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2013 | OriginalPaper | Buchkapitel

Prediction from Weeks to Decades

verfasst von : Ben Kirtman, David Anderson, Gilbert Brunet, In-Sik Kang, Adam A. Scaife, Doug Smith

Erschienen in: Climate Science for Serving Society

Verlag: Springer Netherlands

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Abstract

This white paper is a synthesis of several recent workshops, reports and published literature on monthly to decadal climate prediction. The intent is to document: (i) the scientific basis for prediction from weeks to decades; (ii) current capabilities; and (iii) outstanding challenges. In terms of the scientific basis we described the various sources of predictability, e.g., the Madden Jullian Ocillation (MJO); Sudden Stratospheric Warmings; Annular Modes; El Niño and the Southern Oscillation (ENSO); Indian Ocean Dipole (IOD); Atlantic “Niño;” Atlantic gradient pattern; snow cover anomalies, soil moisture anomalies; sea-ice anomalies; Pacific Decadal Variability (PDV); Atlantic Multi-Decadal Variability (AMV); trend among others. Some of the outstanding challenges include how to evaluate and validate prediction systems, how to improve models and prediction systems (e.g., observations, data assimilation systems, ensemble strategies), the development of seamless prediction systems.

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Fußnoten
1
Arbitrarily small initial condition errors.
 
2
Here we define the prediction of climate anomalies as the prediction of statistics of weather (i.e., mean temperature or precipitation, variance, probability of extremes such as droughts, floods, hurricanes, high winds …).
 
3
In some of the literature a “prediction” corresponds to an initial value problem and the “projection” corresponds to a boundary forced problem. Here we recognize that decadal prediction and even seasonal prediction is a both an initial value and a boundary value problem. Throughout the text we refer to the combined initial value and boundary value problem as prediction problem.
 
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Metadaten
Titel
Prediction from Weeks to Decades
verfasst von
Ben Kirtman
David Anderson
Gilbert Brunet
In-Sik Kang
Adam A. Scaife
Doug Smith
Copyright-Jahr
2013
Verlag
Springer Netherlands
DOI
https://doi.org/10.1007/978-94-007-6692-1_8