Improvements in Cloud and Water Vapor Simulations Over the Tropical Oceans in CMIP6 Compared to CMIP5. Issue 5 (17th May 2021)

• Record Type: Journal Article
• Authors: Jiang, Jonathan H.; Su, Hui; Wu, Longtao; Zhai, Chengxing; Schiro, Kathleen A.
• Is Part Of: Earth and space science. Volume 8:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-17
• Subjects: climate model -- clouds -- satellite observation -- water vapor; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2020EA001520
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Clouds and water vapor are among the most difficult quantities for global climate models to simulate because they are affected by physical processes that operate over scales unresolved by current climate models. We use NASA satellite data to assess the representation of clouds and water vapor structures in 28 climate models that participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Each model is assigned numerical scores based on its performance in simulating spatial mean, variance and pattern correlation of multi‐year mean clouds and water vapor structures in lower, middle, upper troposphere, and near the tropopause over tropical oceans. We find measurable improvements in CMIP6 models relative to CMIP5 models for both clouds and water vapor. The differences between models and satellite observations and the spread across the models are reduced. In addition, we find that the models' equilibrium climate sensitivity (ECS) is correlated with overall performance scores for both CMIP5 and CMIP6 models, with a weaker correlation in CMIP6, suggesting that the models that capture better tropical clouds and water vapor distributions tend to have higher ECS. The physical processes responsible for the apparent correlation between ECS and model performance score warrant further study. Plain Language Summary: An improved understanding of Earth's climate requires realistic climate model simulations. Currently there are more than 20 climate models in use around the world that form the basis of the Intergovernmental Panel on Climate Change (IPCC) assessments report. One of the largest uncertainties in climate change projections arise from how the models handle the complex feedback mechanisms of clouds and water vapor. Using satellite observations, we made detailed and quantitative evaluation of cloud and water vapor structures from the latest versions of the climate models and their predecessors. Our analyses reveal that the latest models are measurably improved over their predecessors. Individual models were graded based on their performance in simulating clouds and water vapor. The analyses find that the models with better performance also tend to simulate higher surface temperature increase in response to a doubling of CO2 . Key Points: We use satellite data to assess the representation of clouds and water vapor structures in 28 climate models that participate in the CMIP6 We find measurable improvements in CMIP6 models relative to CMIP5 models for both clouds and water vapor In addition, we find that the models' equilibrium climate sensitivity is positively correlated with overall performance scores for the models