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ANALYSIS IN THEORY AND APPLICATIONS
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《Analysis in Theory and Applications》 2008年第4期I0001-I0002,共2页
关键词 CHEN analysis IN THEORY and applications Vol CONTENTS
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《ANALYSIS IN THEORY AND APPLICATIONS》CONTENTS
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《Analysis in Theory and Applications》 2012年第4期I0001-I0002,共2页
关键词 analysis IN THEORY and applications CONTENTS
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ANALYSIS in THEORY and APPLICATIONS
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《Analysis in Theory and Applications》 2007年第4期F0002-F0002,共1页
关键词 CHEN analysis IN THEORY and applications Vol.23 2007 CONTENTS
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ANALYSIS IN THEORY AND APPLICATIONS Vol.25,2009 CONTENTS
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《Analysis in Theory and Applications》 2009年第4期I0001-I0002,共2页
关键词 analysis IN THEORY and applications Vol.25 2009 CONTENTS
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ANALYSIS IN THEORY AND APPLICATIONS Vol.27,2011 CONTENTS
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《Analysis in Theory and Applications》 2011年第4期I0002-I0003,共2页
关键词 analysis IN THEORY and applications Vol.27 2011 CONTENTS
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NOTICE
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《Analysis in Theory and Applications》 2010年第3期F0003-F0003,共1页
1. The Journal Analysis in Theory and Applications ( abbr. ATA used to be Approximation Theory and its Applications in 1984-2002) publishes original papers in the following fields:
关键词 WANG analysis IN THEORY and applications Vol CONTENTS 2010
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NOTICE
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《Analysis in Theory and Applications》 2005年第3期F0003-F0003,共1页
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关键词 analysis IN THEORY and applications Vol CONTENTS
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NOTICE
8
《Analysis in Theory and Applications》 2010年第1期F0003-F0003,共1页
1. The Journal Analysis in Theory and Applications ( abbr. ATA used to be Approximation Theory and its Applications in 1984-2002) publishes original papers in the following fields:
关键词 analysis in THEORY and applications Members of Editorial Committee WANG
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Applicability Assessment of the 1998–2018 CLDAS Multi-Source Precipitation Fusion Dataset over China 被引量:10
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作者 Shuai SUN Chunxiang SHI +5 位作者 Yang PAN Lei BAI Bin XU Tao ZHANG Shuai HAN Lipeng JIANG 《Journal of Meteorological Research》 SCIE CSCD 2020年第4期879-892,共14页
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 ... 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. 展开更多
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)
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