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The article discusses the possibility that global warming contributed to insufficient ice thickness in the Netherlands in February 2012 despite the cold spell that much of Western Europe experienced at the time. It mentions the requirement of 15 centimeters of ice thickness for holding the 11-City Tour of Fyrsia ice-skating marathon, which was last held in January 1997. Snowfall on thin ice that had just formed is shown to have limited ice growth more strongly than the effect of global warming.

The author comments on an article about the predictability of winter climate over the North Atlantic European region during the El Niño Southern Oscillation (ENSO) events. Linear teleconnections to winter climate in Europe are known to be very small, much smaller than in spring and fall. It is argued that the ENSO events have a significant influence on the climate of the North Atlantic European region. And it is claimed that the details of the sea surface temperature anomalies determine the shape of the teleconnection, which can therefore not be described by linear correlations.

In this study, the authors investigate the effect of GCM spatial resolution on modeled precipitation over Europe. The objectives of the analysis are to determine whether climate models have sufficient spatial resolution to have an accurate representation of the storm tracks that affect precipitation. They investigate if there is a significant statistical difference in modeled precipitation between a medium-resolution (~112-km horizontal resolution) and a high-resolution (~25-km horizontal resolution) version of a state-of-the-art AGCM (EC-EARTH), if either model resolution gives a better representation of precipitation in the current climate, and what processes are responsible for the differences in modeled precipitation. The authors find that the high-resolution model gives a more accurate representation of northern and central European winter precipitation. The medium-resolution model has a larger positive bias in precipitation in most of the northern half of Europe. Storm tracks are better simulated in the high-resolution model, providing for a more accurate horizontal moisture transport and moisture convergence. Using a decomposition of the precipitation difference between the medium- and high-resolution model in a part related and a part unrelated to a difference in the distribution of vertical atmospheric velocity, the authors find that the smaller precipitation bias in central and northern Europe is largely unrelated to a difference in vertical velocity distribution. The smaller precipitation amount in these areas is in agreement with less moisture transport over this area in the high-resolution model. In areas with orography the change in vertical velocity distribution is found to be more important. [ABSTRACT FROM AUTHOR]

In October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country. [ABSTRACT FROM AUTHOR]

Over the first half of 2020, Siberia experienced the warmest period from January to June since records began and on the 20th of June the weather station at Verkhoyansk reported 38 °C, the highest daily maximum temperature recorded north of the Arctic Circle. We present a multi-model, multi-method analysis on how anthropogenic climate change affected the probability of these events occurring using both observational datasets and a large collection of climate models, including state-of-the-art higher-resolution simulations designed for attribution and many from the latest generation of coupled ocean-atmosphere models, CMIP6. Conscious that the impacts of heatwaves can span large differences in spatial and temporal scales, we focus on two measures of the extreme Siberian heat of 2020: January to June mean temperatures over a large Siberian region and maximum daily temperatures in the vicinity of the town of Verkhoyansk. We show that human-induced climate change has dramatically increased the probability of occurrence and magnitude of extremes in both of these (with lower confidence for the probability for Verkhoyansk) and that without human influence the temperatures widely experienced in Siberia in the first half of 2020 would have been practically impossible. [ABSTRACT FROM AUTHOR]

In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit. [ABSTRACT FROM AUTHOR]

The science of event attribution has emerged to routinely answer the question whether and to what extent human-induced climate change altered the likelihood and intensity of recently observed extreme weather events. In Europe a pilot program to operationalize the method started in November 2019, highlighting the demand for timely information on the role of climate change when it is needed most: in the direct aftermath of an extreme event. Independent of whether studies are provided operationally or as academic studies, the necessity of good observational data and well-verified climate models imply most attributions are currently made for highly developed countries only. Current attribution assessments therefore provide very little information about those events and regions where the largest damages and socio-economic losses are incurred. Arguably, these larger damages signify a much greater need for information on how the likelihood and intensity of such high-impact events have been changing and are likely to change in a warmer world. In short, why do we not focus event attribution research efforts on the whole world, and particularly events in the developing world? The reasons are not just societal and political but also scientific. We simply cannot attribute these events in the same probabilistic framework employed in most studies today. We outline six focus areas to lessen these barriers, but we will not overcome them in the near future. [ABSTRACT FROM AUTHOR]

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution. [ABSTRACT FROM AUTHOR]

Summer 2012 was very wet in northern Europe, and unusually dry and hot in southern Europe. We use multiple approaches to determine whether anthropogenic forcing made the extreme European summer of 2012 more likely. Using a number of observation- and model-based methods, we find that there was an anthropogenic contribution to the extremes in southern Europe, with a qualitative consensus across all methodologies. There was a consensus across the methodologies that there has been a significant increase in the risk of hot summers in southern Europe with climate change. Most approaches also suggested a slight drying, but none of the results were statistically significant. The unusually wet summer in northern Europe was made more likely by the observed atmospheric circulation pattern in 2012, but no evidence was found for a long-term trend in circulation. [ABSTRACT FROM AUTHOR]

The article presents the study that estimates the changes of the global temperature since preindustrial period. The topics discussed include the importance of the preindustrial period in crossing the thresholds in global temperature, the different approaches used in assessing changes in global temperature, and recommendations on how the assessments can be enhanced. It also cites the goal of the 2015 Paris COP21 Agreement of the United Nations in maintaining global temperature below two degrees.

The article discusses the study regarding the role of anthropogenic warming or human-induced climate change in the frequency and intensity of heat waves in central Europe in 2015. Topics discussed include the frequency of summer heat stress, the application of bias-corrected regional climate model simulations, and the use of multimethod analysis.

Here we present a set of regional climate scenarios of sea level rise for the northeast Atlantic Ocean. In this study, the latest observations and results obtained with state-of-the-art climate models are combined. In addition, regional effects due to ocean dynamics and changes in the Earth’s gravity field induced by melting of land-based ice masses have been taken into account. The climate scenarios are constructed for the target years 2050 and 2100, for both a moderate and a large rise in global mean atmospheric temperature (2 °C and 4 °C in 2100 respectively). The climate scenarios contain contributions from changes in ocean density (global thermal expansion and local steric changes related to changing ocean dynamics) and changes in ocean mass (melting of mountain glaciers and ice caps, changes in the Greenland and Antarctic ice sheets, and (minor) terrestrial water-storage contributions). All major components depend on the global temperature rise achieved in the target periods considered. The resulting set of climate scenarios represents our best estimate of twenty-first century sea level rise in the northeast Atlantic Ocean, given the current understanding of the various contributions. For 2100, they yield a local rise of 30 to 55 cm and 40 to 80 cm for the moderate and large rise in global mean atmospheric temperature, respectively. [ABSTRACT FROM AUTHOR]

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.