Nikolaos Christidis

Fires are now raging longer and more intensely in many regions worldwide. However, non-linear interactions between fire weather, fuel, land use, management, and ignitions so far impeded formal attribution of global burned area changes. Here we show that climate change is increasingly explaining regional burned area patterns, using an ensemble of global fire models. Climate change has increased global burned area by 16% for the period 2003–2019, and raised the probability of experiencing months with above-average global burned area by 43%. Climate change-induced burned area increased in most regions, including those recently struck by extreme fire like Australia, South America and Siberia. Moreover, the contribution of climate change to burned area is rising by 0.22%year^− 1 globally, with the largest increase in Central Australia (2.5%year^− 1). Our results highlight the importance of immediate, drastic and sustained greenhouse gas emission reductions to stabilize fire impacts on lives, livelihoods and ecosystems.

As the world warms, extremely hot days are becoming more frequent and intense, reaching unprecedented temperatures associated with excess mortality. Here, we assess how anthropogenic forcings affect the likelihood of maximum daily temperatures above 50 °C at 12 selected locations around the Mediterranean and the Middle East. We adopt a risk-based attribution methodology that utilises climate model simulations with and without human influence to estimate the probability of extremes. We find that at all locations, temperatures above 50 °C would have been extremely rare or impossible in the pre-industrial world, but under human-induced climate change their likelihood is rapidly increasing. At the hottest locations we estimate the likelihood has increased by a factor of 10–10³, whereas by the end of the century such extremes could occur every year. All selected locations may see 1–2 additional months with excess thermal deaths by 2100, which stresses the need for effective adaptation planning.

Human influence and persistent low pressure are estimated to make extreme May rainfall in the United Kingdom, as in year 2021, about 1.5 and 3.5 times more likely, respectively.

The response of precipitation to global warming is manifest in the strengthening of the hydrological cycle but can be complex on regional scales. Fingerprinting analyses have so far detected the effect of human influence on regional changes of precipitation extremes. Here we examine changes in seasonal precipitation in Europe since the beginning of the twentieth century and use an ensemble of new climate models to assess the role of different climatic forcings, both natural and anthropogenic. We find that human influence gives rise to a characteristic pattern of contrasting trends, with drier seasons in the Mediterranean basin and wetter over the rest of the continent. The trends are stronger in winter and weaker in summer, when drying is more spatially widespread. The anthropogenic signal is dominated by the response to greenhouse gas emissions, but is also weakened, to some extent, by the opposite effect of anthropogenic aerosols. Using a formal fingerprinting attribution methodology, we show here for the first time that the effects of the total anthropogenic forcing, and also of its greenhouse gas component, can be detected in observed changes of winter precipitation. Greenhouse gas emissions are also found to drive an increase in precipitation variability in all seasons. Moreover, the models suggest that human influence alters characteristics of seasonal extremes, with the frequency of high precipitation extremes increasing everywhere except the Mediterranean basin, where low precipitation extremes become more common. Regional attribution information contributes to the scientific basis that can help European citizens build their climate resilience.

Based on the Gini-coefficients, this study has presented an analysis of the impacts of anthropogenic forcing on the temporal inequality (i.e., increase in unevenness or disparity) of precipitation amounts (PRCPTOT), intensity (SDII), and extremes (R95p and RX5day) at national and regional scales (eight regions) in China. A positive anthropogenic influence on the temporal inequality is found for precipitation extremes over China, especially in southern regions during the period 1961–2005. Projections of future precipitation indices except R95p have a stepped upward trend in temporal precipitation variability with increasing anthropogenic forcing in most regions of China under SSP126, SSP370, and SSP585 scenarios. Except for Southern China (SC) and SWC2, R95p has a significant decrease in the future, and the largest decrease is up to 29.5% in Northwest China under SSP370. Results obtained from this study offer insights into temporal variability of precipitation extremes and help policy makers for managing water-related disasters.

"Anthropogenic Climate Change and the Record-High Temperature of May 2020 in Western Europe" published on Mar 2022 by American Meteorological Society.

Domestic energy consumption in the United Kingdom depends on both meteorological and socio‐economic factors. The former are dominated by the effect of temperature during the colder months of the year, with the energy demand increasing as the temperature decreases. Warming of the UK climate under the influence of anthropogenic forcings is therefore expected to lead to a reduction in domestic energy consumption. Here, we present an end‐to‐end attribution study that investigates whether the anthropogenic effect on consumption is already evident in the United Kingdom. We analyse data of gas and electricity use in UK households during 2008–2019 and use a simple linear model to express the temperature dependence. Uncertainties in the resulting transfer functions are derived with a recent methodology, originally introduced for downscaling purposes, but adapted here for use in impact studies. The transfer functions are applied to temperature data from simulations with and without the effect of human influence on the climate, generated by 11 state‐of‐the‐art climate models. We thus assess the anthropogenic impact on energy consumption during the reference period by comparing it with what it might have been in a climate without anthropogenic climate change, but at the same level of adaptation. We find that without human influence on the climate, UK households would consume on average about 1,400 kWh more per year, which would increase the annual energy bills by about 70 GBP. Our attribution assessment provides useful evidence of an impact that has already emerged, which can help inform UK's adaptation plans as the climate continues to warm.

The breaking of the United Kingdom's daily rainfall record in October 2020 made a striking addition to the list of recent heavy precipitation events in the country. Mounting evidence from attribution research suggests that such extremes become more frequent and intense in a warming climate. Although most studies consider extreme events in specific months or seasons, here we investigate for the first time how extremes of the wettest day of the year may be influenced by anthropogenic forcings. Data from large multimodel ensembles indicate that the moderate historical trend towards wetter conditions will emerge more strongly in coming decades, while a notable anthropogenic influence on the variability of the wettest day may be identified as early as the 1900s. Experiments with different forcings are employed to estimate the changing probability of extremes due to anthropogenic climate change in a risk‐based attribution framework. We introduce a new methodology of estimating probabilities of extremes in the present and future that calibrates data from long simulations of the preindustrial climate to the mean state and variability of the reference climatic period. The new approach utilises larger samples of rainfall data than alternative methods, which is a major advantage when analysing extremely rare events. The record rainfall of the wettest day in year 2020 is estimated to have become about 2.5 times more likely because of human influence, while its return time, currently about 100 years, will decrease to only about 30 years by 2100. Compared to a hypothetical natural climate, we estimate a 10‐fold increase in the chances of such extreme rainfall events in the United Kingdom by the end of this century, which underlines the need for effective adaptation planning.