Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China
This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the Universi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2014-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/9/1/015001 |
| _version_ | 1797747998258626560 |
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| author | Qiaohong Sun Chiyuan Miao Qingyun Duan Dongxian Kong Aizhong Ye Zhenhua Di Wei Gong |
| author_facet | Qiaohong Sun Chiyuan Miao Qingyun Duan Dongxian Kong Aizhong Ye Zhenhua Di Wei Gong |
| author_sort | Qiaohong Sun |
| collection | DOAJ |
| description | This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed. |
| first_indexed | 2024-03-12T15:58:37Z |
| format | Article |
| id | doaj.art-6f112e5fbda74858b41d127f59c868f7 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:58:37Z |
| publishDate | 2014-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-6f112e5fbda74858b41d127f59c868f72023-08-09T14:44:19ZengIOP PublishingEnvironmental Research Letters1748-93262014-01-019101500110.1088/1748-9326/9/1/015001Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for ChinaQiaohong Sun0Chiyuan Miao1Qingyun Duan2Dongxian Kong3Aizhong Ye4Zhenhua Di5Wei Gong6State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University , Beijing 100875, People’s Republic of ChinaThis research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed.https://doi.org/10.1088/1748-9326/9/1/015001gridded datasetclimate changeprecipitationtemperatureChina |
| spellingShingle | Qiaohong Sun Chiyuan Miao Qingyun Duan Dongxian Kong Aizhong Ye Zhenhua Di Wei Gong Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China Environmental Research Letters gridded dataset climate change precipitation temperature China |
| title | Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China |
| title_full | Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China |
| title_fullStr | Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China |
| title_full_unstemmed | Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China |
| title_short | Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China |
| title_sort | would the real observed dataset stand up a critical examination of eight observed gridded climate datasets for china |
| topic | gridded dataset climate change precipitation temperature China |
| url | https://doi.org/10.1088/1748-9326/9/1/015001 |
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