Multimodel Ensemble Forecasts for Weather and Seasonal Climate

Krishnamurti, TN and Kishtawal, CM and Zhang, Zhan and LaRow, Timothy and Bachiochi, David and Williford, Eric and Gadgil, Sulochana and Surendran, Sajani (2000) Multimodel Ensemble Forecasts for Weather and Seasonal Climate. In: Journal of Climate, 13 (23). pp. 4196-4216.

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Abstract

In this paper the performance of a multimodel ensemble forecast analysis that shows superior forecast skills is illustrated and compared to all individual models used. The model comparisons include global weather, hurricane track and intensity forecasts, and seasonal climate simulations. The performance improvements are completely attributed to the collective information of all models used in the statistical algorithm. The proposed concept is first illustrated for a low-order spectral model from which the multimodels and a "nature run" were constructed. Two hundred time units are divided into a training period (70 time units) and a forecast period (130 time units). The multimodel forecasts and the observed fields (the nature run) during the training period are subjected to a simple linear multiple regression to derive the statistical weights for the member models. The multimodal forecasts, generated for the next 130 forecast units, outperform all the individual models. This procedure was deployed for the multimodel forecasts of global weather, multiseasonal climate simulations, and hurricane track and intensity forecasts. For each type an improvement of the multimodel analysis is demonstrated and compared to the performance of the individual models. Seasonal and multiseasonal simulations demonstrate a major success of this approach for the atmospheric general circulation models where the sea surface temperatures and the sea ice are prescribed. In many instances, a major improvement in skill over the best models is noted.

Item Type:	Journal Article
Publication:	Journal of Climate
Publisher:	American Meteorological Society
Additional Information:	Copyright belongs to American Meteorological Society.
Department/Centre:	Division of Mechanical Sciences > Centre for Atmospheric & Oceanic Sciences
Date Deposited:	03 Jan 2005
Last Modified:	08 Jan 2013 05:16
URI:	http://eprints.iisc.ac.in/id/eprint/1669

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