Improved weather and seasonal climate forecasts from multimodel superensemble

被引：688
|
作者：
Krishnamurti, TN [1 ]
Kishtawal, CM
LaRow, TE
Bachiochi, DR
Zhang, Z
Williford, CE
Gadgil, S
Surendran, S
机构：
[1] Florida State Univ, Dept Meteorol, Tallahassee, FL 32306 USA
[2] Indian Inst Sci, Ctr Atmospher & Ocean Sci, Bangalore, Karnataka, India
来源：
SCIENCE | 1999年 / 285卷 / 5433期
关键词：
D O I：
10.1126/science.285.5433.1548
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A method for improving weather and climate forecast skill has been developed. It is called a superensemble, and it arose from a study of the statistical properties of a low-order spectral model. Multiple regression was used to determine coefficients from multimodel forecasts and observations. The coefficients were then used in the superensemble technique. The superensemble was shown to outperform all model forecasts for multiseasonal, medium-range weather and hurricane forecasts. In addition, the superensemble was shown to have higher skill than forecasts based solely on ensemble averaging.
引用
收藏
页码：1548 / 1550
页数：3
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