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Towards Reliable Extreme Weather and Climate Event Attribution

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TLDR
It is shown, exploiting advanced correction techniques from the weather forecasting field, that correcting properly for model probabilities alters the attributable risk of extreme events to climate change.
Abstract
Climate change is shaping extreme heat and rain. To what degree human activity has increased the risk of high impact events is of high public concern and still heavily debated. Recent studies attributed single extreme events to climate change by comparing climate model experiments where the influence of an external driver can be included or artificially suppressed. Many of these results however did not properly account for model errors in simulating the probabilities of extreme event occurrences. Here we show, exploiting advanced correction techniques from the weather forecasting field, that correcting properly for model probabilities alters the attributable risk of extreme events to climate change. This study illustrates the need to correct for this type of model error in order to provide trustworthy assessments of climate change impacts.

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1 km monthly temperature and precipitation dataset for China from 1901 to 2017

TL;DR: Peng et al. as mentioned in this paper presented a 0.5 × 1.5 cm dataset with a bilinear interpolation method for air temperatures at 2 cm (minimum, maximum, and mean proxy monthly temperatures, TMPs) and precipitation (PRE) for China.
Journal ArticleDOI

Increased future occurrences of the exceptional 2018-2019 Central European drought under global warming

TL;DR: It is demonstrated that the occurrence of the 2018–2019 (consecutive) summer drought is unprecedented in the last 250 years, and its combined impact on the growing season vegetation activities is stronger compared to the 2003 European drought.
Journal ArticleDOI

Soil microbial community responses to climate extremes: resistance, resilience and transitions to alternative states

TL;DR: This work synthesizes emerging understanding of the intrinsic and extrinsic factors that influence the resistance and resilience of soil microbial communities to climate extremes, with a focus on drought, and identifies drivers that might trigger abrupt changes to alternative states.
Journal ArticleDOI

A protocol for probabilistic extreme event attribution analyses

TL;DR: In this article, the authors present a protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes.
References
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Journal ArticleDOI

Updated high‐resolution grids of monthly climatic observations – the CRU TS3.10 Dataset

TL;DR: In this paper, an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas is presented.
Journal ArticleDOI

The role of increasing temperature variability in European summer heatwaves

TL;DR: It is found that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account, and it is proposed that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003.
Book

Managing the risks of extreme events and disasters to advance climate change adaption

TL;DR: In this article, the authors present a case study for managing the risks from climate extremes and disasters at the local level and national systems for managing risks at the international level and integration across scales.
BookDOI

Forecast verification: a practitioner's guide in atmospheric science

TL;DR: Jolliffe et al. as mentioned in this paper proposed a framework for verification of spatial fields based on binary and categorical events, and proved the correctness of the proposed framework with past, present and future predictions.
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