- 期刊
高解析土壤資料同化系統之效能評估
Evaluation of the High Resolution Land Data Assimilation System
摘要
本研究引進美國國家大氣研究中心所發展之高解析土壤資料同化系統（High Resolution Land Data Assimilation System, HRLDAS），嘗試使用觀測之降水及地面的大氣溫度、濕度、風場和輻射通量等，藉著Noah土壤模式將地面觀測資訊透由土壤物理過程逐步影響到深層土壤，進而取得和大氣強迫作用平衡的土壤溫度和土壤濕度，此即為HRLDAS之土壤分析場，亦可作為氣象模式之土壤初始場。本研究旨在評估HRLDAS土壤溫度和土壤濕度分析場之效能，定性分析顯示HRLDAS須經3個月以上之模式起轉才可與近地面的大氣驅動資料（Forcing data）達能量平衡，而其在土壤溫度和土壤濕度之分析場對降水的反應相當合理。在定量分析上，使用2010至2011年HRLDAS每日逐時土壤溫度分析場，並與台灣地區之土壤溫度觀測值比較，發現HRLDAS的土壤溫度分析場和觀測相當接近，相較之下，作業模式之土壤溫度分析場則有較顯著的暖偏差。此一結論有助於進一步結合HRLDAS土壤分析場和大氣預報模式，以評估其在模式預報中扮演的角色。
並列摘要
The performance of the High Resolution Land Data Assimilation System (HRLDAS) was evaluated in this study. The HRLDAS assimilated the hourly precipitation, near-surface air temperature, moisture, wind, and radiation to drive the Noah land surface model from the upper boundary condition and then output the predicted soil temperature and moisture. The HRLDAS analyses including the soil temperature and moisture were then obtained through an extended assimilation cycle as the Noah land surface model reached an equilibrium state between the surface forcing and the soil state variables. The performances of HRLDAS soil temperature and moisture analysis were examined in the study. Qualitatively, the soil moisture analysis of the HRLDAS has the reasonable response to the surface precipitation forcing, however, it required at least three months for spin-up to reach the equilibrium state. Quantitatively, the verification of the HRLDAS soil temperature analysis against the observations shows it outperforms the operational soil temperature, which was interpolated from the Global Forecast System of the National Center for Environment Prediction. The further study is undergoing to reveal the impact of the HRLDAS analysis on the atmospheric model prediction.
延伸閱讀
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