U.S. Department of EnergyOffice of Scientific and Technical Information
Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation
Abstract
Surface-related model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the variables in these files at the surface and sub-surface levels.
- Authors:
-
- ORNL
- Publication Date:
- DOE Contract Number:
- AC05-00OR22725
- Research Org.:
- Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Collaborations:
- PNNL, BNL, ANL, ORNL
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Argentina; CACTI; LASSO; LASSO-CACTI; LES; Sierras de Córdoba; WRF; Weather Research and Forecasting; atmospheric model; complex terrain; cumulonimbus; deep convection; large eddy simulation; large-eddy simulation; mesoscale ensemble
- OSTI Identifier:
- 1905835
- DOI:
- https://doi.org/10.5439/1905835
Citation Formats
Gustafson, William, Vogelmann, Andrew, Delgado, Mark, Endo, Satoshi, Schuman, Eddie, Toto, Tami, Varble, Adam, and Xiao, Heng. Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation. United States: N. p., 2023.
Web. doi:10.5439/1905835.
Gustafson, William, Vogelmann, Andrew, Delgado, Mark, Endo, Satoshi, Schuman, Eddie, Toto, Tami, Varble, Adam, & Xiao, Heng. Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation. United States. doi:https://doi.org/10.5439/1905835
Gustafson, William, Vogelmann, Andrew, Delgado, Mark, Endo, Satoshi, Schuman, Eddie, Toto, Tami, Varble, Adam, and Xiao, Heng. 2023.
"Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation". United States. doi:https://doi.org/10.5439/1905835. https://www.osti.gov/servlets/purl/1905835. Pub date:Wed Jul 12 04:00:00 UTC 2023
@article{osti_1905835,
title = {Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation},
author = {Gustafson, William and Vogelmann, Andrew and Delgado, Mark and Endo, Satoshi and Schuman, Eddie and Toto, Tami and Varble, Adam and Xiao, Heng},
abstractNote = {Surface-related model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the variables in these files at the surface and sub-surface levels.},
doi = {10.5439/1905835},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jul 12 04:00:00 UTC 2023},
month = {Wed Jul 12 04:00:00 UTC 2023}
}