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Improving the Analysis and Forecast of Hurricane Dorian (2019) with Simultaneous Assimilation of GOES-16 All-Sky Infrared Brightness Temperatures and Tail Doppler Radar Radial Velocities

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DataCite Commons2022-02-18 更新2024-07-13 收录
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Recent studies have shown that the assimilation of all-sky infrared (IR) observations can be beneficial for tropical cyclone analyses and predictions. The assimilation of tail Doppler radar (TDR) radial velocity observations has also been shown to improve tropical cyclone analyses and predictions; however, there is a paucity of literature on the impacts of simultaneously assimilating them with all-sky IR brightness temperatures (BTs). This study examines the impacts of assimilating combinations of GOES-16 all-sky IR brightness temperatures, NOAA P-3 TDR radial velocities, and conventional observations from the Global Telecommunications System (GTS) on the analyses and forecasts of Hurricane Dorian (2019). It is shown that including IR and/or TDR observations on top of conventional GTS observations significantly reduces both track and intensity forecast errors. Track errors are reduced the most (25% at lead times greater than 48 h) when TDR and GTS observations are assimilated. In terms of intensity, errors are always lower at lead times greater than 48 h when IR BTs are assimilated. Simultaneously assimilating TDR and IR observations has the potential to further improve the intensity forecast by as much as 37% at a lead time of 48–72 h. The improved intensity forecasts produced by the experiments assimilating all three observation sources are shown to be a result of the competing effects of IR assimilation producing an overly broad area of strong cyclonic circulation and TDR assimilation constraining that circulation to a more realistic size and intensity. Interestingly, the order in which observations are assimilated has nonnegligible impacts on the analyses and forecasts of Dorian.
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Penn State Data Commons
创建时间:
2022-02-18
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