Seasonal predictability of Kiremt rainfall in coupled general circulation models

The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June–September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions fro...

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Bibliographic Details
Main Authors: Stephanie Gleixner, Noel S Keenlyside, Teferi D Demissie, François Counillon, Yiguo Wang, Ellen Viste
Format: Article
Language:English
Published: IOP Publishing 2017-01-01
Series:Environmental Research Letters
Subjects:
Online Access:https://doi.org/10.1088/1748-9326/aa8cfa
Description
Summary:The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June–September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985–2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.
ISSN:1748-9326