Initialized near-term regional climate change prediction

F. J. Doblas-Reyes (), I. Andreu-Burillo, Y. Chikamoto, J. García-Serrano, V. Guemas, M. Kimoto, T. Mochizuki, L. R. L. Rodrigues and G. J. van Oldenborgh
Additional contact information
F. J. Doblas-Reyes: Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010
I. Andreu-Burillo: Institut Català de Ciències del Clima (IC3)
Y. Chikamoto: International Pacific Research Center (IPRC), University of Hawaii
J. García-Serrano: Institut Català de Ciències del Clima (IC3)
V. Guemas: Institut Català de Ciències del Clima (IC3)
M. Kimoto: Atmosphere and Ocean Research Institute (AORI), University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan
T. Mochizuki: Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showa-machi Kanazawa-ku, Yokohama 236-0001, Japan
L. R. L. Rodrigues: Institut Català de Ciències del Clima (IC3)
G. J. van Oldenborgh: Koninklijk Nederlands Meteorologisch Instituut (KNMI), P.O. 201, De Bilt 3730 AE, The Netherlands

Nature Communications, 2013, vol. 4, issue 1, 1-9

Abstract: Abstract Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth’s temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions.

Date: 2013
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DOI: 10.1038/ncomms2704

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