
Evaluation of Eight Current Reanalyses in Simulating Land Surface Temperature from 1979 to 2003 in China
Author(s) -
Chunlüe Zhou,
Kaicun Wang,
Qian Ma
Publication year - 2017
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-16-0903.1
Subject(s) - climatology , china , plateau (mathematics) , environmental science , precipitation , global warming , interim , climate change , meteorology , geography , geology , mathematical analysis , oceanography , mathematics , archaeology
Land surface temperature Ts provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational Ts data makes assessing model simulations difficult. Here, the authors first examined the simulated Ts of eight current reanalyses based on homogenized Ts data collected at ~2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of Ts in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRA land versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of Ts over the north China plain and south China is mostly influenced by surface incident solar radiation Rs, 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 Ts data show a warming of 0.34°C decade−1 from 1979 to 2003 in China, varying between 0.25° and 0.42°C decade−1 for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of Ts over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of Ts over the north China plain and south China owing to their biases in simulating the Rs 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.