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Publication Date
28 November 2019

Climate Model Climatology Controls Future Changes in Clouds and Relative Humidity

Subtitle
Accurate climate model representation of the current climate is important for reliable climate projections.
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Simulated and predicted changes in cloud fraction and relative humidity.
Science

Scientists at Lawrence Livermore National Laboratory in collaboration with colleagues at the Princeton University and NASA Langley demonstrated that they accurately predict a climate model’s simulated change in upper tropospheric clouds and relative humidity based solely on the model’s present-day distribution of clouds and relative humidity. 

Impact

The research finds that the present distribution of tropical upper tropospheric clouds and relative humidity are predictive of future changes, which means it may be possible to estimate future changes in these fields based on the observed climatology. The result also suggests that model biases in the present-day representation of clouds and relative humidity will lead to errors in the simulation of future cloud and humidity changes, emphasizing the need for realistic simulations of the historical climate.  

Summary

Several studies suggest that as the Earth warms, tropical upper tropospheric clouds and relative humidity should shift upwards with rising isotherms (lines of constant temperature). In the tropics, the vertical profile of warming is constrained by basic thermodynamics. Given these two principles, this study tests whether it is possible to predict changes in clouds and relative humidity by estimating the rise of isotherms (using a moist adiabat) and then shifting climate model’s climatological cloud and relative humidity field upwards so that they maintain a constant temperature. The authors show that this prediction is remarkably accurate and that model differences in future changes in upper tropospheric clouds and relative humidity stem from differences in their current representation of the climate.  

Point of Contact
Benjamin Santer
Institution(s)
Lawrence Livermore National Laboratory (LLNL)
Funding Program Area(s)
Publication