Editorial Type:
Article
Article Type:
Research Article

Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-Permitting Hurricane Initialization and Prediction: Katrina (2005)

Yonghui Weng Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Yonghui Weng in
Current site
Google Scholar
PubMed Close
and
Fuqing Zhang Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Fuqing Zhang in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Feb 2012
DOI:
https://doi.org/10.1175/2011MWR3602.1
Page(s):
841–859
Restricted access

Abstract

Through a Weather Research and Forecasting model (WRF)-based ensemble Kalman filter (EnKF) data assimilation system, the impact of assimilating airborne radar observations for the convection-permitting analysis and prediction of Hurricane Katrina (2005) is examined in this study. A forecast initialized from EnKF analyses of airborne radar observations had substantially smaller hurricane track forecast errors than NOAA’s operational forecasts and a control forecast initialized from NCEP analysis data for lead times up to 120 h. Verifications against independent in situ and remotely sensed observations show that EnKF analyses successfully depict the inner-core structure of the hurricane vortex in terms of both dynamic (wind) and thermodynamic (temperature and moisture) fields. In addition to the improved analyses and deterministic forecast, an ensemble of forecasts initiated from the EnKF analyses also provided forecast uncertainty estimates for the hurricane track and intensity.

Also documented here are the details of a series of data thinning and quality control procedures that were developed to generate superobservations from large volumes of airborne radial velocity measurements. These procedures have since been implemented operationally on the NOAA hurricane reconnaissance aircraft that allows for more efficient real-time transmission of airborne radar observations to the ground.

Corresponding author address: Prof. Fuqing Zhang, Department of Meteorology, The Pennsylvania State University, University Park, PA 16802. E-mail: fzhang@psu.edu

Abstract

Through a Weather Research and Forecasting model (WRF)-based ensemble Kalman filter (EnKF) data assimilation system, the impact of assimilating airborne radar observations for the convection-permitting analysis and prediction of Hurricane Katrina (2005) is examined in this study. A forecast initialized from EnKF analyses of airborne radar observations had substantially smaller hurricane track forecast errors than NOAA’s operational forecasts and a control forecast initialized from NCEP analysis data for lead times up to 120 h. Verifications against independent in situ and remotely sensed observations show that EnKF analyses successfully depict the inner-core structure of the hurricane vortex in terms of both dynamic (wind) and thermodynamic (temperature and moisture) fields. In addition to the improved analyses and deterministic forecast, an ensemble of forecasts initiated from the EnKF analyses also provided forecast uncertainty estimates for the hurricane track and intensity.

Also documented here are the details of a series of data thinning and quality control procedures that were developed to generate superobservations from large volumes of airborne radial velocity measurements. These procedures have since been implemented operationally on the NOAA hurricane reconnaissance aircraft that allows for more efficient real-time transmission of airborne radar observations to the ground.

Corresponding author address: Prof. Fuqing Zhang, Department of Meteorology, The Pennsylvania State University, University Park, PA 16802. E-mail: fzhang@psu.edu
Save
Cover Monthly Weather Review
Monthly Weather Review

  • Barker, D. M., W. Huang, Y.-R. Guo, A. J. Bourgeois, and Q. N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897–914.

    • Search Google Scholar
    • Export Citation

  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3, 396–409.

  • Bishop, C. H., and D. Hodyss, 2007: Flow-adaptive moderation of spurious ensemble correlations and its use in ensemble-based data assimilation. Quart. J. Roy. Meteor. Soc., 133, 2029–2044.

    • Search Google Scholar
    • Export Citation

  • Daley, R., 1991: Atmospheric Data Assimilation. Cambridge University Press, 457 pp.

  • Davis, C. A., C. J. Sarah, and R. Michael, 2008: Hurricane vortex dynamics during Atlantic extratropical transition. J. Atmos. Sci., 65, 714–736.

    • Search Google Scholar
    • Export Citation

  • Dowell, D. C., F. Zhang, L. J. Wicker, C. Snyder, and N. A. Crook, 2004: Wind and thermodynamic retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments. Mon. Wea. Rev., 132, 1982–2005.

    • Search Google Scholar
    • Export Citation

  • 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.

    • Search Google Scholar
    • Export Citation

  • Fang, J., and F. Zhang, 2010: Initial development and genesis of Hurricane Dolly (2008). J. Atmos. Sci., 67, 655–672.

  • Fang, J., and F. Zhang, 2011: Evolution of multiscale vortices in the development of Hurricane Dolly (2008). J. Atmos. Sci., 68, 103–122.

    • Search Google Scholar
    • Export Citation

  • Fritz, H. M., and Coauthors, 2007: Hurricane Katrina storm surge distribution and field observations on the Mississippi barrier islands. Estuarine Coastal Shelf Sci., 74, 12–20.

    • Search Google Scholar
    • Export Citation

  • Gamache, J. F., 2005: Real-time dissemination of hurricane wind fields determined from airborne Doppler radar data. Final report on JHT project, NOAA, 38 pp. [Available online at http://www.nhc.noaa.gov/jht/2003-2005reports/DOPLRgamache_JHTfinalreport.pdf.]

    • Search Google Scholar
    • Export Citation

  • Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693, doi:10.1029/2002GL015311.

    • Search Google Scholar
    • Export Citation

  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice-microphysical processes for the bulk parameterization of cloud and precipitation. Mon. Wea. Rev., 132, 103–120.

