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Significant changes have occurred during the last few decades across the North Atlantic climate system, including in the atmosphere, ocean, and cryosphere. These large-scale changes play a vital role in shaping regional climate and extreme weather events across the UK and Western Europe. This review synthesizes the characteristics of observed large-scale changes in North Atlantic atmospheric and oceanic circulations during past decades, identifies the drivers and physical processes responsible for these changes, outlines projected changes due to anthropogenic warming, and discusses the predictability of these circulations. On multi-decadal time scales, internal variability, anthropogenic forcings (especially greenhouse gases), and natural forcings (such as solar variability and volcanic eruptions) are identified as key contributors to large-scale variability in North Atlantic atmospheric and oceanic circulations. However, there remain many uncertainties regarding the detailed characteristics of these various influences, and in some cases their relative importance. We therefore conclude that a better understanding of these drivers, and more accurate quantification of their relative roles, are crucial for more reliable decadal predictions and projections of regional climate for the North Atlantic and Europe. [ABSTRACT FROM AUTHOR]

Extreme precipitation (EP) in the Northeastern United States increased abruptly after 1996, coinciding with warming Atlantic sea surface temperatures (SSTs). We examine the importance of internal variability and external forcings (including anthropogenic and natural forcings) to these EP and SST increases by using the Community Earth System Model large ensembles and an optimal fingerprint method to isolate the effects of different forcings on 1929–2018 Northeast EP and North Atlantic SSTs. We find that external forcings have significantly influenced both Northeast EP and North Atlantic SSTs, with a time of detection in 2008 and 1968, respectively. Beyond SST changes attributable to internal variability of the Atlantic, anthropogenic aerosols and greenhouse gases are important drivers of SST changes, first detected in 1968 and 1983, respectively. Greenhouse gases are the only anthropogenic forcing exerting substantial influence on EP, first detected in 2008. We therefore attribute the 1996 EP shift to both unforced Atlantic variability and anthropogenic forcings.

Extreme precipitation (EP) in the Northeastern United States increased abruptly after 1996, coinciding with warming Atlantic sea surface temperatures (SSTs). We examine the importance of internal variability and external forcings (including anthropogenic and natural forcings) to these EP and SST increases by using the Community Earth System Model large ensembles and an optimal fingerprint method to isolate the effects of different forcings on 1929–2018 Northeast EP and North Atlantic SSTs. We find that external forcings have significantly influenced both Northeast EP and North Atlantic SSTs, with a time of detection in 2008 and 1968, respectively. Beyond SST changes attributable to internal variability of the Atlantic, anthropogenic aerosols and greenhouse gases are important drivers of SST changes, first detected in 1968 and 1983, respectively. Greenhouse gases are the only anthropogenic forcing exerting substantial influence on EP, first detected in 2008. We therefore attribute the 1996 EP shift to both unforced Atlantic variability and anthropogenic forcings.

Amplified warming in the Mediterranean region in summer, corresponding to strengthening temperature seasonality (Tseasonality), increases the frequency and intensity of heatwaves and endangers both human health and ecosystems. However, previous studies have not found a detectable signal of anthropogenic forcing in changes in Tseasonality in the Mediterranean and the contribution from human activities is unclear. Here, we show that signals of anthropogenic forcing and greenhouse gas forcing can be detected for the period 1950–2014, the signals of anthropogenic and natural forcing are separable, and the contribution of anthropogenic forcing is 74% using the optimal fingerprinting approach. Future projections based on attribution constraints indicated that Tseasonality will continue to strengthen by more than 2°C by 2100, which is much worse than predicted by direct model output. These results are important for understanding and projecting the impacts of human activities on Tseasonality and related summer heatwaves in the future. Plain Language Summary: The temperature seasonality, also known as the amplitude of the annual cycle of temperature, is important for human societies and ecosystems. The amplified summer warming enhances the temperature seasonality in the Mediterranean region, which is vulnerable to climate change. In this study, we detected signals of human influences on changes in the temperature seasonality in this region and further quantified the contribution of anthropogenic forcing using a formal detection and attribution technique. Future projections were then carried out based on attribution constraints and the results showed a much faster increase in the temperature seasonality than direct model output. The result highlights the importance of reducing greenhouse gas emissions for this region. Key Points: The anthropogenic forcing signal was detected in the strengthening temperature seasonality in the Mediterranean regionAnthropogenic forcing was found to play a major role in changes in the temperature seasonalityFuture projections based on attribution constraints indicate an enhancement in the temperature seasonality faster than direct model output [ABSTRACT FROM AUTHOR]

Soil moisture variations and its relevant feedbacks (e.g., soil moisture–temperature and soil moisture–precipitation) have a crucial impact on the climate system. This study uses reanalysis and Coupled Model Intercomparison Project phase 6 simulations datasets to detect, attribute, and project soil moisture variations. The effect of anthropogenic forcings [greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU) change] on soil moisture is much larger than that of the natural forcing. Soil moisture shows a drying trend at a global scale, which is mainly attributed to GHG forcing. The effects of external forcings vary with the regions significantly. Over eastern South America, GHG, AA, and natural forcings make soil dry, while LU forcing makes the soil wet. Over severely drying Europe, all the external forcings including GHG, AA, LU, and natural forcing exhibit drying effect. The optimal fingerprint method detection results show that some of GHG, AA, LU, and natural signals can be detected in soil moisture variations in some regions such as Europe. The soil will keep drying in all scenarios over most parts of the globe except Sahel and parts of mid-latitudes of Asia. With the increase of anthropogenic emissions, the variation of global soil moisture will be more extreme, especially in hotspots where the land–atmosphere coupling is intensive. The drying trend of soil moisture will be much larger on the surface than in middle and deep layers in the future, and this phenomenon will be more severe under the high-emission scenario. It may be affected by increased evaporation and the effect of carbon dioxide fertilization caused by global warming.

