ASSESSING THE ACCURACY OF THE CLOUD AND WATER VAPOR FIELDS IN THE HURRICANE WRF (HWRF) MODEL USING SATELLITE INFRARED BRIGHTNESS TEMPERATURES

ASSESSING THE ACCURACY OF THE CLOUD AND WATER VAPOR FIELDS IN THE HURRICANE WRF (HWRF) MODEL... AbstractIn this study, cycled forecast experiments were performed to assess the ability of different cloud microphysics and cumulus parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) model to accurately simulate the evolution of the cloud and moisture fields during the entire life cycle of Hurricane Edouard (2014). The forecast accuracy for each model configuration was evaluated through comparison of observed and simulated Geostationary Operational Environmental Satellite (GOES)-13 infrared brightness temperatures and satellite-derived tropical cyclone intensity estimates computed using the Advanced Dvorak Technique (ADT). Overall, the analysis revealed a large moist bias in the middle and upper troposphere during the entire forecast period that was at least partially due to a moist bias in the initialization datasets but was also affected by the microphysics and cumulus parameterization schemes. Large differences occurred in the azimuthal brightness temperature distributions, with two of the microphysics schemes producing hurricane eyes that were much larger and clearer than observed, especially for later forecast hours. Comparisons to the forecast 10-m wind speeds showed reasonable agreement (correlations between 0.58 and 0.74) between the surface-based intensities and the ADT intensity estimates inferred via cloud patterns in the upper troposphere. It was also found that model configurations that had the smallest differences between the ADT and surface-based intensities had the most accurate track and intensity forecasts. Last, the cloud microphysics schemes had the largest impact on the forecast accuracy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Monthly Weather Review American Meteorological Society

ASSESSING THE ACCURACY OF THE CLOUD AND WATER VAPOR FIELDS IN THE HURRICANE WRF (HWRF) MODEL USING SATELLITE INFRARED BRIGHTNESS TEMPERATURES

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0493
eISSN
1520-0493
D.O.I.
10.1175/MWR-D-16-0354.1
Publisher site
See Article on Publisher Site

Abstract

AbstractIn this study, cycled forecast experiments were performed to assess the ability of different cloud microphysics and cumulus parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) model to accurately simulate the evolution of the cloud and moisture fields during the entire life cycle of Hurricane Edouard (2014). The forecast accuracy for each model configuration was evaluated through comparison of observed and simulated Geostationary Operational Environmental Satellite (GOES)-13 infrared brightness temperatures and satellite-derived tropical cyclone intensity estimates computed using the Advanced Dvorak Technique (ADT). Overall, the analysis revealed a large moist bias in the middle and upper troposphere during the entire forecast period that was at least partially due to a moist bias in the initialization datasets but was also affected by the microphysics and cumulus parameterization schemes. Large differences occurred in the azimuthal brightness temperature distributions, with two of the microphysics schemes producing hurricane eyes that were much larger and clearer than observed, especially for later forecast hours. Comparisons to the forecast 10-m wind speeds showed reasonable agreement (correlations between 0.58 and 0.74) between the surface-based intensities and the ADT intensity estimates inferred via cloud patterns in the upper troposphere. It was also found that model configurations that had the smallest differences between the ADT and surface-based intensities had the most accurate track and intensity forecasts. Last, the cloud microphysics schemes had the largest impact on the forecast accuracy.

Journal

Monthly Weather ReviewAmerican Meteorological Society

Published: Mar 22, 2017

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