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.
%0 Journal Article
%1 Morse2011Forecast
%A Morse, Andrew P.
%A Doblas-Reyes, Francisco J.
%A Hoshen, Moshe B.
%A Hagedorn, Renate
%A Palmer, Tim N.
%D 2011
%J Tellus A
%K skill seasonal disease health
%R 10.3402/tellusa.v57i3.14668
%T A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model
%U http://dx.doi.org/10.3402/tellusa.v57i3.14668
%X 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.
@article{Morse2011Forecast,
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.},
added-at = {2018-06-18T21:23:34.000+0200},
author = {Morse, Andrew P. and Doblas-Reyes, Francisco J. and Hoshen, Moshe B. and Hagedorn, Renate and Palmer, Tim N.},
biburl = {https://www.bibsonomy.org/bibtex/2d115f86bca8b5b069354f51410cdbc41/pbett},
citeulike-article-id = {14223294},
citeulike-linkout-0 = {http://dx.doi.org/10.3402/tellusa.v57i3.14668},
comment = {(private-note)Uses DEMETER},
day = 30,
doi = {10.3402/tellusa.v57i3.14668},
interhash = {ac9d6d6e2a5bbd1959760efb662550a0},
intrahash = {d115f86bca8b5b069354f51410cdbc41},
issn = {1600-0870},
journal = {Tellus A},
keywords = {skill seasonal disease health},
month = dec,
posted-at = {2016-12-07 15:43:42},
priority = {2},
timestamp = {2018-06-22T18:36:38.000+0200},
title = {A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model},
url = {http://dx.doi.org/10.3402/tellusa.v57i3.14668},
year = 2011
}