GPS掩星與其它資料同化對台灣地區颱風和梅雨模擬之影響

Impact of GPS RO and Other Data Assimilation on Typhoon and Mei-yu Predictions in the Vicinity of Taiwan

黃清勇(Ching-Yuang Huang) ； 迮嘉欣(Chia-Hsin Tso)

《大氣科學》 39卷1期 (2011/03) Pp. 25-52

摘要

本文使用WRF模式和WRFDA同化方法，選取2008年兩個梅雨事件與三個颱風個案進行模擬。模擬中分別同化FORMOSAT-3 GPS RO折射率資料、追風計畫的投落送資料(dropsondes)、SSM/I、QuikSCAT衛星觀測資料和CWB提供的傳統觀測資料(GTS)，並探討五種不同的觀測資料對模式初始場與數值天氣預報的影響。
觀測資料對模式初始場的增量結果顯示，同化SSM/I或GTS的濕度增量比同化其他觀測資料大，溫度增量方面則是同化GPS RO或GTS較多，同化dropsondes或QuikSCAT在風速差異值最為顯著。由梅雨與颱風個案模擬結果顯示，同化GTS或SSM/I資料對模擬結果改善最多，同化QuikSCAT資料對颱風預報也有正面的影響，同化GPS RO對颱風路徑改善並不明顯。降雨模擬方面，累積降雨預報中同化GPS RO或SSM/I結果最佳，沒有同化任何觀測資料的控制組降雨預報較差。
GPS RO和其他觀測資料結合模擬結果方面，同時同化GPS RO和dropsondes時，可發現同化dropsondes資料對於模式模擬的影響較大。GPS cycling實驗中，同時同化多種資料對模擬有顯著的改善。針對GPS RO資料點位置的敏感度實驗，結果顯示颱風環流附近的單一筆GPS RO資料，對於模式模擬結果有很大的影響。

關鍵字

颱風 ； WRF ； GPS RO

並列摘要

This study uses the Weather Research and Forecasting (WRF) model and its data assimilation system (WRFDA) to assimilate various observations (including FORMOSAT-3 GPS RO data, DOTSTAR dropsonde soundings, SSM/I, QuikSCAT, and GTS conventional soundings) for understanding the impact of these data on numerical weather prediction. Five cases in 2008, including two Mei-yu cases and three typhoon cases, are selected for this impact study.
The model initial increments show that assimilation with SSM/I data (both surface wind speed and precipitable water) or GTS data produces more humidity increments than those from other observations. Temperature increments, however, are larger for assimilation with GPS RO data or GTS data than other observations. Assimilation with dropsonde soundings or QuikSCAT data (near-surface oceanic wind velocity) obtains the most significant wind increments. Based on the results of Mei-yu and typhoon simulations, assimilation with GTS data or SSM/I data appears to give the best performance, while QuikSCAT data also have some improvement on typhoon forecasts. Assimilation with GPS RO data does not have a clear impact on typhoon track forecast. However, assimilation with GPS RO data or SSM/I data appears to give the improved performance for rainfall prediction. The simulation without assimilating observations in general gives the worst rainfall prediction.
Dropsonde soundings show more dominant impacts when the GPS RO data are also assimilated. In cycling experiments with the GPS RO data, significant improvement in prediction is also found in combination with other observations. From the sensitivity tests, single GPS RO sounding in the vicinity of typhoon circulation may have a considerable impact on typhoon prediction.

並列關鍵字

Typhoon ； WRF ； GPS RO