Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
Comparison of Surface Air Temperature between Observation and Reanalysis Data over Eastern China for the Last 100 Years
Siqi ZHANGGuoyu RENYuyu RENXiubao SUN
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JOURNALS FREE ACCESS Advance online publication

Article ID: 2019-004

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Abstract

 This study aimed to improve understanding of the differences in surface air temperature data between observations and reanalysis since the beginning of the 20th century and to address the reanalysis data error. The anomaly correlation, standard deviation, and linear trend of temperature during 1909–2010 in eastern China was analyzed based on homogenized observation data from 16 stations and two sets of 20th century monthly mean surface air temperature reanalysis data (20CR and ERA20C). The results show that the inter-annual and decadal variability were consistent between reanalysis and observations in eastern China after 1979. The reanalysis data exhibited a large fluctuation during the 1960s. The average 20CR temperature was lower than the observations during 1920–1950. The inter-annual and decadal variability for winter and spring were consistent with the observations. The correlation and standard deviation ratio between the reanalysis and observations demonstrated a high consistency of their inter-annual variability and dispersion. The ERA20C data were generally closer to the observations than the 20CR data for the period 1979–2010. The linear trends of surface air temperature showed clear warming in both reanalysis datasets and the observations, but the reanalysis trends were significantly smaller than the observational trends for annual mean temperature and most of the seasonal mean temperatures after the 1950s. Overall, ERA20C was generally closer to the observational temperatures than 20CR during 1909–2010, but this consistency does not necessarily indicate ERA20C’s suitability for climate change research because of the systematic bias referenced to the observational data.

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© The Author(s) 2019. This is an open access article published by the Meteorological Society of Japan under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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