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A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900
Xu, Wenhui1; Li, Qingxiang2; Jones, Phil3,4; Wang, Xiaolan L.5; Trewin, Blair6; Yang, Su1; Zhu, Chen1; Zhai, Panmao7; Wang, Jinfeng8; Vincent, Lucie5; Dai, Aiguo9; Gao, Yun10; Ding, Yihui11
2018-04-01
Source PublicationCLIMATE DYNAMICS
ISSN0930-7575
Volume50Issue:7-8Pages:2513-2536
Corresponding AuthorLi, Qingxiang(liqingx5@mail.sysu.edu.cn)
AbstractA new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900-2014, 1979-2014 and 1998-2014. The best estimates of warming trends and there 95% confidence ranges for 1900-2014 are approximately 0.102 +/- 0.006 A degrees C/decade for the whole year, and 0.104 +/- 0.009, 0.112 +/- 0.007, 0.090 +/- 0.006, and 0.092 +/- 0.007 A degrees C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900-2014 and 1979-2014. For an even shorter and more recent period (1998-2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes.
KeywordCMA-LSAT dataset Surface air temperature Homogenized Climate change
DOI10.1007/s00382-017-3755-1
WOS KeywordCLIMATE DATA SERIES ; MAXIMAL T-TEST ; PRECIPITATION SERIES ; MEAN TEMPERATURE ; WARMING HIATUS ; F-TEST ; CHINA ; URBAN ; EXTREMES ; TREND
Indexed BySCI
Language英语
Funding ProjectNational Special Public Welfare Research Fund[GYHY201406016] ; National Special Public Welfare Research Fund[GYHY201206012] ; China Meteorological Administration Special Foundation for Climate Change[CCSF201438] ; Natural Science Foundation of China[91546117] ; Natural Science Foundation of China[71373131]
Funding OrganizationNational Special Public Welfare Research Fund ; China Meteorological Administration Special Foundation for Climate Change ; Natural Science Foundation of China
WOS Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000428600200012
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/57345
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLi, Qingxiang
Affiliation1.China Meteorol Adm, Natl Meteorol Informat Ctr, 46 Zhongguancun South Ave, Beijing 100081, Peoples R China
2.Sun Yat Sen Univ, Sch Atmospher Sci, 135 Xingangxi Rd, Guangzhou 510275, Guangdong, Peoples R China
3.Univ East Anglia, Sch Environm Sci, Climat Res Unit, Norwich NR4 7TJ, Norfolk, England
4.King Abdulaziz Univ, Dept Meteorol, Ctr Excellence Climate Change Res, Jeddah 21589, Saudi Arabia
5.Environm & Climate Change Canada, Div Climate Res, Sci & Technol Branch, Toronto, ON, Canada
6.Australian Bur Meteorol, Melbourne, Vic, Australia
7.China Acad Meteorol Sci, China Meteorol Adm, 46 Zhongguancun South Ave, Beijing 100081, Peoples R China
8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, LREIS, Beijing 100101, Peoples R China
9.SUNY Albany, Dept Atmospher & Environm Sci, Albany, NY 12222 USA
10.China Meteorol Adm, 46 Zhongguancun South Ave, Beijing 100081, Peoples R China
11.China Meteorol Adm, Natl Climate Ctr, 46 Zhongguancun South Ave, Beijing 100081, Peoples R China
Recommended Citation
GB/T 7714
Xu, Wenhui,Li, Qingxiang,Jones, Phil,et al. A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900[J]. CLIMATE DYNAMICS,2018,50(7-8):2513-2536.
APA Xu, Wenhui.,Li, Qingxiang.,Jones, Phil.,Wang, Xiaolan L..,Trewin, Blair.,...&Ding, Yihui.(2018).A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900.CLIMATE DYNAMICS,50(7-8),2513-2536.
MLA Xu, Wenhui,et al."A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900".CLIMATE DYNAMICS 50.7-8(2018):2513-2536.
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