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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Copernicus Publications
2023
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00069760 2023-12-10T09:51:47+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 Tang, Shuaiqi Varble, Adam C. Fast, Jerome D. Zhang, Kai Wu, Peng Dong, Xiquan Mei, Fan Pekour, Mikhail Hardin, Joseph C. Ma, Po-Lun 2023-11 electronic https://doi.org/10.5194/gmd-16-6355-2023 https://noa.gwlb.de/receive/cop_mods_00069760 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068131/gmd-16-6355-2023.pdf https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf eng eng Copernicus Publications Geoscientific Model Development -- http://www.bibliothek.uni-regensburg.de/ezeit/?2456725 -- http://www.geosci-model-dev.net/ -- 1991-9603 https://doi.org/10.5194/gmd-16-6355-2023 https://noa.gwlb.de/receive/cop_mods_00069760 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068131/gmd-16-6355-2023.pdf https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2023 ftnonlinearchiv https://doi.org/10.5194/gmd-16-6355-2023 2023-11-13T00:22:47Z 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 Niedersächsisches Online-Archiv NOA Southern Ocean Pacific Geoscientific Model Development 16 21 6355 6376 |
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article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Tang, Shuaiqi Varble, Adam C. Fast, Jerome D. Zhang, Kai Wu, Peng Dong, Xiquan Mei, Fan Pekour, Mikhail Hardin, Joseph C. Ma, Po-Lun 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 |
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article Verlagsveröffentlichung |
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 |
Tang, Shuaiqi Varble, Adam C. Fast, Jerome D. Zhang, Kai Wu, Peng Dong, Xiquan Mei, Fan Pekour, Mikhail Hardin, Joseph C. Ma, Po-Lun |
author_facet |
Tang, Shuaiqi Varble, Adam C. Fast, Jerome D. Zhang, Kai Wu, Peng Dong, Xiquan Mei, Fan Pekour, Mikhail Hardin, Joseph C. Ma, Po-Lun |
author_sort |
Tang, Shuaiqi |
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://noa.gwlb.de/receive/cop_mods_00069760 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068131/gmd-16-6355-2023.pdf https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf |
geographic |
Southern Ocean Pacific |
geographic_facet |
Southern Ocean Pacific |
genre |
North Atlantic Southern Ocean |
genre_facet |
North Atlantic Southern Ocean |
op_relation |
Geoscientific Model Development -- http://www.bibliothek.uni-regensburg.de/ezeit/?2456725 -- http://www.geosci-model-dev.net/ -- 1991-9603 https://doi.org/10.5194/gmd-16-6355-2023 https://noa.gwlb.de/receive/cop_mods_00069760 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068131/gmd-16-6355-2023.pdf https://gmd.copernicus.org/articles/16/6355/2023/gmd-16-6355-2023.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/gmd-16-6355-2023 |
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Geoscientific Model Development |
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16 |
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21 |
container_start_page |
6355 |
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6376 |
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