Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model
Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processin...
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ftcopernicus:oai:publications.copernicus.org:gmd107577 2023-06-18T03:42:59+02:00 Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model Sakaguchi, Koichi Leung, L. Ruby Zarzycki, Colin M. Jang, Jihyeon McGinnis, Seth Harrop, Bryce E. Skamarock, William C. Gettelman, Andrew Zhao, Chun Gutowski, William J. Leak, Stephen Mearns, Linda 2023-06-01 application/pdf https://doi.org/10.5194/gmd-16-3029-2023 https://gmd.copernicus.org/articles/16/3029/2023/ eng eng doi:10.5194/gmd-16-3029-2023 https://gmd.copernicus.org/articles/16/3029/2023/ eISSN: 1991-9603 Text 2023 ftcopernicus https://doi.org/10.5194/gmd-16-3029-2023 2023-06-05T16:24:03Z Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, ... Text Sea ice Copernicus Publications: E-Journals Geoscientific Model Development 16 10 3029 3081 |
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Open Polar |
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Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
description |
Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, ... |
format |
Text |
author |
Sakaguchi, Koichi Leung, L. Ruby Zarzycki, Colin M. Jang, Jihyeon McGinnis, Seth Harrop, Bryce E. Skamarock, William C. Gettelman, Andrew Zhao, Chun Gutowski, William J. Leak, Stephen Mearns, Linda |
spellingShingle |
Sakaguchi, Koichi Leung, L. Ruby Zarzycki, Colin M. Jang, Jihyeon McGinnis, Seth Harrop, Bryce E. Skamarock, William C. Gettelman, Andrew Zhao, Chun Gutowski, William J. Leak, Stephen Mearns, Linda Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
author_facet |
Sakaguchi, Koichi Leung, L. Ruby Zarzycki, Colin M. Jang, Jihyeon McGinnis, Seth Harrop, Bryce E. Skamarock, William C. Gettelman, Andrew Zhao, Chun Gutowski, William J. Leak, Stephen Mearns, Linda |
author_sort |
Sakaguchi, Koichi |
title |
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
title_short |
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
title_full |
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
title_fullStr |
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
title_full_unstemmed |
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model |
title_sort |
technical descriptions of the experimental dynamical downscaling simulations over north america by the cam–mpas variable-resolution model |
publishDate |
2023 |
url |
https://doi.org/10.5194/gmd-16-3029-2023 https://gmd.copernicus.org/articles/16/3029/2023/ |
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Sea ice |
genre_facet |
Sea ice |
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eISSN: 1991-9603 |
op_relation |
doi:10.5194/gmd-16-3029-2023 https://gmd.copernicus.org/articles/16/3029/2023/ |
op_doi |
https://doi.org/10.5194/gmd-16-3029-2023 |
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Geoscientific Model Development |
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10 |
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3029 |
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3081 |
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