• Amerault, C., and J. Doyle, 2008: Assimilation of small scale observations with a nested adjoint model. Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV: Readiness for GEOSS II, M. D. Goldberg et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 7085), 70850R, doi:10.1117/12.795348.

  • Amerault, C., X. Zou, and J. Doyle, 2009: Assimilation of rain-affected radiances with an adjoint model. J. Appl. Remote Sens., 3, 033531, doi:10.1117/1.3153332.

    • Search Google Scholar
    • Export Citation
  • Andersson, E., J. Pailleux, J.-N. Thépaut, J. R. Eyre, A. P. McNally, G. A. Kelly, and P. Courtier, 1994: Use of cloud-cleared radiances in three/four-dimensional variational data assimilation. Quart. J. Roy. Meteor. Soc., 120, 627653, doi:10.1002/qj.49712051707.

    • Search Google Scholar
    • Export Citation
  • Bao, S., R. Yablonsky, D. Stark, and L. Bernardet, 2012: Community HWRF users guide V3.4a. Developmental Testbed Center Tech. Memo. OAR GSD-42, 124 pp.

  • Bender, M. A., R. J. Ross, R. E. Tuleya, and Y. Kurihara, 1993: Improvements in tropical cyclone track and intensity forecasts using the GFDL initialization system. Mon. Wea. Rev., 121, 20462061, doi:10.1175/1520-0493(1993)121<2046:IITCTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • 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, 22872299, doi:10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Eyre, J. R., G. Kelly, A. P. McNally, E. Andersson, and A. Persson, 1993: Assimilation of TOVS radiance information through one-dimensional variational analysis. Quart. J. Roy. Meteor. Soc., 119, 14271463, doi:10.1002/qj.49711951411.

    • Search Google Scholar
    • Export Citation
  • Goerss, J. S., C. S. Velden, and J. D. Hawkins, 1998: The impact of multispectral GOES-8 wind information on Atlantic tropical cyclone forecasts in 1995. Part II: NOGAPS forecasts. Mon. Wea. Rev., 126, 12191227, doi:10.1175/1520-0493(1998)126<1219:TIOMGW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gopalakrishnan, S., S. Goldenberg, T. Quirino, F. Marks, X. Zhang, K.-S. Yeh, R. Atlas, and V. Tallapragada, 2012: Towards improving high-resolution numerical hurricane forecasting: Influence of model horizontal grid resolution, initialization, and physics. Wea. Forecasting, 27, 647666, doi:10.1175/WAF-D-11-00055.1.

    • Search Google Scholar
    • Export Citation
  • Gopalakrishnan, S., and Coauthors, 2012: Hurricane Weather Research and Forecasting (HWRF) Model: 2012 science documentation. HWRF v3.4a, Developmental Testbed Center Tech. Rep., 96 pp.

  • Han, Y., F. Weng, Q. Liu, and P. van Delst, 2007: A fast radiative transfer model for SSMIS upper atmosphere sounding channels. J. Geophys. Res., 112, D11121, doi:10.1029/2006JD008208.

    • Search Google Scholar
    • Export Citation
  • Heidinger, A., 2011: NOAA NESDIS Center for Satellite Applications and Research algorithm theoretical basis document: ABI cloud mask. Version 2.0, 93 pp.

  • Janjić, Z. I., 2003: A nonhydrostatic model based on a new approach. Meteor. Atmos. Phys., 82, 271285, doi:10.1007/s00703-001-0587-6.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., J. P. Gerrity, and S. Nickovic, 2001: An alternative approach to nonhydrostatic modeling. Mon. Wea. Rev., 129, 11641178, doi:10.1175/1520-0493(2001)129<1164:AAATNM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Köpken, C., G. Kelly, and J.-N. Thépaut, 2004: Assimilation of Meteosat radiance data within the 4D-Var system at ECMWF: Assimilation experiments and forecast impact. Quart. J. Roy. Meteor. Soc., 130, 22772292, doi:10.1256/qj.02.230.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., M. A. Bender, and R. J. Ross, 1993: An initialization scheme of hurricane models byvortex specification. Mon. Wea. Rev., 121, 20302045, doi:10.1175/1520-0493(1993)121<2030:AISOHM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1995: Improvements in the GFDL Hurricane Prediction System. Mon. Wea. Rev., 123, 27912801, doi:10.1175/1520-0493(1995)123<2791:IITGHP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • McNally, A. P., and Coauthors, 2006: The assimilation of AIRS radiance data at ECMWF. Quart. J. Roy. Meteor. Soc., 132, 935957, doi:10.1256/qj.04.171.

    • Search Google Scholar
    • Export Citation
  • Migliorini, S., 2012: On the equivalence between radiance and retrieval assimilation. Mon. Wea. Rev., 140, 258265, doi:10.1175/MWR-D-10-05047.1.

