globalchange  > 影响、适应和脆弱性
DOI: 10.1007/s00382-017-3755-1
Scopus记录号: 2-s2.0-85021129501
论文题名:
A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900
作者: Xu W.; Li Q.; Jones P.; Wang X.L.; Trewin B.; Yang S.; Zhu C.; Zhai P.; Wang J.; Vincent L.; Dai A.; Gao Y.; Ding Y.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 50, 期:2018-07-08
起始页码: 2513
结束页码: 2536
语种: 英语
英文关键词: Climate change ; CMA-LSAT dataset ; Homogenized ; Surface air temperature
Scopus关键词: air temperature ; annual variation ; climate change ; climate variation ; data quality ; data set ; homogeneity ; land surface
英文摘要: A 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 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °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. © 2017, Springer-Verlag GmbH Germany.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109360
Appears in Collections:影响、适应和脆弱性
气候变化事实与影响

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作者单位: China Meteorological Administration, National Meteorological Information Center, 46 Zhongguancun South Avenue, Haidian District, Beijing, 100081, China; School of Atmospheric Sciences, Sun Yat-sen University, 135 Xingangxi Road, Guangzhou, 510275, China; Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom; Center of Excellence for Climate Change Research, Department of Meteorology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia; Climate Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, ON, Canada; Australian Bureau of Meteorology, Melbourne, VIC, Australia; China Meteorological Administration, China Academy of Meteorological Sciences, 46 Zhongguancun South Avenue, Haidian District, Beijing, 100081, China; LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; Department of Atmospheric and Environmental Sciences, University at Albany, SUNY, Albany, NY 12222, United States; China Meteorological Administration, 46 Zhongguancun South Avenue, Haidian District, Beijing, 100081, China; China Meteorological Administration, National Climate Center, 46 Zhongguancun South Avenue, Haidian District, Beijing, 100081, China

Recommended Citation:
Xu W.,Li Q.,Jones P.,et al. A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900[J]. Climate Dynamics,2018-01-01,50(2018-07-08)
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