A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model | Tellus (original) (raw)

A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model

Original Research Papers

• Andrew P. Morse
• Francisco J. Doblas-Reyes
• Moshe B. Hoshen
• Renate Hagedorn
• Tim N. Palmer

Abstract

We discuss a novel three-tier hierarchical approach to the validation of an end-to-end seasonal climate forecast system. We present a malaria transmission simulation model (MTSM) driven with output from the DEMETER multi-model seasonal climate predictions, to produce probabilistic hindcasts of malaria prevalence. These prevalence hindcasts are second-tier validated against estimates from the MTSM driven with ERA-40 gridded analyses. The DEMETER’MTSM prevalence hindcasts are shown to be (tier-2) skilful for the one-month lead seasonal predictions as well as for the period covering the seasonal malaria peak with a 4–6 month forecast window for the event prevalence above the median. Interestingly, the tier-2 Brier skill score for the forecast window of the hindcasts starting in February, for the event prevalence above the median, is higher than for either the tier-1 precipitation or temperature forecasts, which were the MTSM driving variables.

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