Extreme precipitation (EP) in the Northeastern United States increased abruptly after 1996, coinciding with warming Atlantic sea surface temperatures (SSTs). We examine the importance of internal variability and external forcings (including anthropogenic and natural forcings) to these EP and SST increases by using the Community Earth System Model large ensembles and an optimal fingerprint method to isolate the effects of different forcings on 1929–2018 Northeast EP and North Atlantic SSTs. We find that external forcings have significantly influenced both Northeast EP and North Atlantic SSTs, with a time of detection in 2008 and 1968, respectively. Beyond SST changes attributable to internal variability of the Atlantic, anthropogenic aerosols and greenhouse gases are important drivers of SST changes, first detected in 1968 and 1983, respectively. Greenhouse gases are the only anthropogenic forcing exerting substantial influence on EP, first detected in 2008. We therefore attribute the 1996 EP shift to both unforced Atlantic variability and anthropogenic forcings.

The long term variation of total and daily maximum precipitation over Tucuman during summer is analyzed in this work. Precipitation data cover the period 1911-2016 and was measured at the Experimental Agroindustrial Obispo Colombres (EEAOC). Total precipitation presents a significant positive linear trend during the whole period due to the 1956 climatic jump, while maximum daily precipitation presents a significant trend only during 1956-1994. Taking into account that the South American monsoon is a strong determinant of precipitation regimes in Northern of Argentina, the correlation with atmospheric circulation variables is analyzed: upper troposphere zonal wind (U) in the Bolivian High region and lower troposphere meridional wind (V) in the Chaco Low region, together with pressure (P) and temperature (T) in the South Atlantic region. There is a good statistical agreement between precipitation series and these variables when the whole period is considered due to all these series present a general linear trend. In the sub-period 1960-2012 total precipitation presents a 20-year quasi-periodicity in phase with P, and have no correlation with U and V. Maximum daily precipitation instead correlates better with velocity variables during this same period, which in turn are linked to the regional convection. The association with the oceanic variability is analyzed finding good correlation with the Pacific Decadal Oscillation (PDO) during the second half of twentieth century. Finally, the possible role on the trends of the global CO2 increase and the polar column O3 depletion is analyzed. There is a significant positive correlation with CO2, similar to that with T, due to the general increasing trend in both series, and negative correlation with O3 due to, in addition to the opposed trends in both series, they have a coincident sign-trend change in 1960. [ABSTRACT FROM AUTHOR]

Daytime heat is often associated with reduced soil moisture and cloud cover, while nighttime heat is connected to high humidity and increased cloud cover. Due to these differing mechanisms, compound daytime and nighttime heat events may respond differently to major anthropogenic forcings (greenhouse gases, anthropogenic aerosols, land-use and land-cover change). Here, we use GISS ModelE2.1-G historical single-forcing runs from 1955 to 2014 to examine how individual anthropogenic forcings affect compound heat events—specifically warm daytime and nighttime temperatures compounded with dry precipitation or high humidity conditions. We show that greenhouse gases alone amplify the natural frequency of warm-dry events by 1.5–5 times and warm-humid events by 2–9 times in tropical and extratropical latitudes. Conversely, aerosols and land-use/land-cover change reduce the frequency of these events, resulting in more modest increases and in some regions, declines, in the historical ‘all-forcings’ scenario. Individually, aerosol effects are stronger and more widespread compared to land-use, oftentimes reducing the natural frequency of these events by 60%–100%. The responses of these compound events are primarily driven by changes in daytime and nighttime temperatures through large-scale warming via greenhouse gases and cooling from aerosols and land-use/land-cover change. However, changes in warm-dry events are amplified in regions with concurrent precipitation declines (e.g. Central America, Mediterranean regions) and warm-humid events are amplified by global concurrent humidity increases. Additionally, we find differences between daytime and nighttime compound responses in the historical experiment that can be traced back to the individual forcings. In particular, aerosols produce a greater cooling effect on daytime relative to nighttime temperatures, which notably results in a historical reduction of Northern Hemisphere daytime warm-dry events relative to natural conditions. Our analysis provides a more comprehensive understanding of the significant impacts of different anthropogenic climate forcings on daytime and nighttime warm-dry and warm-humid events, informing future risk and impact assessments.

