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Author: Stone, Dáithí A. ×

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    Robust changes in tropical rainy season length at 1.5 °C and 2 °C
    (Bristol : IOP Publ., 2018) Saeed, Fahad; Bethke, Ingo; Fischer, Erich; Legutke, Stephanie; Shiogama, Hideo; Stone, Dáithí A.; Schleussner, Carl-Friedrich
    Changes in the hydrological cycle are among the aspects of climate change most relevant for human systems and ecosystems. Besides trends in overall wetting or drying, changes in temporal characteristics of wetting and drying are of crucial importance in determining the climate hazard posed by such changes. This is particularly the case for tropical regions, where most precipitation occurs during the rainy season and changes in rainy season onset and length have substantial consequences. Here we present projections for changes in tropical rainy season lengths for mean temperature increase of 1.5 °C and 2 °C above pre-industrial levels. Based on multi-ensemble quasi-stationary simulations at these warming levels, our analysis indicates robust changes in rainy season characteristics in large parts of the tropics despite substantial natural variability. Specifically, we report a robust shortening of the rainy season for all of tropical Africa as well as north-east Brazil. About 27% of West Africa is projected to experience robust changes in the rainy season length with a mean shortening of about 7 days under 1.5 °C. We find that changes in the temporal characteristics are largely unrelated to changes in overall precipitation, highlighting the importance of investigating both separately.
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    Rapid systematic assessment of the detection and attribution of regional anthropogenic climate change
    (Heidelberg : Springer, 2015) Stone, Dáithí A.; Hansen, Gerrit
    Despite being a well-established research field, the detection and attribution of observed climate change to anthropogenic forcing is not yet provided as a climate service. One reason for this is the lack of a methodology for performing tailored detection and attribution assessments on a rapid time scale. Here we develop such an approach, based on the translation of quantitative analysis into the “confidence” language employed in recent Assessment Reports of the Intergovernmental Panel on Climate Change. While its systematic nature necessarily ignores some nuances examined in detailed expert assessments, the approach nevertheless goes beyond most detection and attribution studies in considering contributors to building confidence such as errors in observational data products arising from sparse monitoring networks. When compared against recent expert assessments, the results of this approach closely match those of the existing assessments. Where there are small discrepancies, these variously reflect ambiguities in the details of what is being assessed, reveal nuances or limitations of the expert assessments, or indicate limitations of the accuracy of the sort of systematic approach employed here. Deployment of the method on 116 regional assessments of recent temperature and precipitation changes indicates that existing rules of thumb concerning the detectability of climate change ignore the full range of sources of uncertainty, most particularly the importance of adequate observational monitoring.