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Using the past to improve future predictions requires an understanding and quantification of the individual climate contributions to the observed climate change by aerosols and greenhouse gases (GHGs), which is hindered by large uncertainties in aerosol forcings and responses across climate models. To estimate historical aerosol responses, we apply detection and attribution methods to attribute a joint change in temperature and precipitation to forcings by combining signals of observed changes in tropical wet and dry regions, the interhemispheric temperature asymmetry, global mean temperature (GMT), and global mean land precipitation (GMLP). Fingerprints representing the climate response to aerosols (AERs) and the remaining external forcings (noAER; mostly GHG) are derived from large ensembles of historical single- and ALL-forcing simulations from three models in phase 6 of the Coupled Model Intercomparison Project and selected using a perfect model study. Results from an imperfect model study and a hydrological sensitivity analysis support combining our choice of temperature and precipitation fingerprints into a joint study. We find that diagnostics including temperature and precipitation slightly better constrain the noAER signal than diagnostics based purely on temperature or GMT-only and allow for the attribution of AER cooling (even when GMT is not included in the fingerprint). These results are robust across fingerprints from different climate models. Estimated contributions for AER and noAER agree with other published estimates including those from the most recent IPCC report. Finally, we attribute the best estimate of 0.46 K ([−0.86, −0.05] K) of aerosol-induced cooling and 1.63 K ([1.26, 2.00] K) of noAER warming in 2010–19 relative to 1850–1900 using the combined signals of GMT and GMLP. Significance Statement: Aerosols are small liquid or solid airborne particles. They are predominantly the secondary result of emissions of aerosol precursor gases emitted via industrial or natural processes. While greenhouse gases warm the climate, aerosols can have a cooling effect on the climate system, thus offsetting some of the greenhouse gas–related warming. We expect greenhouse gas concentrations in the atmosphere to continue to increase, while aerosol concentrations are likely going to decline due to their impacts on human health. Our study uses observed temperature and precipitation changes to quantify how much aerosols have offset warming from past greenhouse gas emissions. This can help constrain future predictions of global warming. [ABSTRACT FROM AUTHOR]

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]

Large explosive volcanic eruptions cause short-term climatic impacts on both regional and global scales. Their impact on tropical climate variability, in particular El Niño–Southern Oscillation (ENSO), is still uncertain, as is their combined and separate effect on tropical and global precipitation. Here, we investigate the relationship between large-scale temperature and precipitation and tropical volcanic eruption strength, using 100-member MPI-ESM ensembles for idealized equatorial symmetric Northern Hemisphere summer eruptions of different sulfur emission strengths. Our results show that for idealized tropical eruptions, global and hemispheric mean near-surface temperature and precipitation anomalies are negative and linearly scalable for sulfur emissions between 10 and 40 Tg S. We identify 20 Tg S emission as a threshold where the global ensemble-mean near-surface temperature and precipitation signals exceed the range of internal variability, even though some ensemble members emerge from variability for lower eruption strengths. Seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are highly correlated across eruption strengths, in particular for larger emission strengths in the tropics, and strongly modulated by ENSO. There is a tendency to shift toward a warm ENSO phase for the first postvolcanic year as the emission strength increases. Volcanic cooling emerges on a hemisphere-wide scale, while the precipitation response is more localized, and emergence is mainly confined to the tropics and subtropics. Significance Statement: The purpose of this study is to investigate at which strength the climate responses of volcanic forcing can be distinguished from the internal climate variability and whether the responses will linearly increase as the emission strengths become stronger. We ran 100-member MPI-ESM ensembles of idealized equatorial volcanic eruptions of different sulfur emission strengths and find that seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are distinguishable and linearly scalable for sulfur emissions from 10 to 40 Tg S if their forcing patterns are similar. The identification of volcanic fingerprints is important for seasonal to decadal forecasts in the case of potential future eruptions and could help to prepare society for the regional climatic consequences of such an event. [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]

Climate models can produce accurate representations of the most important modes of climate variability, but they cannot be expected to follow their observed time evolution. This makes direct comparison of simulated and observed variability difficult and creates uncertainty in estimates of forced change. We investigate the role of three modes of climate variability, the North Atlantic Oscillation, El Niño–Southern Oscillation and the Southern Annular Mode, as pacemakers of climate variability since 1781, evaluating where their evolution masks or enhances forced climate trends. We use particle filter data assimilation to constrain the observed variability in a global climate model without nudging, producing a near-free-running model simulation with the time evolution of these modes similar to those observed. Since the climate model also contains external forcings, these simulations, in combination with model experiments with identical forcing but no assimilation, can be used to compare the forced response to the effect of the three modes assimilated and evaluate the extent to which these are confounded with the forced response. The assimilated model is significantly closer than the "forcing only" simulations to annual temperature and precipitation observations over many regions, in particular the tropics, the North Atlantic and Europe. The results indicate where initialised simulations that track these modes could be expected to show additional skill. Assimilating the three modes cannot explain the large discrepancy previously found between observed and modelled variability in the southern extra-tropics but constraining the El Niño–Southern Oscillation reconciles simulated global cooling with that observed after volcanic eruptions. [ABSTRACT FROM AUTHOR]

Here we investigate how uncertainties in the solar and volcanic forcing records of the past millennium affect the large-scale temperature response using a two-box impulse response model. We use different published solar forcing records and present a new volcanic forcing ensemble that accounts for random uncertainties in eruption dating and sulfur injection amount. The simulations are compared to proxy reconstructions from PAGES 2k and Northern Hemispheric tree ring data. We find that low solar forcing is most consistent with all the proxy reconstructions, even when accounting for volcanic uncertainty. We also find that the residuals are in line with CMIP6 control variability at centennial timescales. Volcanic forcing uncertainty induces a significant spread in the temperature response, especially at periods of peak forcing. For individual eruptions and superposed epoch analyses, volcanic uncertainty can strongly affect the agreement with proxy reconstructions and partly explain known proxy–model discrepancies. [ABSTRACT FROM AUTHOR]