The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection

Abstract

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.

Size dependence in chord characteristics from simulated and observed continental shallow cumulus

“…The clear scaling in vertical velocity below the clouds supports the use of multiple plumes with different sizes as originally proposed by Arakawa and Schubert (1974). Also in regards to parameterized plumes, that the moisture anomalies below the clouds are relatively small (1 %-2 %) indicates that initializing multiple plumes at the surface using the background moisture is justifiable (Park, 2014;Neggers, 2015;Hagos et al, 2018).…”

Linking Large‐Eddy Simulations to Local Cloud Observations

“…W. I. Gustafson et al, 2020). In this section, we will show that one advantage of the forcing at the open boundaries is a reduced dependency on the large-scale forcing.…”

“…van Laar et al, 2019; W. I. Gustafson et al, 2020). Such comparisons are difficult if the models exhibit large biases in the representation of the synoptic setting.…”

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

“…Measurements of the CFP are important to quantify the impact of shallow cumulus clouds on the grid-scale meteorological state, because the fractional cloudiness of a grid box has an impact on the radiative transfer (e.g., Albrecht, 1981;Larson et al, 2001) and the vertical cumulus mass flux (e.g., de Roode and Bretheton, 2003;van Stratum et al, 2014). Zenith-profiling cloud radar and lidar measurements traditionally have been used to provide CFP estimates (e.g., Hogan et al, 2001;Kollias et al, 2009;Remillard et al, 2013;Angevine et al, 2018). Typically, the profiling radar and lidar observations are combined synergistically to provide a hydrometeor mask such as those described in ARSCL (Clothiaux et al, 2000) and the CloudNet target classification (Illingworth et al, 2007).…”