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Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias‐corrected wind supply data and the estimated temperature‐related part of demand to analyse events of potential weather‐related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present‐day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short‐lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions. [ABSTRACT FROM AUTHOR]

Variability in the North Atlantic Oscillation (NAO) has contributed to the recent multidecadal trends observed in European climate, especially to trends in winter precipitation over Northern Europe. However, the current generation of coupled climate models struggle to reproduce the NAO's contribution to multidecadal trends, which has important implications for deriving constraints based on the comparison of observed and modeled trends. An observational constraint based on attribution results, both with and without the contribution of variability associated with the NAO, is applied to projections of Northern European precipitation and temperature, and observed NAO variability is shown to lead to a constraint that overestimates future forced changes. Only after removing the NAO variability is the observed climate change consistent with model simulations, and a tighter, unbiased observational constraint based on the forced signal (without the NAO) can be applied to future projections. Plain Language Summary: The observed precipitation and temperature across Northern Europe in winter has been increasing over the past several decades. However, the magnitude of this trend is generally not well reproduced by the latest set of global climate models. A part of the observed increase in precipitation can be related to the variability in the North Atlantic Oscillation (NAO), which is a large‐scale pattern of sea level pressure in the North Atlantic region that varies in strength each season and year, and is strongly linked to temperature and precipitation patterns across Europe, particularly in winter. In this study, we show that if the variability related to the NAO is first removed from the precipitation time series, from both the observations and the model simulations, the difference between the long‐term observed and modeled trends in precipitation is reduced. Removing the NAO variability also has an impact on the difference in observed and modeled trends in temperature. This has important implications for approaches that use the difference in observations and model simulations as a way of constraining future projections of climate change. Key Points: Variability in the North Atlantic Oscillation (NAO) has contributed to the recent multidecadal trends observed in European climateThe suite of current comprehensive global models (CMIP6) struggle to reproduce the NAO's contribution to multidecadal trendsRemoving the NAO from both observations and models provides a tighter, unbiased constraint, which can then be applied to model projections [ABSTRACT FROM AUTHOR]

As global surface temperatures continue to rise, both the duration and the intensity of heat waves across most land areas are expected to increase. The 2022 European summer broke a number of temperature records where a new record daily maximum temperature of 40.3°C was reached on 19th July making it the hottest July heat wave event in the UK. This paper aims to detect and analyse historical heat wave events, particularly prior to 1927 and compare these with recent events, particularly, 2022, which featured four summer heat wave events in the UK. This allows us to understand how noteworthy historical extremes are in comparison to those in recent decades, to place modern events into historical context, and to extend the sample of extreme events. Summer heat wave events have been detected between 1878 and 2022 from long station data in the UK. Heat wave extent, duration, and intensity have been analysed to compare past heat waves to the recent 2022 heat waves. For each of the summer months at least one of the top 10 most intense events between 1878 and 2022 occurred in the earliest third of the dataset (before 1927) emphasising the value of analysing early heat events. In all detected events, the anomalous UK heat was part of large‐scale European extreme heat when examining 20th‐century reanalysis data, associated with a high‐pressure system. The 2022 July event resembles in pattern of warming and circulation some earlier events, for example, in 1925. While there is a clear trend in the monthly data and the overall frequency of anomalously hot days, heat wave activity on daily scales even in the period 1878 and 1926 is considerable and in some cases comparable to modern heat wave events in the UK. The most intense events detected led to societal impacts based on UK newspaper articles from the period including impacts on the agricultural sector, health impacts, and travel disruptions, broadly comparable to impacts from recent events. [ABSTRACT FROM AUTHOR]

Although the West Antarctic surface climate has experienced large changes over the past decades with widespread surface warming, an overall increase in snow accumulation and a deepening of the Amundsen Sea Low, the exact role of human activities in these changes has not yet been fully investigated, which limits confidence in future projections. Here, we perform a detection and attribution analysis using instrumental and proxy‐based reconstructions, and two large climate model simulation ensembles to quantify the forced response in these observed changes. We show that surface climate changes since the 1950s were driven by anthropogenic forcing, in particular the greenhouse gas forcing and stratospheric ozone depletion. Therefore, our results indicate that the 21st century changes will depend on both the greenhouse gas emissions and the ozone layer recovery. Plain Language Summary: Since the second half of the 20th century, West Antarctica has experienced large climate changes, such as widespread warming, increased snow accumulation, and a deepening of a low‐pressure system located off the West Antarctic coasts. The observed climate changes in West Antarctica are influenced by both the internal (related to the chaotic nature of climate) and forced (related to changes in forcings) variability but it is still unclear to what extent human activities are responsible for these changes. We used a statistical method to distinguish between changes caused by humans and by natural influences both for instrumental observations and reconstructions of past climate. Our results show that the observed changes since the 1950s are out of the range of natural variability and can be attributed to human activities—that is, the increase of greenhouse gases and stratospheric ozone depletion. Therefore, our findings indicate that the future state of the West Antarctic surface climate will depend on the greenhouse gas emissions as well as the ozone layer recovery. Key Points: Surface climate changes since the 1950s in West Antarctica are out of the range of internal variabilityThe increase in greenhouse gas emissions and stratospheric ozone depletion are responsible for these changesThe future changes over the 21st century will depend on both the greenhouse gas emissions and the ozone layer recovery [ABSTRACT FROM AUTHOR]

