Skilful interannual climate prediction from two large initialised model ensembles

Nick Dunstone; Doug Smith; Steve Yeager; Gokhan Danabasoglu; Paul Arthur Monerie; Leon Hermanson; Rosie Eade; Sarah Ineson; Jon Robson; Adam Scaife; Hong Li Ren

doi:10.1088/1748-9326/ab9f7d

Skilful interannual climate prediction from two large initialised model ensembles

Nick Dunstone, Doug Smith, Steve Yeager, Gokhan Danabasoglu, Paul Arthur Monerie, Leon Hermanson, Rosie Eade, Sarah Ineson, Jon Robson, Adam Scaife, Hong Li Ren

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

Climate prediction skill on the interannual timescale, which sits between that of seasonal and decadal, is investigated using large ensembles from the Met Office and CESM initialised coupled prediction systems. A key goal is to determine what can be skillfully predicted about the coming year when combining these two ensembles together. Annual surface temperature predictions show good skill at both global and regional scales, but skill diminishes when the trend associated with global warming is removed. Skill for the extended boreal summer (months 7-11) and winter (months 12-16) seasons are examined, focusing on circulation and rainfall predictions. Skill in predicting rainfall in tropical monsoon regions is found to be significant for the majority of regions examined. Skill increases for all regions when active ENSO seasons are forecast. There is some regional skill for predicting extratropical circulation, but predictive signals appear to be spuriously weak.

Original language	English
Article number	094083
Journal	Environmental Research Letters
Volume	15
Issue number	9
DOIs	https://doi.org/10.1088/1748-9326/ab9f7d
State	Published - Sep 2020

Keywords

climate prediction
global temperature
interannual
large ensemble
monsoon prediction

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10.1088/1748-9326/ab9f7d

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title = "Skilful interannual climate prediction from two large initialised model ensembles",

abstract = "Climate prediction skill on the interannual timescale, which sits between that of seasonal and decadal, is investigated using large ensembles from the Met Office and CESM initialised coupled prediction systems. A key goal is to determine what can be skillfully predicted about the coming year when combining these two ensembles together. Annual surface temperature predictions show good skill at both global and regional scales, but skill diminishes when the trend associated with global warming is removed. Skill for the extended boreal summer (months 7-11) and winter (months 12-16) seasons are examined, focusing on circulation and rainfall predictions. Skill in predicting rainfall in tropical monsoon regions is found to be significant for the majority of regions examined. Skill increases for all regions when active ENSO seasons are forecast. There is some regional skill for predicting extratropical circulation, but predictive signals appear to be spuriously weak.",

keywords = "climate prediction, global temperature, interannual, large ensemble, monsoon prediction",

author = "Nick Dunstone and Doug Smith and Steve Yeager and Gokhan Danabasoglu and Monerie, \{Paul Arthur\} and Leon Hermanson and Rosie Eade and Sarah Ineson and Jon Robson and Adam Scaife and Ren, \{Hong Li\}",

note = "Publisher Copyright: {\textcopyright} 2020 Crown copyright. Reproduced with the permission of the Controller of Her Majesty's Stationery Office.",

year = "2020",

month = sep,

doi = "10.1088/1748-9326/ab9f7d",

language = "English",

volume = "15",

journal = "Environmental Research Letters",

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T1 - Skilful interannual climate prediction from two large initialised model ensembles

AU - Dunstone, Nick

AU - Smith, Doug

AU - Yeager, Steve

AU - Danabasoglu, Gokhan

AU - Monerie, Paul Arthur

AU - Hermanson, Leon

AU - Eade, Rosie

AU - Ineson, Sarah

AU - Robson, Jon

AU - Scaife, Adam

AU - Ren, Hong Li

PY - 2020/9

Y1 - 2020/9

N2 - Climate prediction skill on the interannual timescale, which sits between that of seasonal and decadal, is investigated using large ensembles from the Met Office and CESM initialised coupled prediction systems. A key goal is to determine what can be skillfully predicted about the coming year when combining these two ensembles together. Annual surface temperature predictions show good skill at both global and regional scales, but skill diminishes when the trend associated with global warming is removed. Skill for the extended boreal summer (months 7-11) and winter (months 12-16) seasons are examined, focusing on circulation and rainfall predictions. Skill in predicting rainfall in tropical monsoon regions is found to be significant for the majority of regions examined. Skill increases for all regions when active ENSO seasons are forecast. There is some regional skill for predicting extratropical circulation, but predictive signals appear to be spuriously weak.

AB - Climate prediction skill on the interannual timescale, which sits between that of seasonal and decadal, is investigated using large ensembles from the Met Office and CESM initialised coupled prediction systems. A key goal is to determine what can be skillfully predicted about the coming year when combining these two ensembles together. Annual surface temperature predictions show good skill at both global and regional scales, but skill diminishes when the trend associated with global warming is removed. Skill for the extended boreal summer (months 7-11) and winter (months 12-16) seasons are examined, focusing on circulation and rainfall predictions. Skill in predicting rainfall in tropical monsoon regions is found to be significant for the majority of regions examined. Skill increases for all regions when active ENSO seasons are forecast. There is some regional skill for predicting extratropical circulation, but predictive signals appear to be spuriously weak.

KW - climate prediction

KW - global temperature

KW - interannual

KW - large ensemble

KW - monsoon prediction

UR - https://www.scopus.com/pages/publications/85091628173

U2 - 10.1088/1748-9326/ab9f7d

DO - 10.1088/1748-9326/ab9f7d

M3 - Article

AN - SCOPUS:85091628173

SN - 1748-9318

VL - 15

JO - Environmental Research Letters

JF - Environmental Research Letters

IS - 9

M1 - 094083

ER -

Skilful interannual climate prediction from two large initialised model ensembles

Abstract

Keywords

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