DOI: 10.1007/s00382-013-2001-8
Scopus记录号: 2-s2.0-84888237174
论文题名: Rainfall anomaly prediction using statistical downscaling in a multimodel superensemble over tropical South America
作者: Johnson B. ; Kumar V. ; Krishnamurti T.N.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2013
卷: 43, 期: 2017-07-08 起始页码: 1731
结束页码: 1752
语种: 英语
英文摘要: This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical downscaling along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric–ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of downscaling and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well. © 2013, Springer-Verlag (outside the USA). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/54998
Appears in Collections: 过去全球变化的重建
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作者单位: Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL, United States
Recommended Citation:
Johnson B.,Kumar V.,Krishnamurti T.N.. Rainfall anomaly prediction using statistical downscaling in a multimodel superensemble over tropical South America[J]. Climate Dynamics,2013-01-01,43(2017-07-08)