Articles | Volume 15, issue 7
Geosci. Model Dev., 15, 2881–2916, 2022
https://doi.org/10.5194/gmd-15-2881-2022
Geosci. Model Dev., 15, 2881–2916, 2022
https://doi.org/10.5194/gmd-15-2881-2022
Development and technical paper
07 Apr 2022
Development and technical paper | 07 Apr 2022

Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

Po-Lun Ma et al.

Data sets

Model simulation data P.-L. Ma https://portal.nersc.gov/archive/home/p/plma/www/eamv1_tunings

ERA5 monthly averaged data on pressure levels from 1979 to present H. Hersbach, B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, C. Peubey, R. Radu, I. Rozum, D. Schepers, A. Simmons, C. Soci, D. Dee, and J.-N. Thépaut https://doi.org/10.24381/cds.6860a573

Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product (https://ceres-tool.larc.nasa.gov/ord-tool/jsp/EBAFTOA41Selection.jsp) Norman G. Loeb, David R. Doelling, Hailan Wang, Wenying Su, Cathy Nguyen, Joseph G. Corbett, Lusheng Liang, Cristian Mitrescu, Fred G. Rose, and Seiji Kato https://doi.org/10.1175/jcli-d-17-0208.1

The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation (https://psl.noaa.gov/data/gridded/data.gpcp.html) Robert F. Adler, Mathew R. P. Sapiano, George J. Huffman, Jian-Jian Wang, Guojun Gu, David Bolvin, Long Chiu, Udo Schneider, Andreas Becker, Eric Nelkin, Pingping Xie, Ralph Ferraro, and Dong-Bin Shin https://doi.org/10.3390/atmos9040138

Giovanni NASA https://giovanni.gsfc.nasa.gov/giovanni/

GES DISC NASA https://disc.gsfc.nasa.gov/

CFMIP Observations for Model evaluation S. Bony, H. Chepfer, M. Chiriaco, J.-L. Dufresne, S. Klein, N. Loeb, R. Marchand, R. Pincus, D. Tanré, M. Webb, D. Winker, S. Xie, and Y. Zhang https://climserv.ipsl.polytechnique.fr/cfmip-obs/

Scripts for E3SM_diags used for Ma et al model calibration P.-L Ma https://doi.org/10.5281/zenodo.5555094

Model code and software

Energy Exascale Earth System Model v1.0 E3SM Project, DOE https://doi.org/10.11578/E3SM/dc.20180418.36

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Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.