Combining simulations and observations reveals the complexity of shallow clouds



Fast, Jerome D — Pacific Northwest National Laboratory

Area of research

Cloud Processes

Journal Reference

Huang M, H Xiao, M Wang, and J Fast. 2020. "Assessing CLUBB PDF closure assumptions for a continental shallow‐to‐deep convective transition case over multiple spatial scales." Journal of Advances in Modeling Earth Systems, 12(10), e2020ms002145, 10.1029/2020MS002145.


Shallow clouds play an important role in regulating energy and water transport in the lower atmosphere. But these shallow clouds are too small in size to be resolved at the resolutions of traditional global climate models. Global climate models rely on parameterizations, which are simple embedded models, to represent these clouds. This study found that the key assumptions used in a group of popular shallow cloud parameterizations are flawed. Discrepancies in representing the moisture variability near cloud tops and bases lead to biases in the modeled cloud properties. Increasing model resolution diminishes the impact of these discrepancies on the simulated clouds.


The results revealed the complexities of moisture and temperature variability within the shallow cloud layer. They pinpointed a challenge currently used parameterizations have in representing this variability in shallow clouds. This study also suggests these problems will persist in next-generation climate models that run at higher resolutions, although the biases will be less severe. For current-generation models running at lower resolutions, these parameterizations need modification to improve their performance.


Researchers analyzed a large-eddy simulation (LES) of a continental shallow-to-deep convection transition event observed during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign over the U.S. Department of Energy Atmospheric Radiation Measurement user facility's Southern Great Plains observatory. The results showed that the vertical structure of moisture and temperature variability in the shallow cloud layer is more complicated than what most shallow convection parameterizations can capture. Most parameterizations use assumptions that can only represent the variability associated with the active, mature cloud eddies that dominate the middle of the cloud layer. They fail to adequately capture the variability associated with the overshooting or decaying eddies that exist near the cloud base and top. Offline calculations of cloud properties using the assumed probability density functions used in the parameterizations and input from the LES show biases in the simulated shallow cloud properties that persist near the cloud base, but diminish near the cloud top with increasing horizontal resolution (from 100 km to 2 km).