Expanding LASSO to Simulate CACTI Deep Convection
Authors
William I. Gustafson — Pacific Northwest National Laboratory
Andrew M. Vogelmann — Brookhaven National Laboratory
Zhijin Li — University of California
Kyle K Dumas — Oak Ridge National Laboratory
Satoshi Endo — Brookhaven National Laboratory
Tami Fairless — Pacific Northwest National Laboratory
Michael Giansiracusa — Oak Ridge National Laboratory
Karen Lee Johnson — Brookhaven National Laboratory
Hugh Clifton Morrison — University Corporation for Atmospheric Research
Adam Varble — Pacific Northwest National Laboratory
Heng Xiao — Pacific Northwest National Laboratory
Category
Convective clouds, including aerosol interactions
Description
The Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity has focused on shallow convection to date. Now, LASSO is expanding to simulate deep convection during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. This new scenario is currently under development with a science focus on deep convective initiation and upscale growth. Soon, the overall approach and model configuration will need to be finalized to enable production simulations to begin.
This poster summarizes the planned approach for the deep convection scenario. The science drivers imply high-resolution should be used to identify moist convective thermals and how they interact as deep convection develops. Expectations are for 100 m grid spacing with domains that will vary to best capture the storm events for each case. Because of the increased cost of the deep convection LES, a smaller number of cases will be simulated combined with smaller ensembles than used for shallow convection. Observations will increasingly draw from radar and other remote sensing retrievals, which will require a different approach for the data bundles used to package the scenario output.
Stop by this poster to provide your input on how you would use these simulations. How would particular model configurations be most useful for your research? What frequency of model output would you need? What observations would you find helpful to have packaged with the model output? Help make LASSO useful for you!
Lead PI
William I. Gustafson — Pacific Northwest National Laboratory