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Impact of Assimilating Underwater Glider Data on Hurricane Gonzalo (2014) Forecasts
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2017
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Source: Weather and Forecasting, 32(3), 1143-1159.
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Journal Title:Weather and Forecasting
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Description:The initialization of ocean conditions is essential to coupled tropical cyclone (TC) forecasts. This study investigates the impact of ocean observation assimilation, particularly underwater glider data, on high-resolution coupled TC forecasts. Using the coupled Hurricane Weather Research and Forecasting (HWRF) Model-Hybrid Coordinate Ocean Model (HYCOM) system, numerical experiments are performed by assimilating underwater glider observations alone and with other standard ocean observations for the forecast of Hurricane Gonzalo (2014). The glider observations are able to provide valuable information on subsurface ocean thermal and saline structure, even with their limited spatial coverage along the storm track and the relatively small amount of data assimilated. Through the assimilation of underwater glider observations, the prestorm thermal and saline structures of initial upper-ocean conditions are significantly improved near the location of glider observations, though the impact is localized because of the limited coverage of glider data. The ocean initial conditions are best represented when both the standard ocean observations and the underwater glider data are assimilated together. The barrier layer and the associated sharp density gradient in the upper ocean are successfully represented in the ocean initial conditions only with the use of underwater glider observations. The upper-ocean temperature and salinity forecasts in the first 48 h are improved by assimilating both underwater glider and standard ocean observations. The assimilation of glider observations alone does not make a large impact on the intensity forecast due to their limited coverage along the storm track. The 126-h intensity forecast of Hurricane Gonzalo is improved moderately through assimilating both underwater glider data and standard ocean observations.
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Source:Weather and Forecasting, 32(3), 1143-1159.
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