Repository snapshots for LASSO-CACTI overview paper

The following code repositories were used to generate the simulations, analyses, and plots presented in the LASSO-CACTI overview paper. This folder contains snapshots of the codes that reproduce the results, to the best of our knowledge. Some figures were developed further in software such as Adobe Illustrator to adjust line thicknesses, panel layout, and labeling; these edits maintained the scientific integrity of the plots. Questions can be addressed to lasso@arm.gov. LASSO-CACTI stands for the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation scenario for the US Department of Energy ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. CACTI occurred in the region of Córdoba, Argentina from late 2018 through early 2019. The paper associated with this data is in review as of November 2025: Gustafson, W. I., A. M. Vogelmann, S. E. Giangrande, M. M. Delgado, S. Endo, J. D. Rausch, E. K. Schuman, A. C. Varble, and H. Xiao, 2025: The LASSO-CACTI library of deep convection simulations for Córdoba, Argentina: Overview of mesoscale and large-eddy simulations. Earth Space Sci., in review. More information about LASSO-CACTI can be obtained from its online technical documentation at https://lasso-cacti-doc.arm.gov/latest/index.html. Contact: William I. Gustafson Jr. Principal Investigator for LASSO Pacific Northwest National Laboratory, lasso@arm.gov or william.gustafson@pnnl.gov Software repositories used for the paper Each repository is stored in a separate folder within the zip file for this DOI. The first line of each "repository block", below, provides the repository name and the folder name in which to find that repository. WRF-Hydro: wrf_hydro_nwm_publicRepository cloning location: https://github.com/NCAR/wrf_hydro_nwm_public.gitCode version: 5.1.2Repository tag: 5.1.2License: https://github.com/NCAR/wrf_hydro_nwm_public/blob/v5.1.2/LICENSE.txt Code to ingest ERA5-Land data into WRF-Hydro: wrfhydro_forcing_preparationRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/wrfhydro_forcing_preparation.gitRepository commit hash: d11c7ea90713499e91a902e07c82dd3795bbb55bLicense: BSD 3-Clause License LASSO-CACTI Modified Version of WRF Preprocessing System: lasso-wps-cactiRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/lasso-wps-cacti.gitRepository commit hash: a5ef10601dae7ec099009fa0af901d78ab53f655License: https://code.arm.gov/lasso/lasso-cacti/lasso-wrf-cacti/-/blob/main/LICENSE.txt LASSO-CACTI Modified Version of WRF model: lasso-wrf-cactiRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/lasso-wrf-cacti.gitRepository cohttps://code.arm.gov/lasso/lasso-cacti/lasso-wrf-cacti/-/blob/main/LICENSE.txtmmit hash: 3e761eacb32850fb656c6ee70dd317688c0bddc0License: https://code.arm.gov/lasso/lasso-cacti/lasso-wrf-cacti/-/blob/main/LICENSE.txt Code to subset WRF output files: subsetwrfRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/subsetwrf.gitRepository commit hash: 5221e0747f77dfd4c24bf592b3e42618214a73bcLicense: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code for Tb skill scoring for Meso simulations: cacti_post_proc_Tb_mesoRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/cacti_post_proc.gitRepository commit hash: acac2079e323a3e49745e31c381d839078580dbcLicense: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code for Tb skill scoring for LES simulations: cacti_post_proc_Tb_lesRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/cacti_post_proc.gitRepository commit hash: 4bd39632b71674276c74a9032300c6814526a68dLicense: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code for ETH skill scoring for Meso simulations: cacti_post_proc_eth_mesoRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/cacti_post_proc_eth.gitRepository commit hash: 2ff6d4d084c5e071029cc829cb1f51a78697b6d6License: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code for ETH skill scoring for LES simulations: cacti_post_proc_eth_lesRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/cacti_post_proc_eth.gitRepository commit hash: 98e32f544048f9110a75fe4deff4f97beba3a968License: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code for precipitation skill scoring: rain_stats_plotsRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/rain_stats_plots.gitRepository commit hash: 76c806dd0e7263d75da5c6ed65e0625c5482c031License: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Code to generate plots and analyses for this paper: cacti_overview_paperRepository cloning location: https://code.arm.gov/lasso/lasso-cacti/cacti_notebook_library.gitRepository commit hash: 27e46446cf8695f4eaa709083905d7a228c48fd5 (on branch cacti_overview_paper)License: This work is licensed under the Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Acknowledgements The authors thank participants of the LASSO Expansion Workshop held at the National Center of Atmospheric Research in May 2019 (Gustafson et al., 2019, http://www.arm.gov/publications/programdocs/doe-sc-arm-19-023.pdf), and in particular, the white paper authors that proposed the deep convection scenario that has evolved into LASSO-CACTI: Hugh Morrison, Ann Fridlind, Scott Giangrande, Adam Varble, Scott Collis, Zhe Feng, Daniel Hernandez-Deckers, Matthew Kumjian, Sonia Lasher-Trapp, Toshi Matsui, Mariko Oue, Glen Romine, Greg Thompson, Marcus van Lier-Walqui, and Guang Zhang. We also thank the dozens of ARM staff required to achieve LASSO-CACTI, without whom we would not be able to run and make available the LASSO-CACTI dataset. Portions of the work were performed at Pacific Northwest National Laboratory (PNNL). Battelle Memorial Institute operates PNNL under contract DEAC05-76RL01830, and at Brookhaven National Laboratory via a subcontract through PNNL. Brookhaven National Laboratory, Brookhaven Science Associates, LLC operates under contract DE-SC0012704 with the U.S. DOE. The Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Computing resources for LASSO simulations provided by the Atmospheric Radiation Measurement user facility with additional operational support from the Oak Ridge Leadership Computing Facility. Data provided by NSF-NCAR/EOL under the sponsorship of the National Science Foundation, https://data.eol.ucar.edu/. Generated using Copernicus Climate Change Service information. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains. SatCORPS data provided by the Satellite Cloud and Radiative Property Retrieval System team at NASA Langley Research Center. NOAA Geostationary Operational Environmental Satellites (GOES) 16 was accessed on 14 Jun 2024 from https://registry.opendata.aws/noaa-goes. A portion of this work used code generously provided by Brian Blaylock's GOES-2-go python package (https://github.com/blaylockbk/goes2go). The publisher by accepting the paper for publication acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this paper, or allow others to do so, for United States Government purposes.