Journal
CLIMATE OF THE PAST
Volume 9, Issue 1, Pages 393-421Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/cp-9-393-2013
Keywords
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Funding
- FPU [AP2009-4061]
- ANR ESCARSEL grant
- [UCM-921407]
- [CGL2008-06558-C02-02/CLI]
- [CGL2011-29672-C02-02]
- [200800050083542]
- [200800050084028]
- [CGL2008-05968-C02-01]
- [ENAC-PTDC/AAC-CLI/103567/2008]
- Natural Environment Research Council [NE/G019819/1] Funding Source: researchfish
- NERC [NE/G019819/1] Funding Source: UKRI
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Understanding natural climate variability and its driving factors is crucial to assessing future climate change. Therefore, comparing proxy-based climate reconstructions with forcing factors as well as comparing these with paleo-climate model simulations is key to gaining insights into the relative roles of internal versus forced variability. A review of the state of modelling of the climate of the last millennium prior to the CMIP5-PMIP3 (Coupled Model Intercomparison Project Phase 5-Paleoclimate Modelling Intercomparison Project Phase 3) coordinated effort is presented and compared to the available temperature reconstructions. Simulations and reconstructions broadly agree on reproducing the major temperature changes and suggest an overall linear response to external forcing on multidecadal or longer timescales. Internal variability is found to have an important influence at hemispheric and global scales. The spatial distribution of simulated temperature changes during the transition from the Medieval Climate Anomaly to the Little Ice Age disagrees with that found in the reconstructions. Thus, either internal variability is a possible major player in shaping temperature changes through the millennium or the model simulations have problems realistically representing the response pattern to external forcing. A last millennium transient climate response (LMTCR) is defined to provide a quantitative framework for analysing the consistency between simulated and reconstructed climate. Beyond an overall agreement between simulated and reconstructed LMTCR ranges, this analysis is able to single out specific discrepancies between some reconstructions and the ensemble of simulations. The disagreement is found in the cases where the reconstructions show reduced covariability with external forcings or when they present high rates of temperature change.
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