Abstract
Soil moisture is an important state variable for land-atmosphere interactions. It is a vital land surface variable for research on hydrology, agriculture, climate, and drought monitoring. In current study, a soil moisture data assimilation framework has been developed by using the Community Land Model version 4.5 (CLM4.5) and the proper orthogonal decomposition (POD)-based ensemble four-dimensional variational assimilation (PODEn4DVar) algorithm. Assimilation experiments were conducted at four agricultural sites in Pakistan by assimilating in-situ soil moisture observations. The results showed that it was a reliable system. To quantify further the feasibility of the data assimilation (DA) system, soil moisture observations from the top four soil-depths (0–5, 5–10, 10–20, and 20–30 cm) were assimilated. The evaluation results indicated that the DA system improved soil moisture estimation. In addition, updating the soil moisture in the upper soil layers of CLM4.5 could improve soil moisture estimation in deeper soil layers [layer 7 (L7, 62.0 cm) and layer 8 (L8, 103.8 cm)]. To further evaluate the DA system, observing system simulation experiments (OSSEs) were designed for Pakistan by assimilating daily observations. These idealized experiments produced statistical results that had higher correlation coefficients, reduced root mean square errors, and lower biases for assimilation, which showed that the DA system is able to produce and improve soil moisture estimation in Pakistan.
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Supported by the National Key Basic Research and Development Program of China (2018YFC1506602), National Natural Science Foundation of China (41830967), and Key Research Program of Frontier Sciences, Chinese Academy of Sciences (QYZDY-SSW-DQC012).
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Mahmood, T., Xie, Z., Jia, B. et al. A Soil Moisture Data Assimilation System for Pakistan Using PODEn4DVar and CLM4.5. J Meteorol Res 33, 1182–1193 (2019). https://doi.org/10.1007/s13351-019-9020-2
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DOI: https://doi.org/10.1007/s13351-019-9020-2