• 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, 2046–2061.

  • Courtier, P., J.-N. Thépaut, and A. Hollingsworth, 1994: A strategy for operational implementation of 4D-Var, using an incremental approach. Quart. J. Roy. Meteor. Soc.,120, 1367–1387.

  • ——, and Coauthors, 1998: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). I: Formulation. Quart. J. Roy. Meteor. Soc.,124, 1783–1808.

  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev.,121, 1493–1513.

  • Dvorak, V., and H. M. Mogil, 1994: Tropical cyclone motion forecasting using satellite water vapor imagery. NOAA Tech. Rep. NESDIS 83, 42 pp. [Available from NOAA/NESDIS, 5200 Auth Rd., Washington, DC 20233.].

  • Fujita, T., 1952: Pressure distribution within a typhoon. Geophys. Mag.,23, 437–451.

  • Grell, G. A., J. Dudhia, and D. R. Stauffer, 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN-398 + STR, National Center for Atmospheric Research, Boulder, CO, 138 pp.

  • Krishnamurti, T. N., D. Oosterhof, and N. Dignon, 1989: Hurricane prediction with a high resolution global model. Mon. Wea. Rev.,117, 631–669.

  • ——, J. Xue, H. S. Bedi, K. Ingles, and D. Oosterhof, 1991: Physical initialization for numerical weather prediction over tropics. Tellus,43AB, 53–81.

  • ——, S. K. Roy Bhowmik, D. Oosterhof, and G. Rohaly, 1995: Mesoscale signatures within the Tropics generated by physical initialization. Mon. Wea. Rev.,123, 2771–2790.

  • Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1990: Prediction experiments of Hurricane Gloria (1985) using a multiply nested movable mesh model. Mon. Wea. Rev.,118, 2185–2198.

  • ——, ——, and R. J. Ross, 1993: An initialization scheme of hurricane models by vortex specification. Mon. Wea. Rev.,121, 2030–2045.

  • ——, R. E. Tuleya, and M. A. Bender, 1998: The GFDL hurricane prediction system and its performance in the 1995 hurricane season. Mon. Wea. Rev.,126, 1306–1322.

  • Liu, Y., D.-L. Zhang, and M. K. Yau, 1997: A multiscale numerical study of Hurricane Andrew (1992). Part I: Explicit simulation and verification. Mon. Wea. Rev.,125, 3073–3093.

  • Lord, S. J., 1991: A bogusing system for vortex circulations in the National Meteorological Center global forecast model. Preprints, 19th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 328–330.

  • Navon, I. M., X. Zou, J. Derber, and J. Sela, 1992: Variational data assimilation with an adiabatic version of the NMC spectral model. Mon. Wea. Rev.,120, 1433–1446.

  • Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev.,120, 1747–1763.

  • Trinh, V. T., and T. N. Krishnamurti, 1992: Vortex initialization for typhoon track prediction. Meteor. Atmos. Phys.,47, 117–126.

  • Velden, S. V., C. M. Hayden, S. J. Nieman, W. P. Menzel, S. Wanzong, and J. S. Goerss, 1997: Upper-tropospheric winds derived from geostationary satellite water vapor observations. Bull. Amer. Meteor. Soc.,78, 173–195.

  • Willoughby, H. E., 1995: Mature structure and evolution. Global perspectives on tropical cyclones. World Meteorological Organization Tech. Document WMO/TD-No. 693, 21–62.

  • Zou, X., I. M. Navon, and F. X. Le Dimet, 1992: Incomplete observations and control of gravity waves in variational data assimilation. Tellus,44A, 273–296.

  • ——, ——, and J. Sela, 1993: Control of gravity oscillations in variational data assimilation. Mon. Wea. Rev.,121, 272–289.

  • ——, Y.-H. Kuo, and Y.-R. Guo, 1995: Assimilation of atmospheric radio refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev.,123, 2229–2249.

  • ——, F. Vandenberghe, M. Pondeca, and Y.-H. Kuo, 1997: Introduction to adjoint techniques and the MM5 adjoint modeling system. NCAR Tech. Note NCAR/TN-435 - STR, National Center for Atmospheric Research, Boulder, CO, 110 pp.