It sounds straightforward. As the Earth warms due to the increased concentration of greenhouse gases in the atmosphere, global temperatures rise and so heatwaves become warmer as well. This means that a fixed temperature threshold is passed more often: the probability of extreme heat increases. However, land use changes, vegetation change, irrigation, air pollution, and other changes also drive local and regional trends in heatwaves. Sometimes they enhance heatwave intensity, but they can also counteract the effects of climate change, and in some regions, the mechanisms that impact on trends in heatwaves have not yet been fully identified. Climate models simulate heatwaves and the increased intensity and probability of extreme heat reasonably well on large scales. However, changes in annual daily maximum temperatures do not follow global warming over some regions, including the Eastern United States and parts of Asia, reflecting the influence of local drivers as well as natural variability. Also, temperature variability is unrealistic in many models, and can fail standard quality checks. Therefore, reliable attribution and projection of change in heatwaves remain a major scientific challenge in many regions, particularly where the moisture budget is not well simulated, and where land surface changes, changes in short‐lived forcers, and soil moisture interactions are important. Plain Language Summary: Heatwaves are arguably the most deadly weather phenomena. As the Earth warms due to higher concentrations of greenhouse gases, one would expect heatwaves to become worse as well, killing even more people unless they are better protected against the heat. However, it turns out that the world is not so simple and that many other factors also influence heatwaves. Land use changes, irrigation, air pollution, and other changes also drive trends in heatwaves. Some of these cause much larger trends while some have counteracted the climate change‐driven trends up to now. In some regions, the causes of high trends have not yet been identified. Current generation climate models often do not simulate all these mechanisms correctly so will have to be improved before we can more confidently trust their description of past trends and projections of future trends in heatwaves. Key Points: The IPCC AR6 WG1 states the "frequency and intensity of hot extremes have increased"The IPCC notes that the effect of increased greenhouse gas on high temperatures is moderated or amplified at local scales by other factorsConfident quantitative attribution statements of the human influence on heatwaves are limited by our understanding of these local processes [ABSTRACT FROM AUTHOR]

Providing comprehensive regional‐ and local‐scale information on changes observed in the climate system plays a vital role in planning effective and efficient climate change adaptation options, specifically over resource‐limited regions. Here, we assess changes in temperature and heat waves over different regions of the African continent, with a focus on spatiotemporal trends and the time of emergence of change in hot extremes from natural variability. We analyse absolute and relative threshold indices. Data sets include temperatures from observations (CRUTS4.03 and BEST) and from three representative state‐of‐the‐art reanalyses (ERA5, MERRA2 and JRA‐55) for the common period 1980–2018. Statistically significant warming is observed over all regions of Africa in temperature time series from CRU observations and reanalysis data, although the trend strength varies between data sets. Also, extreme temperatures and heat wave indices from BEST observations and all reanalysis data sets reveal increasing trends over all regions of the African continent. However, there are differences in both trend strength and time evolution of heat wave indices between different reanalysis data sets. Most data sets agree in identifying 2010 as a peak heat year over Northern and Western Africa while Eastern and Southern Africa experienced the highest heat wave occurrence in 2016. Our results clearly reveal that heat wave occurrences have emerged from natural climate variability in Africa. The earliest time of emergence takes place in the Northern Africa region in the early 2000s while in the other African regions emergence over natural variability is found mainly after 2010. This also depends on the respective index metrics, where indices based on more consecutive days show later emergence of heat wave trends. Overall, significant warming and an increase in heat wave occurrence is found in all regions of Africa and has emerged from natural variability in the past one or two decades. [ABSTRACT FROM AUTHOR]

