Evaluating clouds in CMIP6 models with satellite data and the ESMValTool
Biases in model simulations of present-day climate do not only affect confidence in the models but also raise concerns about the accurate representation of future climate change. In this study we investigate the performance of state-of-the-art global climate models from the sixth phase of the Couple...
| Main Authors: | , , |
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| Format: | Conference Object |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://elib.dlr.de/143968/ https://elib.dlr.de/143968/1/Lauer_ESMValTool_CFMIP2021_elib.pdf |
| Summary: | Biases in model simulations of present-day climate do not only affect confidence in the models but also raise concerns about the accurate representation of future climate change. In this study we investigate the performance of state-of-the-art global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) by comparing simulated cloud properties with satellite observations. A focus is the variability of clouds on seasonal and interannual time scales as well as the 3-dimensional distributions of cloud fraction, cloud liquid and cloud ice water content. The analysis includes an investigation of cloud properties by dynamical regime and is performed with the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of Earth System Models. While many long-standing biases in the simulated cloud properties in CMIP6 models persist, first results show, for instance, that the CMIP5 problem of clouds over the Southern Ocean being too reflective ("too few, too bright") is reduced in CMIP6. Comparisons with satellite data also show that the total cloud water for a given total cloud fraction in CMIP6 is in better agreement with observations such as ESACCI-CLOUD compared to CMIP5. |
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