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| 題 名 | 同化雙偏極化雷達差異反射率之新方法:2021年宜蘭降雨觀測實驗IOP2個案分析=New Approach to Assimilate Radar Differential Reflectivity: 2021YESR #IOP2 Wintertime Rainfall Case Study |
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| 作 者 | 張沁全; 鍾高陞; 莊秉學; 張偉裕; 蔡直謙; 郭鴻基; | 書刊名 | 大氣科學 |
| 卷 期 | 52:2 2024.12[民113.12] |
| 頁 次 | 頁99-135 |
| 分類號 | 328.63 |
| 關鍵詞 | 雙偏極化雷達資料同化; 宜蘭降雨觀測實驗; 質量權重平均粒徑; Dual-polarimetric radar data assimilation; Yilan experiment for severe rainfall; Mass-weighted mean diameter; |
| 語 文 | 中文(Chinese) |
| DOI | 10.53106/025400022024125202002 |
| 中文摘要 | 本研究利用LETKF分析場與預報場,驗證雙偏極化雷達差異反射率資料同化在2021年冬季降水個案的表現,進一步評估質量權重平均粒徑更新法同化差異反射率之效益。三組實驗設定如下:第一組只進行傳統雷達觀測資料(ZH, Vr)同化,第二組(VrZZ)額外同化差異反射率(Z_(DR))並使用傳統方法直接更新水象粒子。最後一組實驗同樣同化Z_(DR),但在進行模式更新時,使用質量權重平均粒徑更新法。分析場結果顯示,Z_(DR)資料同化能改善模式分析場水氣混合比、調整雨滴平均粒徑大小,並減少分析場Z_(DR)與觀測表現之差異。使用質量權重平均粒徑更新法進行模式更新時,能夠有效且快速調整模式微物理結構,並獲得最接近觀測的ZH與Z_(DR)結構。在短期定量降水預報表現上,VrZ能改善第一小時的預報表現,但明顯低估第二小時降雨表現,影響2~6小時累積降雨表現。相較之下,同化Z_(DR)進入模式,能改善預報前3小時定量降水表現,並提高不同降雨門檻下的超越機率。此外使用新變數轉換法更新模式,能夠在局部地區增加降雨超越機率,使其更加接近於觀測表現。統整研究結果,同化Z_(DR)觀測資訊在冬季個案研究中,可有效調整分析場微物理與熱力結構,並使降水預報能力有所提升。其效益在使用質量權重平均粒徑更新法時,能有更好的表現。 |
| 英文摘要 | The new approach of assimilating dual-pol radar differential reflectivity (Z_(DR)) is investigated in this study. By using LETKF data assimilation system and selecting wintertime rainfall event, two sets of experiments, which VrZ assimilates reflectivity and radial velocity, and VrZZ assimilates reflectivity, radial velocity and Z_(DR) are conducted. In addition, the impact of assimilating Z_(DR) with the Mean Diameter Update (MDU) Approach has been investigated to understand the performance between the new method and the method proposed by Jung et al. 2008. Results of analyses show that water vapor and raindrops size are enhanced after assimilating Z_(DR), which modify the Z_(DR) structure toward observations. In addition, updating model by Mean Diameter Update Approach has much more improvement. Assimilating Vr and Z radar data into model improves Quantitative Precipitation Forecast (QPF) in the first hour forecasts. Nevertheless, VrZ underestimates the rainfall intensity in the following hours that leads to the worst extended probability than other experiments. On the contrary, the improvement of QPF would be extended to the third hour in the forecasts after Z_(DR) assimilation. Also, the extend probability of partial rainfall would be enhanced by using Mean Diameter Update Approach. In summary, properly assimilating additional Z_(DR) observations can not only illustrate the uniform Z_(DR) structure better but enhance precipitation prediction in the wintertime rainfall case. |
本系統中英文摘要資訊取自各篇刊載內容。