The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2
The potential for multiyear prediction of impactful Earth system change remains relatively underexplored compared to shorter (subseasonal to seasonal) and longer (decadal) timescales. In this study, we introduce a new initialized prediction system using the Community Earth System Model version 2 (CE...
Published in: | Geoscientific Model Development |
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Online Access: | http://www.osti.gov/servlets/purl/1891495 https://www.osti.gov/biblio/1891495 https://doi.org/10.5194/gmd-15-6451-2022 |
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ftosti:oai:osti.gov:1891495 2023-07-30T04:06:46+02:00 The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 Yeager, Stephen G. Rosenbloom, Nan Glanville, Anne A. Wu, Xian Simpson, Isla Li, Hui Molina, Maria J. Krumhardt, Kristen Mogen, Samuel Lindsay, Keith Lombardozzi, Danica Wieder, Will Kim, Who M. Richter, Jadwiga H. Long, Matthew Danabasoglu, Gokhan Bailey, David Holland, Marika Lovenduski, Nicole Strand, Warren G. King, Teagan 2023-02-23 application/pdf http://www.osti.gov/servlets/purl/1891495 https://www.osti.gov/biblio/1891495 https://doi.org/10.5194/gmd-15-6451-2022 unknown http://www.osti.gov/servlets/purl/1891495 https://www.osti.gov/biblio/1891495 https://doi.org/10.5194/gmd-15-6451-2022 doi:10.5194/gmd-15-6451-2022 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.5194/gmd-15-6451-2022 2023-07-11T10:15:26Z The potential for multiyear prediction of impactful Earth system change remains relatively underexplored compared to shorter (subseasonal to seasonal) and longer (decadal) timescales. In this study, we introduce a new initialized prediction system using the Community Earth System Model version 2 (CESM2) that is specifically designed to probe potential and actual prediction skill at lead times ranging from 1 month out to 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of a collection of 2-year-long hindcast simulations, with four initializations per year from 1970 to 2019 and an ensemble size of 20. A full suite of output is available for exploring near-term predictability of all Earth system components represented in CESM2. We show that SMYLE skill for El Niño–Southern Oscillation is competitive with other prominent seasonal prediction systems, with correlations exceeding 0.5 beyond a lead time of 12 months. A broad overview of prediction skill reveals varying degrees of potential for useful multiyear predictions of seasonal anomalies in the atmosphere, ocean, land, and sea ice. The SMYLE dataset, experimental design, model, initial conditions, and associated analysis tools are all publicly available, providing a foundation for research on multiyear prediction of environmental change by the wider community. Other/Unknown Material Sea ice SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Geoscientific Model Development 15 16 6451 6493 |
institution |
Open Polar |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
spellingShingle |
54 ENVIRONMENTAL SCIENCES Yeager, Stephen G. Rosenbloom, Nan Glanville, Anne A. Wu, Xian Simpson, Isla Li, Hui Molina, Maria J. Krumhardt, Kristen Mogen, Samuel Lindsay, Keith Lombardozzi, Danica Wieder, Will Kim, Who M. Richter, Jadwiga H. Long, Matthew Danabasoglu, Gokhan Bailey, David Holland, Marika Lovenduski, Nicole Strand, Warren G. King, Teagan The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
The potential for multiyear prediction of impactful Earth system change remains relatively underexplored compared to shorter (subseasonal to seasonal) and longer (decadal) timescales. In this study, we introduce a new initialized prediction system using the Community Earth System Model version 2 (CESM2) that is specifically designed to probe potential and actual prediction skill at lead times ranging from 1 month out to 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of a collection of 2-year-long hindcast simulations, with four initializations per year from 1970 to 2019 and an ensemble size of 20. A full suite of output is available for exploring near-term predictability of all Earth system components represented in CESM2. We show that SMYLE skill for El Niño–Southern Oscillation is competitive with other prominent seasonal prediction systems, with correlations exceeding 0.5 beyond a lead time of 12 months. A broad overview of prediction skill reveals varying degrees of potential for useful multiyear predictions of seasonal anomalies in the atmosphere, ocean, land, and sea ice. The SMYLE dataset, experimental design, model, initial conditions, and associated analysis tools are all publicly available, providing a foundation for research on multiyear prediction of environmental change by the wider community. |
author |
Yeager, Stephen G. Rosenbloom, Nan Glanville, Anne A. Wu, Xian Simpson, Isla Li, Hui Molina, Maria J. Krumhardt, Kristen Mogen, Samuel Lindsay, Keith Lombardozzi, Danica Wieder, Will Kim, Who M. Richter, Jadwiga H. Long, Matthew Danabasoglu, Gokhan Bailey, David Holland, Marika Lovenduski, Nicole Strand, Warren G. King, Teagan |
author_facet |
Yeager, Stephen G. Rosenbloom, Nan Glanville, Anne A. Wu, Xian Simpson, Isla Li, Hui Molina, Maria J. Krumhardt, Kristen Mogen, Samuel Lindsay, Keith Lombardozzi, Danica Wieder, Will Kim, Who M. Richter, Jadwiga H. Long, Matthew Danabasoglu, Gokhan Bailey, David Holland, Marika Lovenduski, Nicole Strand, Warren G. King, Teagan |
author_sort |
Yeager, Stephen G. |
title |
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
title_short |
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
title_full |
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
title_fullStr |
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
title_full_unstemmed |
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2 |
title_sort |
seasonal-to-multiyear large ensemble (smyle) prediction system using the community earth system model version 2 |
publishDate |
2023 |
url |
http://www.osti.gov/servlets/purl/1891495 https://www.osti.gov/biblio/1891495 https://doi.org/10.5194/gmd-15-6451-2022 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
http://www.osti.gov/servlets/purl/1891495 https://www.osti.gov/biblio/1891495 https://doi.org/10.5194/gmd-15-6451-2022 doi:10.5194/gmd-15-6451-2022 |
op_doi |
https://doi.org/10.5194/gmd-15-6451-2022 |
container_title |
Geoscientific Model Development |
container_volume |
15 |
container_issue |
16 |
container_start_page |
6451 |
op_container_end_page |
6493 |
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1772819671800610816 |