Optimization of key land surface albedo parameter reduces wet bias of climate modeling for the Tibetan Plateau
文献类型：期刊论文
| 作者 | Ma, Xiaogang5,7; Zhao, Long3,6; Sun, Jing5; Chen, Jinyan3; Wang, Yan2; Zhou, Jianhong3,5; Liu, Jiarui5; Lu, Hui1,4,5; Yang, Kun5,6 |
| 刊名 | SCIENCE CHINA-EARTH SCIENCES
 |
| 出版日期 | 2025-07-17 |
| 卷号 | N/A |
| 关键词 | Surface albedo parameter Precipitation simulation Moisture flux convergence Evapotranspiration Tibetan Plateau |
| ISSN号 | 1674-7313 |
| DOI | 10.1007/s11430-025-1635-0 |
| 产权排序 | 5 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Land surface albedo plays a key role in regulating surface energy budgets and thereby land-atmosphere interactions. Most land surface models employ a so-called soil color parameter to determine albedos for dry/saturated soils, yet it is poorly characterized in the Weather Research and Forecasting (WRF) model, leading to an underestimation of summertime surface albedo on the Tibetan Plateau (TP). This study introduces an optimized soil color map, which can effectively enhance the simulation of surface albedo and land surface temperature over a 10-year climate modeling period. This improvement reduces the TP's thermal effect, along with decreased net radiation, latent, and sensible heat during the summer, leading to an increase in geopotential height in the lower troposphere and a reduction in water vapor flux convergence. The resulting precipitation estimation shows a reduced wet bias (52% to 36%), as compared with IMERG and GSMaP products. Further evaluation against rain-gauge observations suggests that the incorporation of an optimized soil color map improves precipitation simulation at 66% of the stations, with mean wet bias mitigated from 1.02 to 0.82 mm d-1. The findings reveal that the underestimation of surface albedo is partially responsible for the wet bias in precipitation simulation. It also highlights the feasibility of improving climate modeling by optimizing land surface parameters, which is highly affordable through the joint use of land surface models and satellite remote sensing products. |
| URL标识 | 查看原文 |
| WOS关键词 | SNOW ALBEDO ; VEGETATION ; WRF ; IMPLEMENTATION ; SIMULATION ; IMPACTS ; NOAH |
| WOS研究方向 | Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001531443700001 |
| 出版者 | SCIENCE PRESS |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/215316]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Zhao, Long |
| 作者单位 | 1.Tsinghua Univ, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China; 2.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 3.Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst, Natl Observat & Res Stn, Chongqing 400715, Peoples R China; 4.Tsinghua Univ, Xian Inst Surveying & Mapping, Joint Res Ctr Next Generat Smart Mapping, Dept Earth Syst Sci, Beijing 100084, Peoples R China 5.Tsinghua Univ, Inst Global Change Studies, Dept Earth Syst Sci, Minist Educ,Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China; 6.Chinese Acad Sci, Inst Tibetan Plateau Res, State Key Lab Tibetan Plateau Earth Syst Environm, Beijing 100101, Peoples R China; 7.Minist Emergency Management China, Natl Inst Nat Hazards, Beijing 100085, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Ma, Xiaogang,Zhao, Long,Sun, Jing,et al. Optimization of key land surface albedo parameter reduces wet bias of climate modeling for the Tibetan Plateau[J]. SCIENCE CHINA-EARTH SCIENCES,2025,N/A. |
| APA | Ma, Xiaogang.,Zhao, Long.,Sun, Jing.,Chen, Jinyan.,Wang, Yan.,...&Yang, Kun.(2025).Optimization of key land surface albedo parameter reduces wet bias of climate modeling for the Tibetan Plateau.SCIENCE CHINA-EARTH SCIENCES,N/A. |
| MLA | Ma, Xiaogang,et al."Optimization of key land surface albedo parameter reduces wet bias of climate modeling for the Tibetan Plateau".SCIENCE CHINA-EARTH SCIENCES N/A(2025). |
入库方式： OAI收割
来源：地理科学与资源研究所
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