    • Search Google Scholar
    • Export Citation
  • Nieman, S. J., J. Schmetz, and W. P. Menzel, 1993: A comparison of several techniques to assign heights to cloud tracers. J. Appl. Meteor., 32, 15591568, doi:10.1175/1520-0450(1993)032<1559:ACOSTT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Pu, Z., X. Li, and J. Sun, 2009: Impact of airborne Doppler radar data assimilation on the numerical simulation of intensity changes of Hurricane Dennis near a landfall. J. Atmos. Sci., 66, 33513365, doi:10.1175/2009JAS3121.1.

    • Search Google Scholar
    • Export Citation
  • Purser, R. J., W.-S. Wu, D. F. Parrish, and N. M. Roberts, 2003a: Numerical aspects of the application of recursive filters to variational statistical analysis. Part I: Spatially homogeneous and isotropic Gaussian covariances. Mon. Wea. Rev., 131, 15241535, doi:10.1175/1520-0493(2003)131<1524:NAOTAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Purser, R. J., W.-S. Wu, D. F. Parrish, and N. M. Roberts, 2003b: Numerical aspects of the application of recursive filters to variational statistical analysis. Part II: Spatially inhomogeneous and anisotropic general covariances. Mon. Wea. Rev., 131, 15361548, doi:10.1175/2543.1.

    • Search Google Scholar
    • Export Citation
  • 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, 7592, doi:10.1175/MWR-D-12-00079.1.

    • Search Google Scholar
    • Export Citation
  • Rao, P. A., C. S. Velden, and S. A. Braun, 2002: The vertical error characteristics of GOES-derived winds: Description and experiments with numerical weather prediction. J. Appl. Meteor., 41, 253271, doi:10.1175/1520-0450(2002)041<0253:TVECOG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., C. S. Velden, and R. E. Tuleya, 2001: The impact of satellite winds on experimental GFDL hurricane model forecasts. Mon. Wea. Rev., 129, 835852, doi:10.1175/1520-0493(2001)129<0835:TIOSWO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Stengel, M., P. Undén, M. Lindskog, P. Dahlgren, N. Gustafsson, and R. Bennartz, 2009: Assimilation of SEVIRI infrared radiances with HIRLAM 4D-Var. Quart. J. Roy. Meteor. Soc., 135, 21002109, doi:10.1002/qj.501.

    • Search Google Scholar
    • Export Citation
  • Su, X., J. Derber, J. Jung, Y. Tahara, D. Keyser, and R. Treadon, 2003: The usage of GOES imager clear-sky radiance in the NCEP Global Data Assimilation System. Preprints, 12th Conf. on Satellite Meteorological and Oceanography, Long Beach, CA, Amer. Meteor. Soc., P3.20. [Available online at https://ams.confex.com/ams/annual2003/techprogram/paper_56361.htm.]

  • Szyndel, M. D. E., J.-N. Thépaut, and G. Kelly, 2005: Evaluation of potential benefit of SEVIRI water vapour radiance data from Meteosat-8 into global numerical weather prediction analyses. Atmos. Sci. Lett., 6, 105111, doi:10.1002/asl.98.

    • Search Google Scholar
    • Export Citation
  • Tomassini, M., G. Kelly, and R. Saunders, 1999: Use and impact of satellite atmospheric motion winds on ECMWF analyses and forecasts. Mon. Wea. Rev., 127, 971986, doi:10.1175/1520-0493(1999)127<0971:UAIOSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Velden, C. S., 1996: Winds derived from geostationary satellite moisture channel observations: Applications and impact on numerical weather prediction. Meteor. Atmos. Phys., 60, 3746, doi:10.1007/BF01029784.

    • Search Google Scholar
    • Export Citation
  • Velden, C. S., C. M. Hayden, S. J. Nieman, W. P. Menzel, S. Wazong, and J. S. Goerss, 1997: Upper-tropospheric winds derived from geostationary satellite water vapor observations. Bull. Amer. Meteor. Soc., 78, 173195, doi:10.1175/1520-0477(1997)078<0173:UTWDFG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Velden, C. S., T. L. Olander, and S. Wazong, 1998: The impact of multispectral GOES-8 wind information on Atlantic tropical cyclone track forecasts in 1995. Part I: Dataset methodology, description and case analysis. Mon. Wea. Rev., 126, 12021218, doi:10.1175/1520-0493(1998)126<1202:TIOMGW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weng, F., 2007: Advances in radiative transfer modeling in support of satellite data assimilation. J. Atmos. Sci., 64, 37993807, doi:10.1175/2007JAS2112.1.

    • Search Google Scholar
    • Export Citation
  • Wu, W.-S., R. J. Purser, and D. F. Parrish, 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130, 29052916, doi:10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., and Y. Weng, 2015: Predicting hurricane intensity and associated hazards: A five-year real-time forecast experiment with the assimilation of airborne Doppler radar observations. Bull. Amer. Meteor. Soc., 96, 25–33, doi:10.1175/ BAMS-D-13-00231.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., Y. Weng, J. F. Gamache, and 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.

