Abstract
More accurate prediction of the strong winds and heavy rain associated with tropical cyclones using numerical weather prediction (NWP) models would be helpful in the provision of weather services for the public. In this paper, the impact of assimilating radar data in the simulation of Typhoon Neoguri and Severe Tropical Storm Kammuri in 2008 is studied using Weather Research and Forecasting (WRF) version 2.2 and WRF VAR version 2.1. Only the data from the radar at Tate's Cairn in Hong Kong are considered. Four experiments are conducted, namely, (a) simulation without radar data, (b) simulation with radar data assimilated at the initial time, (c) cycling simulation with the assimilation of radar data (Doppler velocity and reflectivity) directly assimilated, and (d) cycling simulation with the assimilation of 2D wind field retrieved from the Doppler velocity data from the radar. By comparing with actual observations of the surface wind distribution in Hong Kong and the actual radar reflectivity data, it turns out that both (c) and (d) outperform (a) and (b), and (c) and (d) show comparable skills. As a result, cycling simulation with the assimilation of weather radar data (even for a single radar) could improve the prediction of winds and rain bands associated with tropical cyclones.
Highlights
Tropical cyclones bring about hazardous weather to coastal areas of southern China, including strong winds and heavy rain associated with the outer rain bands
Numerical weather prediction (NWP) models, from synoptic scale to mesoscale scale, are widely used in the weather services in forecasting heavy rain and strong wind areas brought by tropical cyclones
Its simulation domain is shown in Fig. (1a). It is nested with the operational regional spectral model (ORSM) of the Hong Kong Observatory (HKO) with a spatial resolution of 20 km
Summary
Tropical cyclones bring about hazardous weather to coastal areas of southern China, including strong winds and heavy rain associated with the outer rain bands. Numerical weather prediction (NWP) models, from synoptic scale to mesoscale scale, are widely used in the weather services in forecasting heavy rain and strong wind areas brought by tropical cyclones. The assimilation of remote-sensing data covering the tropical cyclones, such as radar and satellite observations, could help initializing the NWP models. Similar study should be carried out for tropical cyclones over other ocean basins, such as the South China Sea. In this paper, the impact of assimilating radar data on the model forecasting of strong wind and heavy rain areas of tropical cyclones is studied. The study aims at finding out which assimilation method has the strongest positive impact on the simulation results, in terms of the forecasting of strong winds and heavy rain areas of the cyclones.
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