%0 Journal Article %1 Bett2017Skill %A Bett, Philip E. %A Thornton, Hazel E. %A Lockwood, Julia F. %A Scaife, Adam A. %A Golding, Nicola %A Hewitt, Chris %A Zhu, Rong %A Zhang, Peiqun %A Li, Chaofan %D 2017 %I American Meteorological Society %J J. Appl. Meteor. Climatol. %K wind climateservices colleagues energy solar skill seasonal renewables reliability temperature verification China myown %N 11 %P 3099--3114 %R 10.1175/jamc-d-17-0070.1 %T Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector %U http://dx.doi.org/10.1175/jamc-d-17-0070.1 %V 56 %X We assess the skill and reliability of forecasts of winter and summer temperature, wind speed and irradiance over China, using the GloSea5 seasonal forecast system. 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. We find 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 skilfully forecast around the coast of the South China Sea, related to skilful forecasts of the El Niño?Southern Oscillation. Such information could improve seasonal estimates of offshore wind power generation. Similarly, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar power estimation. Much of China shows skill in summer temperatures, which derives from an upward trend. However, the region around Beijing retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of our results will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.

@article{Bett2017Skill, abstract = {We assess the skill and reliability of forecasts of winter and summer temperature, wind speed and irradiance over China, using the GloSea5 seasonal forecast system. 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. We find 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 skilfully forecast around the coast of the South China Sea, related to skilful forecasts of the El Ni\~{n}o?Southern Oscillation. Such information could improve seasonal estimates of offshore wind power generation. Similarly, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar power estimation. Much of China shows skill in summer temperatures, which derives from an upward trend. However, the region around Beijing retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of our results will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Bett, Philip E. and Thornton, Hazel E. and Lockwood, Julia F. and Scaife, Adam A. and Golding, Nicola and Hewitt, Chris and Zhu, Rong and Zhang, Peiqun and Li, Chaofan}, biburl = {https://www.bibsonomy.org/bibtex/225a035b02c5fc08963060ce612e661ba/pbett}, citeulike-article-id = {14421519}, citeulike-attachment-1 = {23ref_cssp_energyskill.pdf; /pdf/user/pbett/article/14421519/1123825/23ref_cssp_energyskill.pdf; a02d243144c54af10d8f5094bd0d3de332af78df}, citeulike-linkout-0 = {http://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-17-0070.1}, citeulike-linkout-1 = {http://dx.doi.org/10.1175/jamc-d-17-0070.1}, day = 29, doi = {10.1175/jamc-d-17-0070.1}, file = {23ref_cssp_energyskill.pdf}, interhash = {7a156556699dc617ff8f304558e7066f}, intrahash = {25a035b02c5fc08963060ce612e661ba}, journal = {J. Appl. Meteor. Climatol.}, keywords = {wind climateservices colleagues energy solar skill seasonal renewables reliability temperature verification China myown}, month = aug, number = 11, pages = {3099--3114}, posted-at = {2017-08-30 12:09:04}, priority = {2}, publisher = {American Meteorological Society}, timestamp = {2018-10-01T09:50:26.000+0200}, title = {Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector}, url = {http://dx.doi.org/10.1175/jamc-d-17-0070.1}, volume = 56, year = 2017 }