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This study presents a new simple approach for combining empirical with raw (i.e., not bias corrected) coupled model ensemble forecasts in order to make more skillful interval forecasts of ENSO. A Bayesian normal model has been used to combine empirical and raw coupled model December SST Niño-3.4 index forecasts started at the end of the preceding July(More)
This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based(More)
This study investigates likely changes in mean and extreme precipitation over southern Africa in response to changes in radiative forcing using an ensemble of global climate models prepared for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Extreme seasonal precipitation is defined in terms of 10-yr return levels(More)
This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: (i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and (ii) a multimodel system composed of three(More)
This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow(More)
Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model(More)
The seasonal predictability of cold spring seasons (March-April-May) in Europe from hindcasts/forecasts of three operational coupled general circulation models (CGCMs) is investigated. The models used in the investigation are the UKMO GloSea, ECMWF S2 and the NCEP-CFS. Using the relative operating characteristic score and the Brier skill score the long-term(More)
This study investigates likely changes in seasonal precipitation extremes in southern Africa in response to changes in radiative forcing using an ensemble of global climate models prepared for the IPCC Fourth Assessment Report (AR4). Changes in mean summer precipitation rates are investigated and compared with changes in extremes. Extreme seasonal(More)
This study addresses seasonal predictability of South American rainfall during ENSO. The skill of empirical and coupled multi-model predictions is assessed and compared. The empirical model uses the previous season August-September-October Pacific and Atlantic sea surface temperatures as predictors for December-January-February rainfall. Coupled multi-model(More)
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