Resnick Fellow, Ignacio Lopez Gomez, is a member of a research team developing a mathematical model that represents clouds in climate models. The team's two recent publications, "A Generalized Mixing Length Closure for Eddy‐Diffusivity Mass‐Flux Schemes of Turbulence and Convection" and "Unified Entrainment and Detrainment Closures for Extended Eddy‐diffusivity Mass‐Flux Schemes", describe the mathematical model of the processes most strongly affecting cloud formation in the atmosphere: turbulence and convection. The papers show that the model will lead to more accurate simulations of clouds in climate models, which addresses one of the biggest sources of uncertainty in them.
We developed a mathematical model that represents clouds in climate models faithfully.
Significance and Impact
The leading source of uncertainty in climate projections can be traced back to the inability of climate models to represent clouds. Our model provides a way forward.
- The model is tested for stratocumulus, cumulus and cumulonimbus clouds. Weather and climate models struggle to correctly represent stratocumulus clouds, which are common off the coast of California, Peru and Namibia. In our study, we demonstrate the prediction accuracy of our proposed cloud model for this type of cloud.
- The model is time-dependent and captures the diurnal cycle of convection well. Climate models have important biases regarding the onset time of precipitation, which is related to the diurnal cycle of convection. Our model predictions show good agreement with high-fidelity numerical simulations.
Lopez‐Gomez, I., Cohen, Y., He, J., Jaruga, A., & Schneider, T. A generalized mixing length closure for eddy‐diffusivity mass‐flux schemes of turbulence and convection. Journal of Advances in Modeling Earth Systems (2000) 12, e2020MS002161. https://doi.org/10.1029/2020MS002161
Cohen, Y., Lopez‐Gomez, I., Jaruga, A., He, J., Kaul, C. M., & Schneider, T. Unified entrainment and detrainment closures for extended eddy‐diffusivity mass‐flux schemes. Journal of Advances in Modeling Earth Systems (2020) 12, e2020MS002162. https://doi.org/10.1029/2020MS002162
Contact: Tapio Schneider