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.
| Original language | English |
|---|---|
| Pages (from-to) | E462-E479 |
| Journal | Bulletin of the American Meteorological Society |
| Volume | 101 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2020 |
Funding
Portions of the work were performed at 1) Pacific Northwest National Laboratory (PNNL)—Battelle Memorial Institute operates PNNL under contract DEAC05-76RL01830, 2) Oak Ridge National Laboratory (ORNL)—UT-Battelle, LLC operates ORNL for the DOE under contract DE-AC05-00OR22725, 3) Brookhaven National Laboratory, and 4) the Jet Propulsion Laboratory and University of California, Los Angeles, with the latter two via subcontracts through PNNL. Computation has been provided by 1) the ARM Data Center Computing Facility, 2) the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC05-00OR22725, 3) the National Energy Research Scientific Computing Center, a DOE Office of Science user facility supported under Contract DE-AC02-05CH11231, and 4) PNNL Research Computing. Funding has been provided by the U.S. Department of Energy, Office of Science Biological and Environmental Research, via the Atmospheric Radiation Measurement facility. We acknowledge the advice from external members of the LASSO Advisory Team: Maike Ahlgrimm (Deutscher Wetterdienst), Chris Bretherton (University of Washington), Graham Feingold (NOAA ESRL), Chris Golaz (LLNL), David Turner (NOAA ESRL), Minghua Zhang (Stony Brook University), and James Mather (ARM Technical Director). We gratefully acknowledge the large number of ARM infrastructure team members outside of the authors that it takes to conduct an activity such as LASSO. People have contributed in multiple capacities as follows?for contributing new or custom-processed observations: David Turner, Laura Riihimaki, Tim Shippert, K. Sunny Lim, Virendra Ghate, Jonathan Helmus, and Rob Newsom; for proving ECMWF-based forcing data: Maike Ahlgrimm; for processing of VARANAL forcing data: Shaocheng Xie and Shuaiqi Tang; for providing data archive plus computing software and hardware support: Robert Records, Michael Giansiracusa, Jitu Kumar, Lynn Ma, and Aifang Zhou; for management support and working on the SGP reconfiguration and computing facilities that enabled LASSO: James Mather, Jennifer Comstock, and Giri Prakash; and for communication support: Hanna Goss, Rolanda Jundt, Robert Stafford, and Stacy Larsen. Portions of the work were performed at 1) Pacific Northwest National Laboratory (PNNL)?Battelle Memorial Institute operates PNNL under contract DEAC05-76RL01830, 2) Oak Ridge National Laboratory (ORNL)?UT-Battelle, LLC operates ORNL for the DOE under contract DE-AC05-00OR22725, 3) Brookhaven National Laboratory, and 4) the Jet Propulsion Laboratory and University of California, Los Angeles, with the latter two via subcontracts through PNNL. Computation has been provided by 1) the ARM Data Center Computing Facility, 2) the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC05-00OR22725, 3) the National Energy Research Scientific Computing Center, a DOE Office of Science user facility supported under Contract DE-AC02-05CH11231, and 4) PNNL Research Computing. Acknowledgments. Funding has been provided by the U.S. Department of Energy, Office of Science Biological and Environmental Research, via the Atmospheric Radiation Measurement facility. We acknowledge the advice from external members of the LASSO Advisory Team: Maike Ahlgrimm (Deutscher Wetterdienst), Chris Bretherton (University of Washington), Graham Feingold (NOAA ESRL), Chris Golaz (LLNL), David Turner (NOAA ESRL), Minghua Zhang (Stony Brook University), and James Mather (ARM Technical Director).