The Impact of the Observation Data Assimilation on Atmospheric Reanalyses over Tibetan Plateau and Western Yunnan-Guizhou Plateau

Abstract

Three modern atmospheric reanalyses with different input observation data (NOAA–CIRES 20th Century Reanalysis (20CR), Japanese 55-year Reanalysis (JRA-55), and JRA-55C) were compared against the independent radiosonde observations over the Tibetan Plateau (TP) and the western Yunnan–Guizhou Plateau (YGP) from the China-Japan Meteorological Disaster Reduction Cooperation (JICA/Tibet) Center Project in the summer of 2018 to investigate the effects of the assimilation of the observation data on the quality and accuracy of the reanalyses in the troposphere. The results indicate that the mean biases and mean root-mean-square errors of horizontal wind, temperature, and specific humidity significantly decreased when comparing the 20CR reanalysis (assimilating only surface pressure) to the JRA-55C (assimilating conventional surface and upper-air observations) and the JRA-55 (assimilating conventional and satellite observations), and the bias spreads of these aboveground variables in JRA-55C and JRA-55 were cut to almost half of those observed in 20CR. However, the mean biases and uncertainties varied little from JRA-55C to JRA-55. This means that the assimilation of conventional observation data plays a vital role in the quality of reanalyses for the troposphere over these data-sparse plateaus. It was also found that the temperature and specific humidity near the ground over TP showed larger mean biases and bias spans than those over YGP, likely due to the sparser surface observation over TP.