The Performance of CMIP6 Versus CMIP5 in Simulating Temperature Extremes Over the Global Land Surface. Issue 18 (18th September 2020)

• Record Type: Journal Article
• Authors: Fan, Xuewei; Miao, Chiyuan; Duan, Qingyun; Shen, Chenwei; Wu, Yi
• Is Part Of: Journal of geophysical research. Volume 125:Issue 18(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-18
• Subjects: CMIP6 -- global land -- performance -- temperature extremes; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2020JD033031
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Simulations from the models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), which represent the most recent generation of climate models, are now available. Understanding the performance of these models in simulating historical climate extremes can provide a basis for producing reliable future climate projections. Here, we assess the simulation of 16 indices of temperature extremes defined by the Expert Team on Climate Change Detection and Indices using results from 24 CMIP6 models as compared with results from CMIP5. Comparisons with observations and reanalyses indicate that the CMIP6 models could capture the spatial patterns and temporal variations of the observed temperature extremes well for some indices, although less well for others. Based on spatial and temporal skill scores, CMIP6 ensemble means were more skillful in simulating absolute and threshold indices of extreme temperature than CMIP5 ensemble means were, but the performances of both the CMIP5 and CMIP6 ensemble means in simulating the spatial patterns for duration and percentile indices were relatively unsatisfactory (spatial skill scores S < 0.3). Furthermore, our results suggest that there have been improvements in spatial pattern skill scores in some individual CMIP6 models relative to CMIP5 model scores for summer days, tropical nights, cold spell duration, and diurnal temperature range. Key Points: The performance of CMIP6 models has been evaluated for simulating global temperature extremes CMIP6 models can capture the spatial patterns and temporal variations of temperature extremes indices CMIP6 shows improvement over CMIP5 in simulating several absolute and threshold indices of extreme temperature