DOE ARM LASSO Activity: Progress on ENA Maritime Cloud Scenario

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) activity has been developing a new scenario focused on maritime clouds at ARM’s Eastern North Atlantic (ENA) atmospheric observatory. LASSO employs high-resolution modeling to give context to ARM’s suite of observations, which is useful to link modelers to ARM observations, help with understanding connections between observations, and various other applications such as providing readily available model output for educational purposes. A “scenario” concept focuses sets of simulations around a scientific topic and location. The LASSO-ENA scenario is designed around maritime cloud organization and related precipitation processes at ENA.

A range of case dates have been examined for the new LASSO-ENA scenario to cover cloud regimes identified as open, closed, and transitioning. Preliminary simulations examine the sensitivity to forcing data using the System for Atmospheric Modeling (SAM) model. Biases for cloud fraction differ between the open and closed regimes, with a tendency for high and low biases, respectively. Simulations with the Predicting INteractions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) model are explored to identify how a nested downscaling domain configuration differs from using doubly periodic domain boundaries, as is done with SAM, for the three maritime cloud regimes. Both models employ an anelastic dynamical core, and thus benefit from the faster anelastic calculations than when using a fully compressible dynamical core.

Plans for the coming year include releasing batches of the ENA simulations to the public alongside simulation evaluations using ARM and satellite data. These will then form LASSO’s third scenario, which will complement the existing shallow-convection scenario at Oklahoma and the deep convection scenario at Argentina for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. More information is available on the ARM LASSO website, https://www.arm.gov/capabilities/modeling/lasso.