| Land surface model calibration through microwave data assimilation for improving soil moisture simulations | |
| Yang, K (Yang, Kun)1,2; Zhu, L (Zhu, La)1,3; Chen, YY (Chen, Yingying)1,2; Zhao, L (Zhao, Long)4; Qin, J (Qin, Jun)1; Lu, H (Lu, Hui)5,6; Tang, WJ (Tang, Wenjun)1,2; Han, ML (Han, Menglei)1,3; Ding, BH (Ding, Baohong)1; Fang, N (Fang, Nan)3; Yang, K | |
| Source Publication | JOURNAL OF HYDROLOGY
 |
| 2016 | |
| Volume | 533Issue:0Pages:266-276 |
| DOI | 10.1016/j.jhydrol.2015.12.018 |
| Abstract | Soil moisture is a key variable in climate system, and its accurate simulation needs effective soil parameter values. Conventional approaches may obtain soil parameter values at point scale, but they are costly and not efficient at grid scale (10-100 km) of current climate models. This study explores the possibility to estimate soil parameter values by assimilating AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. A crucial step for the parameter estimation is made to suppress the contamination of uncertainties in atmospheric forcing data. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration. (C) 2015 Elsevier B.V. All rights reserved. |
| Subject Area | 自然地理学 |
| WOS ID | WOS:000370086200022 |
| Language | 英语 |
| Indexed By | SCI |
| Keyword | Central Tibetan Plateau In-situ Observations Discharge Measurements Hydraulic-properties Satellite System Temperature Validation Products Regions |
| Cooperation Status | 国际 |
| Department | 环境 |
| Subtype | Article |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.itpcas.ac.cn/handle/131C11/7766 |
| Collection | 图书馆 |
| Corresponding Author | Yang, K |
| Affiliation | 1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Univ Texas Austin, Jackson Sch Geosci, Dept Geol Sci, C1100, Austin, TX 78712 USA 5.Tsinghua Univ, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China 6.Tsinghua Univ, Ctr Earth Syst Sci, Beijing 100084, Peoples R China |
| Recommended Citation GB/T 7714 | Yang, K ,Zhu, L ,Chen, YY ,et al. Land surface model calibration through microwave data assimilation for improving soil moisture simulations[J]. JOURNAL OF HYDROLOGY,2016,533(0):266-276. |
| APA | Yang, K .,Zhu, L .,Chen, YY .,Zhao, L .,Qin, J .,...&Yang, K.(2016).Land surface model calibration through microwave data assimilation for improving soil moisture simulations.JOURNAL OF HYDROLOGY,533(0),266-276. |
| MLA | Yang, K ,et al."Land surface model calibration through microwave data assimilation for improving soil moisture simulations".JOURNAL OF HYDROLOGY 533.0(2016):266-276. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| V.533 266-276 2016.p（2422KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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