Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

Philip E. Bett Met Office Hadley Centre, Exeter, United Kingdom

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Hazel E. Thornton Met Office Hadley Centre, Exeter, United Kingdom

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Julia F. Lockwood Met Office Hadley Centre, Exeter, United Kingdom

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Adam A. Scaife Met Office Hadley Centre, and College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom

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Nicola Golding Met Office Hadley Centre, Exeter, United Kingdom

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Chris Hewitt Met Office Hadley Centre, Exeter, United Kingdom

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Rong Zhu Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Peiqun Zhang Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Chaofan Li Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Abstract

The skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Niño–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an upward trend, is shown over much of China. The region around Beijing, however, retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of the results presented here will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Philip E. Bett, philip.bett@metoffice.gov.uk

Abstract

The skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Niño–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an upward trend, is shown over much of China. The region around Beijing, however, retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of the results presented here will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Philip E. Bett, philip.bett@metoffice.gov.uk
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