4.7 Article

Evaluation of Eight Current Reanalyses in Simulating Land Surface Temperature from 1979 to 2003 in China

Journal

JOURNAL OF CLIMATE
Volume 30, Issue 18, Pages 7379-7398

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-16-0903.1

Keywords

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Funding

  1. National Natural Science Foundation of China [41525018]
  2. National Basic Research Program of China [2017YFA0603601]

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Land surface temperature T-s provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational T-s data makes assessing model simulations difficult. Here, the authors first examined the simulated T-s of eight current reanalyses based on homogenized T-s data collected at similar to 2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of T-s in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRAl and versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of T-s over the north China plain and south China is mostly influenced by surface incident solar radiation R-s, followed by precipitation frequency, whereas the opposite is true over the northwest China, northeast China, and the Tibetan Plateau. This variable relationship is well captured by ERA-Interim, ERA-Interim land, MERRA, and JRA-55. The homogenized T-s data show a warming of 0.34 degrees C decade(-1) from 1979 to 2003 in China, varying between 0.25 degrees and 0.42 degrees C decade(-1) for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of T-s over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of T-s over the north China plain and south China owing to their biases in simulating the R-s and precipitation frequency trends. This study provides a diagnostic method for examining the capability of current atmospheric/land reanalysis data in regional climate change studies.

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