Plot showing pattern correlations between models and observations for simulated annual mean climatology over the period 1980–1999 for five climate variables
Pattern correlations between models and observations for the simulated annual mean climatology over the period 1980–1999 for five climate variables: near-surface temperature, precipitation, outgoing longwave radiation at the top of the atmosphere (TOA), shortwave cloud radiative effect at TOA, and atmosphere pressure at sea level. Each mark is for an individual CMIP3 (black), CMIP5 (blue), and CMIP6 (brown) models (short lines), along with the corresponding ensemble averages (long lines). To ensure a fair comparison across a range of model resolutions, the pattern correlations are computed after re-gridding all data sets to a resolution of 2.5° in longitude and 2.5° in latitude. Credit: Bock et al. [2020], Figure 7
Source: Journal of Geophysical Research: Atmospheres

Since the early 1990s, the Coupled Model Intercomparison Project (CMIP) has been using climate model simulations to better understand past, present, and future climate variability. Bock et al. [2020] contrast the performances of climate models in three phases – CMIP3, CMIP5, and the latest CMIP6 – which represent the time evolution of climate modeling in the past 15 years.

Temperature, water vapor, and zonal wind speed show improvements in CMIP6 with amplitudes of many long-standing biases smaller than CMIP3 and CMIP5. High-resolution models show significant improvements in their historical CMIP6 simulations for temperature and precipitation mean biases. A striking result is that the spread in effective climate sensitivity in CMIP6 models is larger than in previous phases. Results from CMIP6 will be used in the next assessment of past and future climate change by the Inter-governmental Panel for Climate Change (IPCC).

Citation: Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., et al. [2020]. Quantifying progress across different CMIP phases with the ESMValTool. Journal of Geophysical Research: Atmospheres, 125, e2019JD032321.

—Minghua Zhang, Editor-in-Chief, JGR: Atmospheres

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