High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections
The article of record as published may be found at https://agu.confex.com/agu/osm20/meetingapp.cgi/Paper/641925 Ocean Sciences Meeting 2020 The Arctic is one of the most challenging regions to model climate change due to its complexity, including the cryosphere, small scale processes and feedbacks c...
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ftnavalpschool:oai:calhoun.nps.edu:10945/66161 2024-06-09T07:42:17+00:00 High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections Maslowski, Wieslaw Osinski, Robert Lee, Younjoo Kinney, Jaclyn L. Clement Craig, Anthony Seefeldt, Mark W. Cassano, John J. Nijssen, Bart Naval Postgraduate School (U.S.) Oceanography 2020-02 2 p. application/pdf https://hdl.handle.net/10945/66161 unknown EGU Maslowski, Wieslaw, et al. "High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections." Ocean Sciences Meeting 2020. AGU, 2020. PC42A-03 https://hdl.handle.net/10945/66161 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Abstract 2020 ftnavalpschool 2024-05-15T00:20:53Z The article of record as published may be found at https://agu.confex.com/agu/osm20/meetingapp.cgi/Paper/641925 Ocean Sciences Meeting 2020 The Arctic is one of the most challenging regions to model climate change due to its complexity, including the cryosphere, small scale processes and feedbacks controlling its amplified response to global climate change. The combination of these factors defines the need for high spatial and temporal model resolution, which is commonly not practical for most state-of-the-art global Earth system models (ESMs), including those participating in the Coupled Model Intercomparison Project Phase 6. We offer an alternative approach to improve model physics and reduce uncertainties in modeling Arctic climate using a high resolution regional climate system model for dynamical downscaling of output from ESMs. The Regional Arctic System Model (RASM) has been developed to better understand the past and present operation of the Arctic climate system and to predict its change at time scales up to decades. RASM is a coupled model, consisting of the atmosphere, ocean, sea ice, land hydrology and river routing scheme components. Its domain is pan-Arctic, with 50-km or 25-km grids for the atmosphere and land components. The ocean and sea ice components are configured at ~9.3-km or ~2.4-km grids horizontally and with 45 or 60 vertical layers. For hindcast simulations, RASM derives boundary conditions from global atmospheric reanalyses, allowing comparison with observations in place and time, which is a unique capability not available with ESMs. We will discuss improvements to RASM model physics offered by high resolution and in generation of internally consistent realistic initial conditions for Arctic climate prediction. We will also discuss the need for fine-tuning of scale aware parameterizations of sub-grid physical processes in varying model configurations. Finally, selected results will be presented to demonstrate gains of dynamical downscaling in comparison with observations and with ... Article in Journal/Newspaper Arctic Arctic Climate change Sea ice Naval Postgraduate School: Calhoun Arctic |
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Open Polar |
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Naval Postgraduate School: Calhoun |
op_collection_id |
ftnavalpschool |
language |
unknown |
description |
The article of record as published may be found at https://agu.confex.com/agu/osm20/meetingapp.cgi/Paper/641925 Ocean Sciences Meeting 2020 The Arctic is one of the most challenging regions to model climate change due to its complexity, including the cryosphere, small scale processes and feedbacks controlling its amplified response to global climate change. The combination of these factors defines the need for high spatial and temporal model resolution, which is commonly not practical for most state-of-the-art global Earth system models (ESMs), including those participating in the Coupled Model Intercomparison Project Phase 6. We offer an alternative approach to improve model physics and reduce uncertainties in modeling Arctic climate using a high resolution regional climate system model for dynamical downscaling of output from ESMs. The Regional Arctic System Model (RASM) has been developed to better understand the past and present operation of the Arctic climate system and to predict its change at time scales up to decades. RASM is a coupled model, consisting of the atmosphere, ocean, sea ice, land hydrology and river routing scheme components. Its domain is pan-Arctic, with 50-km or 25-km grids for the atmosphere and land components. The ocean and sea ice components are configured at ~9.3-km or ~2.4-km grids horizontally and with 45 or 60 vertical layers. For hindcast simulations, RASM derives boundary conditions from global atmospheric reanalyses, allowing comparison with observations in place and time, which is a unique capability not available with ESMs. We will discuss improvements to RASM model physics offered by high resolution and in generation of internally consistent realistic initial conditions for Arctic climate prediction. We will also discuss the need for fine-tuning of scale aware parameterizations of sub-grid physical processes in varying model configurations. Finally, selected results will be presented to demonstrate gains of dynamical downscaling in comparison with observations and with ... |
author2 |
Naval Postgraduate School (U.S.) Oceanography |
format |
Article in Journal/Newspaper |
author |
Maslowski, Wieslaw Osinski, Robert Lee, Younjoo Kinney, Jaclyn L. Clement Craig, Anthony Seefeldt, Mark W. Cassano, John J. Nijssen, Bart |
spellingShingle |
Maslowski, Wieslaw Osinski, Robert Lee, Younjoo Kinney, Jaclyn L. Clement Craig, Anthony Seefeldt, Mark W. Cassano, John J. Nijssen, Bart High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
author_facet |
Maslowski, Wieslaw Osinski, Robert Lee, Younjoo Kinney, Jaclyn L. Clement Craig, Anthony Seefeldt, Mark W. Cassano, John J. Nijssen, Bart |
author_sort |
Maslowski, Wieslaw |
title |
High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
title_short |
High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
title_full |
High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
title_fullStr |
High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
title_full_unstemmed |
High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections |
title_sort |
high-resolution modeling of arctic climate using the regional arctic system model for dynamical downscaling of global climate model reanalyses and projections |
publisher |
EGU |
publishDate |
2020 |
url |
https://hdl.handle.net/10945/66161 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Climate change Sea ice |
genre_facet |
Arctic Arctic Climate change Sea ice |
op_relation |
Maslowski, Wieslaw, et al. "High-Resolution Modeling of Arctic Climate Using the Regional Arctic System Model for Dynamical Downscaling of Global Climate Model Reanalyses and Projections." Ocean Sciences Meeting 2020. AGU, 2020. PC42A-03 https://hdl.handle.net/10945/66161 |
op_rights |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. |
_version_ |
1801371175837761536 |