Extreme temperature events causing significant environmental and humanitarian impacts are expected to increase in frequency and magnitude due to global warming. The latest generation of climate model projections, Coupled Model Intercomparison Project Phase Six (CMIP6), provides a new and improved database to investigate change in future daily scale extreme temperature events. This study examines the changes in 1, 3, and 5 day averaged annual maximum temperature in four large CMIP6 ensembles. It analyses, using a generalized extreme value (GEV) method, the change in extreme daily mean temperatures at 1.5 and 2°C of global warming, levels highlighted by the 2016 Paris Agreement, and additionally at 3°C. Extremely hot events are characterized using the annual maxima of daily near surface air temperature in the SSP370 scenario. Global changes in the mode of the distributions (location parameter) follow long‐term summer warming and show very similar spatial patterns. Changes in variability (scale parameter) show a clear trend of increases over the tropics and decreases over higher latitudes, while changes to the tails of distributions (shape parameter) show less globally consistent trends but clear signals over the Arctic sea ice, behaviour also seen in variability. Risk ratios (RRs) indicating the change in probability of hot daily extremes that currently have a 10 year return period increase globally with mean temperature change, with greater increases over the tropics. Globally averaged changes in RR over land range from 3.1–3.6 to 7.9–8.3 for 1.5 and 3°C of warming, respectively. For the latter case, this indicates previously rare, once‐in‐a‐decade summer extremes will occur almost annually in the future under high warming. [ABSTRACT FROM AUTHOR]

Insolation changes caused by the axial precession induce millennial trends in last millennium temperature, varying with season and latitude. A characteristic seasonal trend pattern can be detected in both insolation and modeled surface temperature response. In the extratropical Northern Hemisphere, the maximum insolation trend occurs around April/May, while the minimum trend occurs between July and September. The temperature trend lags behind insolation trend by around a month. Hence orbital forcing potentially affects long‐term trends in proxy data, which are often sensitive to a distinct seasonal window. We find that tree‐ring reconstructions based on early growing season dominated records show different millennial trends from those for late summer dominated proxies. The differential response is similar to that seen in pseudo proxy reconstructions when considering proxy seasonality. This suggests that orbital forcing has influenced long‐term trends in climate proxies. It is therefore vital to use seasonally homogeneous data for reconstructing multicentennial variability. Plain Language Summary: The Earth's axis spins like a slightly wobbly gyroscope, with one spin taking around 24,000 years. Depending on the phase of the spin, more or less sunlight comes in during the different seasons, impacting the Earth's climate. This is orbital forcing. Analyzing temperature data produced by global climate models, we found that orbital forcing causes a distinct seasonal trend pattern over the last millennium, which should influence global and regional climate. These patterns are very different from other natural climate forcings‐like volcanic eruptions or changes of the Sun's energy output. We have also found evidence of orbital forcing in reconstructions of past climate using natural climate archives such as tree rings and other climate proxies. These findings can potentially resolve previous inconsistencies in long‐term climate change found in proxy reconstructions and climate model output. Key Points: Orbital forcing induces a strong seasonal fingerprint in climate model simulations, which is distinct from any other forcingsOver the last millennium, surface temperature trends simulated by climate models lag asymmetrically behind the insolation by around a monthDifferences between long‐term trends of proxy records could be caused by seasonal orbital forcing, which influences climate reconstructions [ABSTRACT FROM AUTHOR]

The most pronounced warming in the historical global climate record prior to the recent warming occurred over the first half of the 20th century and is known as the Early Twentieth Century Warming (ETCW). Understanding this period and the subsequent slowdown of warming is key to disentangling the relationship between decadal variability and the response to human influences in the present and future climate. This review discusses the observed changes during the ETCW and hypotheses for the underlying causes and mechanisms. Attribution studies estimate that about a half (40–54%; p > .8) of the global warming from 1901 to 1950 was forced by a combination of increasing greenhouse gases and natural forcing, offset to some extent by aerosols. Natural variability also made a large contribution, particularly to regional anomalies like the Arctic warming in the 1920s and 1930s. The ETCW period also encompassed exceptional events, several of which are touched upon: Indian monsoon failures during the turn of the century, the “Dust Bowl” droughts and extreme heat waves in North America in the 1930s, the World War II period drought in Australia between 1937 and 1945; and the European droughts and heat waves of the late 1940s and early 1950s. Understanding the mechanisms involved in these events, and their links to large scale forcing is an important test for our understanding of modern climate change and for predicting impacts of future change. This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change [ABSTRACT FROM AUTHOR]

The article investigates the impact of data precision on the calculation of temperature percentile indices. The monitoring, detection and attribution of changes in weather demands the need to gather the daily data on the condition of the climate. However, possible bias occurs when there is insufficient precision in temperature data and it eventually affects the estimation of the means and trends of percentile-based indices. Results of various research related to the climate and temperature changes prove that there are no accurate or fix results of individual observations in climate changes.