Subseasonal prediction of Wintertime East Asian temperature based on atmospheric teleconnections

Changhyun Yoo; Nathaniel C. Johnson; Chueh Hsin Chang; Steven B. Feldstein; Young Ha Kim

doi:10.1175/JCLI-D-17-0811.1

Subseasonal prediction of Wintertime East Asian temperature based on atmospheric teleconnections

Changhyun Yoo, Nathaniel C. Johnson, Chueh Hsin Chang, Steven B. Feldstein, Young Ha Kim

Department of Climate and Energy Systems Engineering

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

13 Scopus citations

Abstract

A composite-based statistical model utilizing Northern Hemisphere teleconnection patterns is developed to predict East Asian wintertime surface air temperature for lead times out to 6 weeks. The level of prediction is determined by using the Heidke skill score. The prediction skill of the statistical model is compared with that of hindcast simulations by a climate model, Global Seasonal Forecast System, version 5. When employed individually, three teleconnections (i.e., the east Atlantic/western Russian, Scandinavian, and polar/Eurasian teleconnection patterns) are found to provide skillful predictions for lead times beyond 4-5 weeks. When information from the teleconnections and the long-term linear trend are combined, the statistical model outperforms the climate model for lead times beyond 3 weeks, especially during those times when the teleconnections are in their active phases.

Original language	English
Pages (from-to)	9351-9366
Number of pages	16
Journal	Journal of Climate
Volume	31
Issue number	22
DOIs	https://doi.org/10.1175/JCLI-D-17-0811.1
State	Published - 1 Nov 2018

Bibliographical note

Funding Information:
The authors thank Dr.Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015

Funding Information:
Acknowledgments. The authors thank Dr. Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015.

Publisher Copyright:
© 2018 American Meteorological Society.

Keywords

Statistical forecasting
Teleconnections

Access to Document

10.1175/JCLI-D-17-0811.1

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title = "Subseasonal prediction of Wintertime East Asian temperature based on atmospheric teleconnections",

abstract = "A composite-based statistical model utilizing Northern Hemisphere teleconnection patterns is developed to predict East Asian wintertime surface air temperature for lead times out to 6 weeks. The level of prediction is determined by using the Heidke skill score. The prediction skill of the statistical model is compared with that of hindcast simulations by a climate model, Global Seasonal Forecast System, version 5. When employed individually, three teleconnections (i.e., the east Atlantic/western Russian, Scandinavian, and polar/Eurasian teleconnection patterns) are found to provide skillful predictions for lead times beyond 4-5 weeks. When information from the teleconnections and the long-term linear trend are combined, the statistical model outperforms the climate model for lead times beyond 3 weeks, especially during those times when the teleconnections are in their active phases.",

keywords = "Statistical forecasting, Teleconnections",

author = "Changhyun Yoo and Johnson, {Nathaniel C.} and Chang, {Chueh Hsin} and Feldstein, {Steven B.} and Kim, {Young Ha}",

note = "Funding Information: The authors thank Dr.Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015 Funding Information: Acknowledgments. The authors thank Dr. Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015. Publisher Copyright: {\textcopyright} 2018 American Meteorological Society.",

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N1 - Funding Information: The authors thank Dr.Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015 Funding Information: Acknowledgments. The authors thank Dr. Byung-Kwon Park for making the GloSea5 hindcast experiments available for the study and two anonymous reviewers for their constructive comments. The authors also acknowledge the European Center for Medium-Range Weather Forecasts for providing the ERA-Interim reanalysis products via their data server. CY acknowledges the support of the Korea Polar Research Institute Grant PN17081. NCJ acknowledges the support from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce (Award NA14OAR4320106). C-H C is supported by the Ministry of Science and Technology Grant MOST 106-2111-M-002-003-MY2. SBF acknowledges the support of the National Science Foundation Grants AGS-1401220 and AGS-1822015. Publisher Copyright: © 2018 American Meteorological Society.

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N2 - A composite-based statistical model utilizing Northern Hemisphere teleconnection patterns is developed to predict East Asian wintertime surface air temperature for lead times out to 6 weeks. The level of prediction is determined by using the Heidke skill score. The prediction skill of the statistical model is compared with that of hindcast simulations by a climate model, Global Seasonal Forecast System, version 5. When employed individually, three teleconnections (i.e., the east Atlantic/western Russian, Scandinavian, and polar/Eurasian teleconnection patterns) are found to provide skillful predictions for lead times beyond 4-5 weeks. When information from the teleconnections and the long-term linear trend are combined, the statistical model outperforms the climate model for lead times beyond 3 weeks, especially during those times when the teleconnections are in their active phases.

AB - A composite-based statistical model utilizing Northern Hemisphere teleconnection patterns is developed to predict East Asian wintertime surface air temperature for lead times out to 6 weeks. The level of prediction is determined by using the Heidke skill score. The prediction skill of the statistical model is compared with that of hindcast simulations by a climate model, Global Seasonal Forecast System, version 5. When employed individually, three teleconnections (i.e., the east Atlantic/western Russian, Scandinavian, and polar/Eurasian teleconnection patterns) are found to provide skillful predictions for lead times beyond 4-5 weeks. When information from the teleconnections and the long-term linear trend are combined, the statistical model outperforms the climate model for lead times beyond 3 weeks, especially during those times when the teleconnections are in their active phases.

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JO - Journal of Climate

JF - Journal of Climate

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ER -

Subseasonal prediction of Wintertime East Asian temperature based on atmospheric teleconnections

Abstract

Bibliographical note

Keywords

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