维普中文期刊产品整合服务

Applicability Assessment of the 1998–2018 CLDAS Multi-Source Precipitation Fusion Dataset over China

查看全文 作　　者：Shuai [1]SUN;Chunxiang [1]SHI;Yang [1]PAN;Lei [1]BAI;Bin [1]XU;Tao [1]ZHANG;Shuai [1]HAN;Lipeng [1]JIANG 高影响力作者 机构地区：[1]National Meteorological Information Center,China Meteorological Administration,Beijing 100081高影响力机构 出　　处：《Journal of Meteorological Research》索引2020年第34卷第4期,共14页高影响力期刊 基　　金：Supported by the National Key Research and Development Program of China(2018YFC1506601);National Natural Science Foundation of China(91437220);China Meteorological Administration Special Public Welfare Research Fund(GYHY201506002 and GYHY201206008);China Meteorological Administration“Meteorological Data Quality Control and Multi-source Data Fusion and Reanalysis”project。 摘　　要：Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to retrieve solid precipitation. In addition, there are no long-term, high-quality precipitation data in China that can be used to drive land surface models. To address these issues, in the China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS), we blended the Climate Prediction Center(CPC) morphing technique(CMORPH) and Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) precipitation datasets with observed temperature and precipitation data on various temporal scales using multigrid variational analysis and temporal downscaling to produce a multi-source precipitation fusion dataset for China(CLDAS-Prcp). This dataset covers all of China at a resolution of 6.25 km at hourly intervals from 1998 to 2018. We performed dependent and independent evaluations of the CLDAS-Prcp dataset from the perspectives of seasonal total precipitation and land surface model simulation. Our results show that the CLDAS-Prcp dataset represents reasonably the spatial distribution of precipitation in China. The dependent evaluation indicates that the CLDAS-Prcp performs better than the MERRA2 precipitation, CMORPH precipitation, Global Land Data Assimilation System version 2(GLDAS-V2.1) precipitation,and CLDAS-V2.0 winter precipitation, as compared to the meteorological observational precipitation. The independent evaluation indicates that the CLDAS-Prcp dataset performs better than the Global Precipitation Measurement(GPM) precipitation dataset and is similar to the CLDAS-V2.0 summer precipitation dataset based on the hydrological observational precipitation. The simulated soil moisture content driven by CLDAS-Prcp is slightly better than that driven by the CLDAS-V2.0 precipitation, whereas the snow depth simulation driven by CLDAS-Prcp is much better than that driven by the CLDAS-V2.0 precipitation. This is because the CLDAS-Prcp data have included solid precipitation. Overall, the CLDAS-Prcp dataset can meet the needs of land surface and hydrological modeling studies. 关 键 词：China Meteorological Administration Land Data Assimilation System(CLDAS) PRECIPITATION data fusion Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) Climate Prediction Center(CPC)morphing technique(CMORPH) Space–Time Multiscale Variational Analysis System(STMAS) Noah land surface model with multiparameterization options(Noah-MP)
相关文献

参考文献(36)

引证文献(18)

耦合文献(698)

网站首页 | 关于我们 | 联系我们 | 产品服务 | 客服中心 | 广告服务 | 版权声明 | 网站联盟 | 友情链接 | 售卡网点

版权所有© 渝B2-20050021-1　渝公网安备 50019002500403号　违法和不良信息举报中心

互联网出版许可证 新出网证(渝)字10号 全国400电话 - 免长途话费