  • Zhu, T., D.-L. Zhang, and F. Weng, 2002: Impact of the Advanced Microwave Sounding Unit measurements on hurricane prediction. Mon. Wea. Rev., 130, 24162432, doi:10.1175/1520-0493(2002)130<2416:IOTAMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zou, X., and Q. Xiao, 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci., 57, 836860, doi:10.1175/1520-0469(2000)057<0836:SOTIAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zou, X., Q. Xiao, A. E. Lipton, and G. D. Modica, 2001: A numerical study of the effect of GOES sounder cloud-cleared brightness temperatures on the prediction of hurricane Felix. J. Appl. Meteor., 40, 3455, doi:10.1175/1520-0450(2001)040<0034:ANSOTE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zou, X., Z. Qin, and F. Weng, 2011: Improved coastal precipitation forecasts with direct assimilation of GOES-11/12 imager radiances. Mon. Wea. Rev., 139, 37113729, doi:10.1175/MWR-D-10-05040.1.

    • Search Google Scholar
    • Export Citation
  • Zou, X., F. Weng, B. Zhang, L. Lin, Z. Qin, and V. Tallapragada, 2013: Impacts of assimilation of ATMS data in HWRF on track and intensity forecasts of 2012 four landfall hurricanes. J. Geophys. Res. Atmos.,118, 11 558–11 576, doi:10.1002/2013JD020405.

    • Search Google Scholar
    • Export Citation
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Improved Tropical Storm Forecasts with GOES-13/15 Imager Radiance Assimilation and Asymmetric Vortex Initialization in HWRF

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  • 1 Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
  • | 2 Nanjing University of Information Science and Technology, Nanjing, China, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
  • | 3 Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
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Abstract

The Geostationary Operational Environmental Satellite (GOES) imagers provide high temporal- and spatial-resolution data for many applications, such as monitoring severe weather events. In this study, radiance observations of four infrared channels from GOES-13 and GOES-15 imagers are directly assimilated using the National Centers for Environmental Prediction (NCEP) gridpoint statistical interpolation (GSI) analysis system to produce the initial conditions for the Hurricane Weather Research and Forecasting Model (HWRF). Impacts of GOES imager data assimilation on track and intensity forecasts are demonstrated for a landfalling tropical storm that moved across the Gulf of Mexico—Debby (2012). With a higher model top and a warm start, an asymmetric component is also added to the original HWRF symmetric vortex initialization. Two pairs of data assimilation and forecasting experiments are carried out for assessing the impacts of the GOES imager data assimilation on tropical storm forecasts. The first pair employs a symmetric vortex initialization and the second pair includes an asymmetric vortex initialization. Numerical forecast results from these experiments are compared against each other. It is shown that a direct assimilation of GOES-13 and GOES-15 imager radiance observations, which are available at all analysis times, in HWRF results in a consistently positive impact on the track and intensity forecasts of Tropical Storm Debby in the Gulf of Mexico. The largest positive impact on the track and intensity forecasts comes from a combined effect of GOES imager radiance assimilation and an asymmetric vortex initialization.

Corresponding author address: Dr. Xiaolei Zou, Earth System Science Interdisciplinary Center, University of Maryland, College Park, 5825 University of Maryland Research Court, Office 4078, College Park, MD 20740-3823. E-mail: xzou1@umd.edu

Abstract

The Geostationary Operational Environmental Satellite (GOES) imagers provide high temporal- and spatial-resolution data for many applications, such as monitoring severe weather events. In this study, radiance observations of four infrared channels from GOES-13 and GOES-15 imagers are directly assimilated using the National Centers for Environmental Prediction (NCEP) gridpoint statistical interpolation (GSI) analysis system to produce the initial conditions for the Hurricane Weather Research and Forecasting Model (HWRF). Impacts of GOES imager data assimilation on track and intensity forecasts are demonstrated for a landfalling tropical storm that moved across the Gulf of Mexico—Debby (2012). With a higher model top and a warm start, an asymmetric component is also added to the original HWRF symmetric vortex initialization. Two pairs of data assimilation and forecasting experiments are carried out for assessing the impacts of the GOES imager data assimilation on tropical storm forecasts. The first pair employs a symmetric vortex initialization and the second pair includes an asymmetric vortex initialization. Numerical forecast results from these experiments are compared against each other. It is shown that a direct assimilation of GOES-13 and GOES-15 imager radiance observations, which are available at all analysis times, in HWRF results in a consistently positive impact on the track and intensity forecasts of Tropical Storm Debby in the Gulf of Mexico. The largest positive impact on the track and intensity forecasts comes from a combined effect of GOES imager radiance assimilation and an asymmetric vortex initialization.

Corresponding author address: Dr. Xiaolei Zou, Earth System Science Interdisciplinary Center, University of Maryland, College Park, 5825 University of Maryland Research Court, Office 4078, College Park, MD 20740-3823. E-mail: xzou1@umd.edu
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