Evaluation of the CFSv2 CMIP5 decadal predictions

被引:0
|
作者
Rodrigo J. Bombardi
Jieshun Zhu
Lawrence Marx
Bohua Huang
Hua Chen
Jian Lu
Lakshmi Krishnamurthy
V. Krishnamurthy
Ioana Colfescu
James L. Kinter
Arun Kumar
Zeng-Zhen Hu
Shrinivas Moorthi
Patrick Tripp
Xingren Wu
Edwin K. Schneider
机构
[1] George Mason University,Department of Atmospheric, Oceanic, and Earth Sciences, College of Science
[2] Institute of Global Environment and Society,Center for Ocean
[3] National Centers for Environmental Prediction,Land
[4] Pacific Northwest National Laboratory,Atmosphere Studies
来源
Climate Dynamics | 2015年 / 44卷
关键词
Decadal forecast and prediction; Skill; Biases; CFSv2; CMIP5; Volcanic forcing;
D O I
暂无
中图分类号
学科分类号
摘要
Retrospective decadal forecasts were undertaken using the Climate Forecast System version 2 (CFSv2) as part of Coupled Model Intercomparison Project 5. Decadal forecasts were performed separately by the National Center for Environmental Prediction (NCEP) and by the Center for Ocean-Land-Atmosphere Studies (COLA), with the centers using two different analyses for the ocean initial conditions the NCEP Climate Forecast System Reanalysis (CFSR) and the NEMOVAR-COMBINE analysis. COLA also examined the sensitivity to the inclusion of forcing by specified volcanic aerosols. Biases in the CFSv2 for both sets of initial conditions include cold midlatitude sea surface temperatures, and rapid melting of sea ice associated with warm polar oceans. Forecasts from the NEMOVAR-COMBINE analysis showed strong weakening of the Atlantic Meridional Overturning Circulation (AMOC), eventually approaching the weaker AMOC associated with CFSR. The decadal forecasts showed high predictive skill over the Indian, the western Pacific, and the Atlantic Oceans and low skill over the central and eastern Pacific. The volcanic forcing shows only small regional differences in predictability of surface temperature at 2m (T2m) in comparison to forecasts without volcanic forcing, especially over the Indian Ocean. An ocean heat content (OHC) budget analysis showed that the OHC has substantial memory, indicating potential for the decadal predictability of T2m; however, the model has a systematic drift in global mean OHC. The results suggest that the reduction of model biases may be the most productive path towards improving the model’s decadal forecasts.
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页码:543 / 557
页数:14
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