Deriving a long-term pan evaporation reanalysis dataset for two Chinese pan types
文献类型：期刊论文
| 作者 | Wang, Kaiwen1,2,6; Liu, Xiaomang2; Li, Yuqi3; Yang, Xiaohua4; Bai, Peng2; Liu, Changming2; Chen, Fei5 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2019-12-01 |
| 卷号 | 579页码:11 |
| 关键词 | Pan evaporation reanalysis dataset Long-term continuous and consistent dataset Representativeness to atmospheric evaporative demand |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2019.124162 |
| 通讯作者 | Liu, Xiaomang(liuxm@igsnrr.ac.cn) |
| 英文摘要 | A long-term continuous and consistent pan evaporation (E-pan) reanalysis dataset will augment the analysis of E-pan distributions when the observation network is discontinuous or inconsistent, and assist in the evaluation of the outputs of General Circulation Models (GCMs) and Land Surface Models (LSMs). From the 1950s to early 2000s, China had a continuous observation of the D20 pan, but this was replaced by the 601B pan across China around 2002, and thus the E-pan observation network became discontinuous and inconsistent. This study developed a long-term monthly, 0.05 degrees, continuous and consistent reanalysis dataset for both D20 and 6018 pans covering mainland China throughout 1960-2014, based on meteorological data homogenization and interpolation and E-pan assimilation. The PenPan-V3 model used inE(pan) assimilation was successfully validated by observations at 767 and 591 stations for D20 and 601B pans, respectively. Comprehensively considering the physical influence of elevation, radiation, wind speed, humidity, and air temperature, the average annual and seasonal gridded E-pan reanalyses show significant spatial dependent on proximity to the ocean and latitude, consistent with previous studies. The reanalysis dataset can be used to analyze E-pan distributions across China, including the areas without observations, and to estimate the representativeness of E-pan to atmospheric evaporative demand. The dataset has been released in two cloud servers in China and the United States, and it will continue to be maintained and updated. |
| WOS关键词 | MAXIMAL T-TEST ; REFERENCE EVAPOTRANSPIRATION ; CLIMATE DATA ; ENERGY-BALANCE ; REFERENCE CROP ; TRENDS ; WATER ; MODEL ; DEMAND |
| 资助项目 | National Key R&D Program of China[2018YFA0605404] ; National Key R&D Program of China[2017YFC0506603] ; National Key R&D Program of China[2016YFC0401305] ; General Program of National Natural Science Foundation of China[51679007] ; General Program of National Natural Science Foundation of China[51379013] ; State Key Program of National Natural Science of China[41530635] |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000500371200015 |
| 出版者 | ELSEVIER |
| 资助机构 | National Key R&D Program of China ; General Program of National Natural Science Foundation of China ; State Key Program of National Natural Science of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/130164]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Xiaomang |
| 作者单位 | 1.Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 3.Univ Washington, Dept Urban Design & Planning, Seattle, WA 98195 USA 4.Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing, Peoples R China 5.Minist Water Resources, Gen Inst Water Resources & Hydropower Planning &, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Kaiwen,Liu, Xiaomang,Li, Yuqi,et al. Deriving a long-term pan evaporation reanalysis dataset for two Chinese pan types[J]. JOURNAL OF HYDROLOGY,2019,579:11. |
| APA | Wang, Kaiwen.,Liu, Xiaomang.,Li, Yuqi.,Yang, Xiaohua.,Bai, Peng.,...&Chen, Fei.(2019).Deriving a long-term pan evaporation reanalysis dataset for two Chinese pan types.JOURNAL OF HYDROLOGY,579,11. |
| MLA | Wang, Kaiwen,et al."Deriving a long-term pan evaporation reanalysis dataset for two Chinese pan types".JOURNAL OF HYDROLOGY 579(2019):11. |
入库方式： OAI收割
来源：地理科学与资源研究所
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