Detection and attribution studies have demonstrated that anthropogenic forcings have been driving significant changes in temperature extremes since the middle of the 20th century. Moreover, new methodologies have been developed for the attribution of extreme events that assess how human influence may have changed their characteristics. Here we combine formal statistical analyses based on optimal fingerprinting to attribute observed long term changes in temperature extremes with an ensemble-based approach for event attribution. Our analyses are applied to 16 indices constructed with daily temperature data that focus on different characteristics of extremes and together build up a more complete representation of historical changes in warm and cold extremes than previous studies. For each index we compute an annual value for all years of the post-1960 period using data from observations and experiments with a coupled Earth System model for the analysis of multi-decadal changes and a high-resolution atmospheric model for event attribution. The models indicate that anthropogenic forcings have influenced almost all indices in recent decades and led to more prominent changes in the frequency of extremes. The optimal fingerprinting analyses show that for most indices the anthropogenic signal is detectable in changes during 1961–2010 both in Europe and on a quasi-global scale. The weaker natural effect, resulting mainly from volcanic eruptions, is in most cases not detectable, with the exception of large scale changes in indices linked to the frequency of cold night-time extremes. Our event analyses estimate how anthropogenic forcings alter the chances of getting new record index values in Europe and find that such extremes would be markedly rare if human influence were not accounted for, whereas in the current climate their return times range from a few years to a few decades.

Regional warming due to anthropogenic influence on the climate is expected to increase the frequency of very warm years and seasons. The growing research area of extreme event attribution has provided pertinent scientific evidence for a number of such warm events for which the forced climate response rises above internal climatic variability. Although the demand for attribution assessments is higher shortly after an event occurs, most scientific studies become available several months later. A formal attribution methodology is employed here to pre-compute the changing odds of very warm years and seasons in regions across the world. Events are defined based on the exceedence of temperature thresholds and their changing odds are measured over a range of pre-specified thresholds, which means assessments can be made as soon as a new event happens. Optimal fingerprinting provides observationally constrained estimates of the global temperature response to external forcings from which regional information is extracted. This information is combined with estimates of internal variability to construct temperature distributions with and without the effect of anthropogenic influence. The likelihood of an event is computed for each distribution and the change in the odds estimated. Analyses are conducted with seven climate models to explore the model dependency of the results. Apart from colder regions and seasons, characterised by greater internal climate variability, the odds of warm events are found to have significantly increased and temperatures above the threshold of 1-in-10 year events during 1961-1990 have become at least twice as likely to occur. [ABSTRACT FROM AUTHOR]

Regional distributions of the mean annual temperature in the 2000s are computed with and without the effect of anthropogenic influences on the climate in several sub-continental regions. Simulated global patterns of the temperature response to external forcings are regressed against observations using optimal fingerprinting. The global analysis provides constraints which are then used to construct the regional temperature distributions. A similar approach was also employed in previous work, but here the methodology is extended to examine changes in any region, including areas with a poor observational coverage that were omitted in the earlier study. Two different General Circulation Models (GCMs) are used in the analysis. Anthropogenic forcings are found to have at least quadrupled the likelihood of occurrence of a year warmer than the warmest year since 1900 in 23 out of the 24 regions. The temperature distributions computed with the two models are very similar. While a more detailed assessment of model dependencies remains to be made once additional suitable GCM simulations become available, the present study introduces the statistical methodology and demonstrates its first application. The derived information concerning the effect of human influences on the regional climate is useful for adaptation planning. Moreover, by pre-computing the change in the likelihood of exceeding a temperature threshold over a range of thresholds, this kind of analysis enables a near real-time assessment of the anthropogenic impact on the observed regional temperatures. [ABSTRACT FROM AUTHOR]

The South Asian summer monsoon is a complex coupled human‐natural system that poses unique challenges for understanding its evolution alongside increasing anthropogenic activities. Rapid and substantial changes in land‐use, land‐management and industrial activities over the subcontinent, and warming in the Indian Ocean, have influenced the South Asian summer monsoon. These might continue to be significant drivers in the near‐term along with rising global greenhouse gas emissions. Deciphering the region's vulnerability to climate change requires an understanding of how these anthropogenic activities, acting on a range of spatial scales, have shaped the monsoon spatially and temporally. This review summarizes historical changes in monsoon rainfall characteristics, associated mechanisms, and the role of anthropogenic forcings, focusing on subseasonal variability and extreme events. Several studies have found intensified subseasonal extremes across parts of India and an increase in spatial variability of rainfall despite an overall weakening of seasonal rainfall in the monsoon core. However, understanding these changes remains challenging because of uncertainties in observations and climate models. The mechanisms and relative influences of various anthropogenic activities, particularly on subseasonal extremes, remain relatively underexplored. Large biases in the representation of relevant processes in global climate models limit the ability to attribute historical changes and make reliable projections. Nevertheless, recent advances in modeling these processes using higher‐resolution modeling frameworks provide new tools to investigate the Indian summer monsoon's response to various anthropogenic forcings. There is an urgent need to understand how these forcings interact to shape climate variability and change in this vulnerable region. This article is categorized under: Paleoclimates and Current Trends > Earth System Behavior Influence of anthropogenic forcings on rainfall variability. [ABSTRACT FROM AUTHOR]