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題 名 | 運用一維變分反演法於NOAA-12衛星資料及其相關問題之探討=One Dimensional Variational Retrieval Scheme on Tovs Data and its Associate Problem Study |
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作 者 | 周鑑本; | 書刊名 | 氣象學報 |
卷 期 | 42:3 1998.09[民87.09] |
頁 次 | 頁201-211 |
分類號 | 328.886 |
關鍵詞 | 反演; 偏差; Retrieval; Bias; |
語 文 | 中文(Chinese) |
英文摘要 | In this study a One Dimensional Variational Retrieval (1DVAR) was appiled to the TIROS Operational Vertical Sounder (TOVS) data from the NOAA-12 satellite. The result revealed that this method substantially improved the forecast background field, even in the place where the traditional observation was relatively dense. Specifically, the retrieval slightly improved the temperature profiles of the forecast background which was already quite accurate. More positive impact was found on humidity profiles at upper tropopsheric levels. It is important for this method to analyze the error statistics of satellite data and to remove the bias characteristics. We used a statistical method from the ECMWF to evaluate the error of satellite data. We then removed the bias from satellite observations by a simple way whenever those observational channels had large bias. After the bias had been removed, the result of this method showed considerable improvement. The forecast background's expected error covariance is another factor to affect the retrieval result. We calculated the error covariance matrix by using the forecast and analysis fields from the regional model of the Central Weather Bureau in the period of July-August 1996, and found that the userfulness of 1 DVAR Scheme was limited when the forecast background did not fit the characteristics described by error covariance. |
本系統中英文摘要資訊取自各篇刊載內容。