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Extremes of weather and climate can have devastating effects on human society and the environment. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavy precipitation events over a large part of the Northern Hemisphere land area, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature--and that atmospheric water content is increasing in accord with this theoretical expectation--it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model-model comparisons. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming.

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]

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]

Global warming is expected to not only impact mean temperatures but also temperature variability, substantially altering climate extremes. Here we show that human-caused changes in internal year-to-year temperature variability are expected to emerge from the unforced range by the end of the 21st century across climate model initial-condition large ensembles forced with a strong global warming scenario. Different simulated changes in globally averaged regional temperature variability between models can be explained by a trade-off between strong increases in variability on tropical land and substantial decreases in high latitudes, both shown by most models. This latitudinal pattern of temperature variability change is consistent with loss of sea ice in high latitudes and changes in vegetation cover in the tropics. Instrumental records are broadly in line with this emerging pattern, but have data gaps in key regions. Paleoclimate proxy reconstructions support the simulated magnitude and distribution of temperature variability. Our findings strengthen the need for urgent mitigation to avoid unprecedented changes in temperature variability. Climate change does not only increase mean temperatures, but also the magnitude of year-to-year temperature variability. Here, the authors use large model ensembles to show that these changes can be statistically distinguished from the baseline variability in most regions of the world during the 21st century. [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]

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]

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratosphericozone- only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing. [ABSTRACT FROM AUTHOR]

Extremes of weather and climate can have devastating effects on human society and the environment. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavy precipitation events over a large part of the Northern Hemisphere land area, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature-and that atmospheric water content is increasing in accord with this theoretical expectation-it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model-model comparisons. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming. [ABSTRACT FROM AUTHOR]

Climate records over the last millennium place the twentieth-century warming in a longer historical context. Reconstructions of millennial temperatures show a wide range of variability, raising questions about the reliability of currently available reconstruction techniques and the uniqueness of late-twentieth-century warming. A calibration method is suggested that avoids the loss of low-frequency variance. A new reconstruction using this method shows substantial variability over the last 1500 yr. This record is consistent with independent temperature change estimates from borehole geothermal records, compared over the same spatial and temporal domain. The record is also broadly consistent with other recent reconstructions that attempt to fully recover low-frequency climate variability in their central estimate. High variability in reconstructions does not hamper the detection of greenhouse gas–induced climate change, since a substantial fraction of the variance in these reconstructions from the beginning of the analysis in the late thirteenth century to the end of the records can be attributed to external forcing. Results from a detection and attribution analysis show that greenhouse warming is detectable in all analyzed high-variance reconstructions (with the possible exception of one ending in 1925), and that about a third of the warming in the first half of the twentieth century can be attributed to anthropogenic greenhouse gas emissions. The estimated magnitude of the anthropogenic signal is consistent with most of the warming in the second half of the twentieth century being anthropogenic. [ABSTRACT FROM AUTHOR]

The magnitude and impact of future global warming depends on the sensitivity of the climate system to changes in greenhouse gas concentrations. The commonly accepted range for the equilibrium global mean temperature change in response to a doubling of the atmospheric carbon dioxide concentration, termed climate sensitivity, is 1.5–4.5 K (ref. 2). A number of observational studies, however, find a substantial probability of significantly higher sensitivities, yielding upper limits on climate sensitivity of 7.7 K to above 9 K (refs 3–8). Here we demonstrate that such observational estimates of climate sensitivity can be tightened if reconstructions of Northern Hemisphere temperature over the past several centuries are considered. We use large-ensemble energy balance modelling and simulate the temperature response to past solar, volcanic and greenhouse gas forcing to determine which climate sensitivities yield simulations that are in agreement with proxy reconstructions. After accounting for the uncertainty in reconstructions and estimates of past external forcing, we find an independent estimate of climate sensitivity that is very similar to those from instrumental data. If the latter are combined with the result from all proxy reconstructions, then the 5–95 per cent range shrinks to 1.5–6.2 K, thus substantially reducing the probability of very high climate sensitivity. [ABSTRACT FROM AUTHOR]

The article discusses a report in the same issue by Schmittner and colleagues regarding the use of paleoclimate data to estimate future climate change. Researchers believe that observing climate responses to past long-term events can help to predict the equilibrium climate sensitivity (ECS), or the equilibrium response of surface temperature to increasing atmospheric carbon dioxide. Reconstructions of ocean and land temperatures from the Last Glacial Maximum were used to determine the ECS range for that time period and help predict likely ESC values for recent climate data.

The article relates the authors' view on the study by C. Rosenzweig and colleagues about the impact of climate change, published within the issue. They remarks that study is the first to link observed global changes in physical and biological systems to human induced climate change from increasing greenhouse gases. They mentions the study demonstrated that changes in physical and biological systems are pervasive, and that these impacts lie in consistent with warming of the climate system.

Despite Schneider's claim, the method we use to estimate equilibrium climate sensitivity from multiple proxy-based reconstructions of the temperature in the Northern Hemisphere does account for uncertainty in reconstructions, including that associated with non-temperature and sampling error in the reconstruction. We arrive at a tighter constraint on climate sensitivity not by neglecting uncertainties, but by combining our wide-tailed proxy-based estimate with an independent estimate of climate sensitivity based on twentieth-century warming. [ABSTRACT FROM AUTHOR]