Bias Correction and Ensemble Projections of Temperature Changes over Ten Subregions in CORDEX East Asia
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• Original Paper •
Bias Correction and Ensemble Projections of Temperature Changes over Ten Subregions in CORDEX East Asia Chenwei SHEN, Qingyun DUAN*, Chiyuan MIAO, Chang XING, Xuewei FAN, Yi WU, and Jingya HAN State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China (Received 6 February 2020; revised 1 July 2020; accepted 17 July 2020) ABSTRACT Regional climate models (RCMs) participating in the Coordinated Regional Downscaling Experiment (CORDEX) have been widely used for providing detailed climate change information for specific regions under different emissions scenarios. This study assesses the effects of three common bias correction methods and two multi-model averaging methods in calibrating historical (1980−2005) temperature simulations over East Asia. Future (2006−49) temperature trends under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios are projected based on the optimal bias correction and ensemble averaging method. Results show the following: (1) The driving global climate model and RCMs can capture the spatial pattern of annual average temperature but with cold biases over most regions, especially in the Tibetan Plateau region. (2) All bias correction methods can significantly reduce the simulation biases. The quantile mapping method outperforms other bias correction methods in all RCMs, with a maximum relative decrease in root-mean-square error for five RCMs reaching 59.8% (HadGEM3-RA), 63.2% (MM5), 51.3% (RegCM), 80.7% (YSU-RCM) and 62.0% (WRF). (3) The Bayesian model averaging (BMA) method outperforms the simple multi-model averaging (SMA) method in narrowing the uncertainty of bias-corrected results. For the spatial correlation coefficient, the improvement rate of the BMA method ranges from 2% to 31% over the 10 subregions, when compared with individual RCMs. (4) For temperature projections, the warming is significant, ranging from 1.2°C to 3.5°C across the whole domain under the RCP8.5 scenario. (5) The quantile mapping method reduces the uncertainty over all subregions by between 66% and 94%. Key words: CORDEX-EA, bias correction, BMA, temperature projection Citation: Shen, C. W., Q. Y. Duan,, C. Y. Miao, C. Xing, X. W. Fan, Y. Wu, and J. Y. Han, 2020: Bias correction and ensemble projections of temperature changes over ten subregions in CORDEX East Asia. Adv. Atmos. Sci., 37(11), 1191−1210, https://doi.org/10.1007/s00376-020-0026-6. Article Highlights:
• RCMs have obvious cold biases over the East Asia region, especially in cold seasons. • Bias correction and BMA methods significantly reduce biases in RCM simulations. • Temperatures increase between 1.2°C and 3.5°C under the RCP8.5 scenario in 2030−49. • The warming trend is more remarkable in the northern part of the East Asia region.
1. Introduction Climate change has attracted much attention as its effects on human society and ecological environments have grown over past decades (Grimm et al., 2013; Sun et
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