, 2009: Intensification of tropical cyclones in the GFS model. Atmos. Chem. Phys., 9, 1407-1417.
    Purser, R. J., W.-S. Wu, D. F. Parrish, et al., 2003a: Nu-merical aspects of the application of recursive filters to variational statistical analysis. Part I: Spatially homogeneous and isotropic Gaussian covariances. Mon. Wea. Rev., 131, 1524-1535.
    McBride, J., and R. Zehr, 1981: Observational analysis of tropical cyclone formation. Part II: Comparison of non-developing versus developing systems. J. Atmos. Sci., 38, 1132-1151.
    McNally, A. P., P. D. Watts, J. A. Smith, et al., 2006: The assimilation of AIRS radiance data at ECMWF.Quart. J. Roy. Meteor. Soc., 132, 935-957.
    Mo, T., 1996: Prelaunch calibration of the Advanced Microwave Sounding Unit-A for NOAA-K. IEEE Trans. Microwave Theory Technol., 44, 1460-1469, doi: 10.1109/22.536029.
    Molinari, J., and D. Vollaro, 2010: Rapid intensification of a sheared tropical storm. Mon. Wea. Rev., 138, 3869-3885.
    Montmerle, T., F. Rabier, and C. Fischer, 2007: Relative impact of polar-orbiting and geostationary satellite radiances in the Aladin/France numerical weather prediction system. Quart. J. R. Meteor. Soc., 133, 655-671.
    Pagano, T. S., H. H. Aumann, S. E. Broberg, et al., 2002: On-board calibration techniques and test results for the Atmospheric Infrared Sounder (AIRS). Proceed-ings of SPIE on Earth Observing Systems VII, 7 July 2002, Seattle, USA.
    Pattanayak, S., U. C. Mohanty, and S. G. Gopalakrish-nan, 2011: Simulation of very severe cyclone Mala over Bay of Bengal with HWRF modeling system.Nat. Hazards, 63, 1413-1437, doi: 10.1007/s11069-011-9863-z.
    Pfeffer, R. L., and M. Challa, 1981: A numerical study of the role of eddy fluxes of momentum in the devel-opment of Atlantic hurricanes. J. Atmos. Sci., 38, 2393-2398.
    Powell, M., 1990: Boundary layer structure and dynam-ics in outer hurricane rainbands. Part II: Downdraft modification and mixed layer recovery. Mon. Wea. Rev., 118, 918-938.
    Purser, R. J., W.-S. Wu, D. F. Parrish, et al., 2003b: Nu-merical aspects of the application of recursive filters to variational statistical analysis. Part II: Spatially inhomogeneous and anisotropic general covariances. Mon. Wea. Rev., 131, 1536-1548.
    Qin, Z., X. Zou, and F. Weng, 2013, Evaluating added benefits of assimilating GOES imager radiance data in GSI for coastal QPFs. Mon. Wea. Rev., 141, 75-92.
    Riemer, M., M. Montgomery, and M. Nicholls, 2010: A new paradigm for intensity modification of tropical cyclones: Thermodynamic impact of vertical wind shear on the inflow layer. Atmos. Chem. Phys., 10, 3163-3188.
    Riemer, M., and M. Montgomery, 2011: Simple kinematic models for the environmental interaction of tropi-cal cyclones in vertical wind shear. Atmos. Chem. Phys., 11, 9395-9414.
    Simpson, R., and R. Riehl, 1958: Mid-tropospheric venti-lation as a constraint on hurricane development and maintenance. Preprints, Tech. Conf. on Hurricanes, Miami Beach, FL, Amer. Meteor. Soc., D4-1-D4-10.
    Stengel, M., P. Undn, M. Lindskog, et al., 2009: Assim-ilation of SEVIRI infrared radiances with HIRLAM
    Untch, A., and A. Simmons, 1999: Increased strato-spheric resolution in the ECMWF forecasting sys-tem. Proceedings of SODA Workshop on Chemical Data Assimilation. ECMWF Newsletter, 82, 2-8.
    Velden, C. S., and L. M. Leslie, 1991: The basic relationship between tropical cyclone intensity and the depth of the environmental steering layer in the Australian region. Wea. Forecasting, 6, 244-253.
    Wang Bin, R. L. Elsberry, Wang Yuqing, et al., 1998:Dynamics in tropical cyclone motion: A review.Chinese J. Atmos. Sci., 22, 416-434.
    Weng, F., B. Yan, and N. Grody, 2001: A microwave land emissivity model. J. Geophys. Res., 106, 20115-20123.
    Weng, F., and Q. Liu, 2003: Satellite data assimilation in numerical weather prediction models. Part I: For-ward radiative transfer and Jacobian modeling in cloudy atmospheres. J. Atmos. Sci., 60, 2633-2646.
    Weng, F., 2007: Advances in radiative transfer modeling in support of satellite data assimilation. J. Atmos. Sci., 64, 3799-3807.
    Weng, F., T. Zhu, and B. Yan, 2007: Satellite data assimilation in numerical weather prediction models. Part II: Uses of rain-affected radiances from mi-crowave observations for hurricane vortex analysis. J. Atmos. Sci., 64, 3910-3925.
    Weng, F., X. Zou, X. Wang, et al., 2012: Introduction to Suomi national polar-orbiting partnership advanced technology microwave sounder for numerical weather prediction and tropical cyclone ap-plications. J. Geophys. Res., 117, D19112, doi: 10.1029/2012JD018144.
    Weng, F., H. Yang, and X. Zou, 2013: On convertibility from antenna to sensor brightness temperature for ATMS. IEEE Trans. Geo. Remote Sen., 10, 771-775.
    Wu, W.-S., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130,2905-2916.
    Wu, X., and W. L. Smith, 1997: Emissivity of rough sea surface for 8-13 m: Modeling and verification. Appl. Opt., 36, 2609-2619.
    Wu, Y., and X. Zou, 2008: Numerical test of a simple approach for using TOMS total ozone data in hurri-cane environment. Quart. J. R. Meteor. Soc., 134,1397-1408.
    Yang, H., and X. Zou, 2013: Optimal ATMS remapping algorithm for climate research. IEEE Trans. Geo. Remote Sensing, 52, 7290-7296.
    Yan, B., F. Weng, and K. Okamoto, 2004: Improved estimation of snow emissivity from 5 to 200 GHz. Proceedings of 8th Specialist Meeting on Microwave Radiometry and Remote Sensing Applications, 24-27 February 2004, Rome, Italy.
    Yeh, K.-S., X. Zhang, S. Gopalakrishnan, et al., 2012: The AOML/ESRL hurricane research system: Per-formance in the 2008 hurricane season. Nat. Haz-ards, 63, 1439-1449, doi: 10.1007/s11069-011-9787-7.
    Zehr, R., 1992: Tropical Cyclogenesis in the Western North Pacific. NOAA Tech. Rep. NESDIS 61, 181 pp.
    Zhang, X., T. S. Quirino, K.-S. Yeh, et al., 2011: HWRFx: Improving hurricane forecast with high-resolution modeling. Comput. Sci. Eng., 13, 13-21.
    Zou, X., F. Weng, B. L. Zhang, et al., 2013: Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of 2012 four landfall hurricanes. J. Geophys. Res., 118, 11558-11576.
    Zou, X., L. Lin, and F. Weng, 2013: Absolute calibration of ATMS upper level temperature sounding channels using GPS RO observations. IEEE Trans. Geosci. Remote Sens., 52, 1397-1406.
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