Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these effor...

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Published in:Geoscientific Model Development
Main Authors: S. Tang, A. C. Varble, J. D. Fast, K. Zhang, P. Wu, X. Dong, F. Mei, M. Pekour, J. C. Hardin, P.-L. Ma
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
Online Access:https://doi.org/10.5194/gmd-16-6355-2023
https://doaj.org/article/bf55c6f152374f68a1f6376a5e04c8ac
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spelling ftdoajarticles:oai:doaj.org/article:bf55c6f152374f68a1f6376a5e04c8ac 2023-12-10T09:51:46+01:00 Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations S. Tang A. C. Varble J. D. Fast K. Zhang P. Wu X. Dong F. Mei M. Pekour J. C. Hardin P.-L. Ma 2023-11-01T00:00:00Z https://doi.org/10.5194/gmd-16-6355-2023 https://doaj.org/article/bf55c6f152374f68a1f6376a5e04c8ac EN eng Copernicus Publications https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-16-6355-2023 1991-959X 1991-9603 https://doaj.org/article/bf55c6f152374f68a1f6376a5e04c8ac Geoscientific Model Development, Vol 16, Pp 6355-6376 (2023) Geology QE1-996.5 article 2023 ftdoajarticles https://doi.org/10.5194/gmd-16-6355-2023 2023-11-12T01:38:42Z Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The ... Article in Journal/Newspaper North Atlantic Southern Ocean Directory of Open Access Journals: DOAJ Articles Pacific Southern Ocean Geoscientific Model Development 16 21 6355 6376
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Geology
QE1-996.5
spellingShingle Geology
QE1-996.5
S. Tang
A. C. Varble
J. D. Fast
K. Zhang
P. Wu
X. Dong
F. Mei
M. Pekour
J. C. Hardin
P.-L. Ma
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
topic_facet Geology
QE1-996.5
description Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The ...
format Article in Journal/Newspaper
author S. Tang
A. C. Varble
J. D. Fast
K. Zhang
P. Wu
X. Dong
F. Mei
M. Pekour
J. C. Hardin
P.-L. Ma
author_facet S. Tang
A. C. Varble
J. D. Fast
K. Zhang
P. Wu
X. Dong
F. Mei
M. Pekour
J. C. Hardin
P.-L. Ma
author_sort S. Tang
title Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
title_short Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
title_full Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
title_fullStr Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
title_full_unstemmed Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
title_sort earth system model aerosol–cloud diagnostics (esmac diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
publisher Copernicus Publications
publishDate 2023
url https://doi.org/10.5194/gmd-16-6355-2023
https://doaj.org/article/bf55c6f152374f68a1f6376a5e04c8ac
geographic Pacific
Southern Ocean
geographic_facet Pacific
Southern Ocean
genre North Atlantic
Southern Ocean
genre_facet North Atlantic
Southern Ocean
op_source Geoscientific Model Development, Vol 16, Pp 6355-6376 (2023)
op_relation https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf
https://doaj.org/toc/1991-959X
https://doaj.org/toc/1991-9603
doi:10.5194/gmd-16-6355-2023
1991-959X
1991-9603
https://doaj.org/article/bf55c6f152374f68a1f6376a5e04c8ac
op_doi https://doi.org/10.5194/gmd-16-6355-2023
container_title Geoscientific Model Development
container_volume 16
container_issue 21
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