Subseasonal Earth System Prediction with CESM2

Jadwiga H. Richter; Anne A. Glanville; James Edwards; Brian Kauffman; Nicholas A. Davis; Abigail Jaye; Hyemi Kim; Nicholas M. Pedatella; Lantao Sun; Judith Berner; Who M. Kim; Stephen G. Yeager; Gokhan Danabasoglu; Julie M. Caron; Keith W. Oleson

doi:10.1175/WAF-D-21-0163.1

Subseasonal Earth System Prediction with CESM2

Jadwiga H. Richter, Anne A. Glanville, James Edwards, Brian Kauffman, Nicholas A. Davis, Abigail Jaye, Hyemi Kim, Nicholas M. Pedatella, Lantao Sun, Judith Berner, Who M. Kim, Stephen G. Yeager, Gokhan Danabasoglu, Julie M. Caron, Keith W. Oleson

Department of Science Education

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available.

Original language	English
Pages (from-to)	797-815
Number of pages	19
Journal	Weather and Forecasting
Volume	37
Issue number	6
DOIs	https://doi.org/10.1175/WAF-D-21-0163.1
State	Published - Jun 2022

Bibliographical note

Funding Information:
This work was supported by the National Oceanic and Atmospheric Administration’s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project.

Funding Information:
Acknowledgments. This work was supported by the National Oceanic and Atmospheric Administration’s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project.

Publisher Copyright:
© 2022 American Meteorological Society.

Keywords

Forecast verification/skill
Forecasting
Seasonal forecasting

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1175/WAF-D-21-0163.1

Cite this

@article{103185d3a5af4a03a11d3d320ad4bc05,

title = "Subseasonal Earth System Prediction with CESM2",

abstract = "Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment{\textquoteright}s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available.",

keywords = "Forecast verification/skill, Forecasting, Seasonal forecasting",

author = "Richter, {Jadwiga H.} and Glanville, {Anne A.} and James Edwards and Brian Kauffman and Davis, {Nicholas A.} and Abigail Jaye and Hyemi Kim and Pedatella, {Nicholas M.} and Lantao Sun and Judith Berner and Kim, {Who M.} and Yeager, {Stephen G.} and Gokhan Danabasoglu and Caron, {Julie M.} and Oleson, {Keith W.}",

note = "Funding Information: This work was supported by the National Oceanic and Atmospheric Administration{\textquoteright}s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy{\textquoteright}s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project. Funding Information: Acknowledgments. This work was supported by the National Oceanic and Atmospheric Administration{\textquoteright}s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy{\textquoteright}s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project. Publisher Copyright: {\textcopyright} 2022 American Meteorological Society.",

year = "2022",

month = jun,

doi = "10.1175/WAF-D-21-0163.1",

language = "English",

volume = "37",

pages = "797--815",

journal = "Weather and Forecasting",

issn = "0882-8156",

publisher = "American Meteorological Society",

number = "6",

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TY - JOUR

T1 - Subseasonal Earth System Prediction with CESM2

AU - Richter, Jadwiga H.

AU - Glanville, Anne A.

AU - Edwards, James

AU - Kauffman, Brian

AU - Davis, Nicholas A.

AU - Jaye, Abigail

AU - Kim, Hyemi

AU - Pedatella, Nicholas M.

AU - Sun, Lantao

AU - Berner, Judith

AU - Kim, Who M.

AU - Yeager, Stephen G.

AU - Danabasoglu, Gokhan

AU - Caron, Julie M.

AU - Oleson, Keith W.

N1 - Funding Information: This work was supported by the National Oceanic and Atmospheric Administration’s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project. Funding Information: Acknowledgments. This work was supported by the National Oceanic and Atmospheric Administration’s Weather Program Office/Climate Test Bed Program, and by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) via NSF Interagency Agreement 1844590. Portions of this study were supported by the NOAA Office of Weather and Air Quality Research Programs (OWAQ) (Subseasonal to Seasonal) under Grant NA19OAR4590156. Computing and data storage resources, including the Cheyenne Supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. We thank the National Aeronautics and Space Administration (NASA) for making the FP-IT data available to us for this project. Publisher Copyright: © 2022 American Meteorological Society.

PY - 2022/6

Y1 - 2022/6

N2 - Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available.

AB - Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available.

KW - Forecast verification/skill

KW - Forecasting

KW - Seasonal forecasting

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DO - 10.1175/WAF-D-21-0163.1

M3 - Article

AN - SCOPUS:85131348695

SN - 0882-8156

VL - 37

SP - 797

EP - 815

JO - Weather and Forecasting

JF - Weather and Forecasting

IS - 6

ER -

Subseasonal Earth System Prediction with CESM2

Abstract

Bibliographical note

Keywords

UN SDGs

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