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Studies on the Initialization and Simulation of a Mature Hurricane Using a Variational Bogus Data Assimilation Scheme

Xiaolei ZouDepartment of Meteorology, The Florida State University, Tallahassee, Florida

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Qingnong XiaoDepartment of Meteorology, The Florida State University, Tallahassee, Florida

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Abstract

A bogus data assimilation (BDA) scheme is presented and used to generate the initial structure of a tropical cyclone for hurricane prediction. It was tested on Hurricane Felix (1995) in the Atlantic Ocean during its mature stage. The Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model version 5 was used for both the data assimilation and prediction. It was found that a dynamically and physically consistent initial condition describing the dynamic and thermodynamic structure of a hurricane vortex can be generated by fitting the forecast model to a specified bogus surface low based on a few observed and estimated parameters. Through forecast model constraint, BDA is able to recover many of the structural features of a mature hurricane including a warm-core vortex with winds swirling in and out of the vortex center in the lower and upper troposphere, respectively; the eyewall; the saturated ascent around the eye and descent or weak ascent in the eye; and the spiral cloud bands and rainbands. Satellite and radar data, if available, can be incorporated into the BDA procedure. It was shown that satellite-derived water vapor winds have an added value for BDA—they can generate a more realistic initial vortex.

As a result of BDA using both a bogus surface low and satellite water vapor wind data, dramatic improvements occurred in the hurricane prediction of Felix. First of all, the initial fields of model variables describing the BDA initial vortex are well adapted to the forecast model. Second, the intensity forecast was greatly improved. The mean error of the central sea level pressure during the entire 72-h forecast period reduced from 25.9 hPa without BDA to less than 2.1 hPa with BDA. Third, the model captured the structures of the storm reasonably well. In particular, the model reproduced the ring of maximum winds, the eye, the eyewall, and the spiral cloud bands. Finally, improvement in the track prediction was also observed. The 24-, 48-, and 72-h forecast track errors with BDA were 76, 76, and 84 km, respectively, compared to the track errors of 93, 170, and 193 km without BDA.

Corresponding author address: Dr. Xiaolei Zou, Department of Meteorology, The Florida State University, Tallahassee, FL 32306-4520.

Email: zou@met.fsu.edu

Abstract

A bogus data assimilation (BDA) scheme is presented and used to generate the initial structure of a tropical cyclone for hurricane prediction. It was tested on Hurricane Felix (1995) in the Atlantic Ocean during its mature stage. The Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model version 5 was used for both the data assimilation and prediction. It was found that a dynamically and physically consistent initial condition describing the dynamic and thermodynamic structure of a hurricane vortex can be generated by fitting the forecast model to a specified bogus surface low based on a few observed and estimated parameters. Through forecast model constraint, BDA is able to recover many of the structural features of a mature hurricane including a warm-core vortex with winds swirling in and out of the vortex center in the lower and upper troposphere, respectively; the eyewall; the saturated ascent around the eye and descent or weak ascent in the eye; and the spiral cloud bands and rainbands. Satellite and radar data, if available, can be incorporated into the BDA procedure. It was shown that satellite-derived water vapor winds have an added value for BDA—they can generate a more realistic initial vortex.

As a result of BDA using both a bogus surface low and satellite water vapor wind data, dramatic improvements occurred in the hurricane prediction of Felix. First of all, the initial fields of model variables describing the BDA initial vortex are well adapted to the forecast model. Second, the intensity forecast was greatly improved. The mean error of the central sea level pressure during the entire 72-h forecast period reduced from 25.9 hPa without BDA to less than 2.1 hPa with BDA. Third, the model captured the structures of the storm reasonably well. In particular, the model reproduced the ring of maximum winds, the eye, the eyewall, and the spiral cloud bands. Finally, improvement in the track prediction was also observed. The 24-, 48-, and 72-h forecast track errors with BDA were 76, 76, and 84 km, respectively, compared to the track errors of 93, 170, and 193 km without BDA.

Corresponding author address: Dr. Xiaolei Zou, Department of Meteorology, The Florida State University, Tallahassee, FL 32306-4520.

Email: zou@met.fsu.edu

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