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

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

doi:10.3402/tellusa.v57i3.14668

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

Tellus

Volume 57 (2005): Issue 3

By: Andrew P. Morse, Francisco J. Doblas-Reyes, Moshe B. Hoshen, Renate Hagedorn and Tim N. Palmer

Open Access

|Jan 2005

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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Articles in this issue

DOI: https://doi.org/10.3402/tellusa.v57i3.14668 | Journal eISSN: 3035-9554

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Language: English

Page range: 464 - 475

Submitted on: Apr 2, 2004

Accepted on: Dec 2, 2004

Published on: Jan 1, 2005

Published by: Stockholm University Press

In partnership with: Paradigm Publishing Services

© 2005 Andrew P. Morse, Francisco J. Doblas-Reyes, Moshe B. Hoshen, Renate Hagedorn, Tim N. Palmer, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 57 (2005): Issue 3