Detection and Attribution

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Abstract

We present a first assessment of the detection of a signal of temperature change over the Mediterranean domain, using HadCRUT3v observation dataset and model outputs from the CMIP3 climate simulations. For this study we have used two new formal detection methodologies, the ‘Regularized Optimal Fingerprint’ and the ‘Temporal Optimal Detection’, developed within the context of the CIRCE project and aiming at improving the ability to detect a climate change signal at the regional scale. We have also applied the ‘Consistency’ method that allows to answer the question whether a given forcing is a plausible explanation of an observed change. The results show the detection of a change on spatially centered temperatures, that allows to identify a regional structure of change additional to the global warming. The formal detection findings also extend to the winter and summer spatial patterns of temperature change. By applying the ‘Consistency’ method, we also detect the GS (Greenhouse gases and Sulfate aerosol) signal in observed annual and seasonal area-mean warming except in winter. Further we find that the recent trends in near-surface temperature are significantly consistent with the simulated GS patterns. Concerning precipitation, we cannot detect formally a signal of climate change on Mediterranean precipitation using 17 series of monthly precipitation from Croatian, French and Italian coastal stations and the CMIP3 climate simulations. However this may be due, at least partly, to the limited extent of the region covered with the precipitation series.

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Planton, S., Barkhordarian, A., Ribes, A., & Von Storch, H. (2013). Detection and Attribution. In Advances in Global Change Research (Vol. 50, pp. 157–186). Springer International Publishing. https://doi.org/10.1007/978-94-007-5781-3_5

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