    • Search Google Scholar
    • Export Citation

  • Knabb, R. D., J. R. Rhome, and D. P. Brown, 2006: Tropical cyclone report: Hurricane Katrina: 23–30 August 2005. National Hurricane Center, Miami, FL, 43 pp. [Available online at http://www.nhc.noaa.gov/pdf/TCR-AL122005_Katrina.pdf.]

    • Search Google Scholar
    • Export Citation

  • 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.

    • 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, 2791–2801.

    • Search Google Scholar
    • Export Citation

  • Leith, C. E., 1974: Theoretical skill of Monte Carlo forecasts. Mon. Wea. Rev., 102, 409–418.

  • Marks, F. D., Jr., and R. A. Houze Jr., 1984: Airborne Doppler radar observations in Hurricane Debby. Bull. Amer. Meteor. Soc., 65, 569–582.

    • Search Google Scholar
    • Export Citation

  • Marks, F. D., Jr., and R. A. Houze Jr., 1987: Inner core structure of Hurricane Alicia from Doppler radar observations. J. Atmos. Sci., 44, 1296–1317.

    • Search Google Scholar
    • Export Citation

  • Marks, F. D., Jr., R. A. Houze Jr., and J. F. Gamache, 1992: Dual-aircraft investigation of the inner core of Hurricane Norbert. Part I: Kinematic structure. J. Atmos. Sci., 49, 919–942.

    • Search Google Scholar
    • Export Citation

  • McTaggart-Cowan, R., L. F. Bosart, J. R. Gyakum, and E. H. Atallah, 2007: Hurricane Katrina (2005). Part II: Evolution and hemispheric impacts of a diabatically generated warm pool. Mon. Wea. Rev., 135, 3927–3949.

    • Search Google Scholar
    • Export Citation

  • Meisner, B. N., cited 2011: An overview of NHC prediction models. NHC Tech. Attachment SR/SSD-95-36. [Available online at http://www.srh.noaa.gov/ssd/nwpmodel/html/nhcmodel.htm.]

    • Search Google Scholar
    • Export Citation

  • Murphy, J. M., 1988: The impact of ensemble forecasts on predictability. Quart. J. Roy. Meteor. Soc., 114, 463–493.

  • Nguyen, S. V., R. K. Smith, and M. T. Montgomery, 2008: Tropical-cyclone intensification and predictability in three dimensions. Quart. J. Roy. Meteor. Soc., 134, 563–582.

    • Search Google Scholar
    • Export Citation

  • Noh, Y., W.-G. Cheon, and S.-Y. Hong, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401–427.

    • Search Google Scholar
    • Export Citation

  • Pielke, R. A., Jr., J. Gratz, C. W. Landsea, D. Collins, M. A. Saunders, and R. Musulin, 2008: Normalized hurricane damages in the United States. Nat. Hazards Rev., 9, 29–42.

    • Search Google Scholar
    • Export Citation

  • Poterjoy, J., and F. Zhang, 2011: Dynamics and structures of forecast error covariance in the core of a developing hurricane. J. Atmos. Sci., 68, 1586–1606.

    • Search Google Scholar
    • Export Citation

  • Rogers, R., and Coauthors, 2006: The Intensity Forecasting Experiment: A NOAA multiyear field program for improving tropical cyclone intensity forecasts. Bull. Amer. Meteor. Soc., 87, 1523–1537.

    • Search Google Scholar
    • Export Citation

  • Shen, B. W., R. Atlas, O. Reale, S.-J. Lin, J.-D. Chern, J. Chang, C. Henze, and J.-L. Li, 2006: Hurricane forecasts with a global mesoscale-resolving model: Preliminary results with Hurricane Katrina (2005). Geophys. Res. Lett., 33, L13813, doi:10.1029/2006GL026143.

    • Search Google Scholar
    • Export Citation

  • Sippel, J. A., and F. Zhang, 2008: A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis. J. Atmos. Sci., 65, 3440–3459.

    • Search Google Scholar
    • Export Citation

  • Sippel, J. A., and F. Zhang, 2010: Factors affecting the predictability of Hurricane Humberto (2007). J. Atmos. Sci., 67, 1759–1778.

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 19 pp.

    • Search Google Scholar
    • Export Citation

  • Snyder, C., and F. Zhang, 2003: Tests of an ensemble Kalman filter for convective-scale data assimilation. Mon. Wea. Rev., 131, 1663–1677.

    • Search Google Scholar
    • Export Citation

  • 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.

    • Search Google Scholar
    • Export Citation

  • Ueno, M., 1995: A study on the impact of asymmetric components around tropical cyclone center on the accuracy of bogus data and the track forecast. Meteor. Atmos. Phys., 56, 125–134.

    • Search Google Scholar
    • Export Citation

  • Weng, Y., M. Zhang, and F. Zhang, 2011: Advanced data assimilation for cloud-resolving hurricane initialization and prediction. Comput. Sci. Eng., 13, 40–49.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., and C. Snyder, 2007: Ensemble-based data assimilation. Bull. Amer. Meteor. Soc., 88, 565–568.

  • Zhang, F., and J. A. Sippel, 2009: Effects of moist convection on hurricane predictability. J. Atmos. Sci., 66, 1944–1961.

  • Zhang, F., C. Snyder, and J. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238–1253.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., Z. Meng, and A. Aksoy, 2006: Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: Perfect model experiments. Mon. Wea. Rev., 134, 722–736.

    • Search Google Scholar
    • Export Citation

  • Zhang, F., Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Convection-permitting hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter: Humberto (2007). Mon. Wea. Rev., 137, 2105–2125.

    • 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.

    • 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, 836–860.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 832 393 55
PDF Downloads 347 125 17