globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-16-0585.1
Scopus记录号: 2-s2.0-85017501880
论文题名:
Dynamical downscaling of SINTEX-F2v CGCM seasonal retrospective austral summer forecasts over Australia
作者: Ratnam J.V.; Doi T.; Behera S.K.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期:9
起始页码: 3219
结束页码: 3235
语种: 英语
Scopus关键词: Atmospheric temperature ; Forecasting ; Supercomputers ; Global circulation model ; Mixed layer ocean models ; Precipitation forecast ; Regional model ; Seasonal forecasting ; Temporal representations ; Vector supercomputers ; Weather research and forecasting models ; Weather forecasting
英文摘要: An ensemble of 1-month-lead seasonal retrospective forecasts generated by the Scale Interaction Experiment (SINTEX)-Frontier Research Center for Global Change (FRCGC), version 2 tuned for performance on a vector supercomputer (SINTEX-F2v), coupled global circulation model (CGCM) were downscaled using the Weather Research and Forecasting (WRF) Model to improve the forecast of the austral summer precipitation and 2-m air temperatures over Australia. A set of four experiments was carried out with the WRF Model to improve the forecasts. The first was to drive the WRF Model with the SINTEX-F2v output, and the second was to bias correct the mean component of the SINTEX-F2v forecast and drive the WRF Model with the corrected fields. The other experiments were to use the SINTEX-F2v forecasts and the mean bias-corrected SINTEX-F2v forecasts to drive the WRF Model coupled to a simple mixed layer ocean model. Evaluation of the forecasts revealed the WRF Model driven by bias-corrected SINTEX-F2v forecasts to have a better spatial and temporal representation of forecast precipitation and 2-m air temperature, compared to SINTEX-F2v forecasts. Using a regional coupled model with the bias-corrected SINTEX-F2v forecast as the driver further improved the skill of the precipitation forecasts. The improvement in the WRF Model forecasts is due to better representation of the variables in the bias-corrected SINTEX-F2v forecasts driving the WRF Model. The study brings out the importance of including air-sea interactions and correcting the global forecasts for systematic biases before downscaling them for societal applications over Australia. These results are important for potentially improving austral summer seasonal forecasts over Australia. © 2017 American Meteorological Society.
资助项目: JSPS, Japan Society for the Promotion of Science
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49667
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作者单位: Application Laboratory, JAMSTEC, Yokohama, Japan

Recommended Citation:
Ratnam J.V.,Doi T.,Behera S.K.. Dynamical downscaling of SINTEX-F2v CGCM seasonal retrospective austral summer forecasts over Australia[J]. Journal of Climate,2017-01-01,30(9)
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