Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 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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Main Authors: 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
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Language:English
Published: 2023
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Online Access:https://doi.org/10.5194/egusphere-2022-1199
https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1199/
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spelling ftcopernicus:oai:publications.copernicus.org:egusphere107577 2023-06-18T03:42:59+02:00 Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 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/egusphere-2022-1199 https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1199/ eng eng doi:10.5194/egusphere-2022-1199 https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1199/ eISSN: Text 2023 ftcopernicus https://doi.org/10.5194/egusphere-2022-1199 2023-06-05T16:24:05Z 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
institution Open Polar
collection 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 CAM5.4-MPAS4.0 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 CAM5.4-MPAS4.0 variable-resolution model
title_short Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 variable-resolution model
title_full Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 variable-resolution model
title_fullStr Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 variable-resolution model
title_full_unstemmed Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM5.4-MPAS4.0 variable-resolution model
title_sort technical descriptions of the experimental dynamical downscaling simulations over north america by the cam5.4-mpas4.0 variable-resolution model
publishDate 2023
url https://doi.org/10.5194/egusphere-2022-1199
https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1199/
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genre_facet Sea ice
op_source eISSN:
op_relation doi:10.5194/egusphere-2022-1199
https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1199/
op_doi https://doi.org/10.5194/egusphere-2022-1199
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