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Anthropogenic climate change has triggered impacts on natural and human systems world-wide, yet the formal scientific method of detection and attribution has been only insufficiently described. Detection and attribution of impacts of climate change is a fundamentally cross-disciplinary issue, involving concepts, terms, and standards spanning the varied requirements of the various disciplines. Key problems for current assessments include the limited availability of long-term observations, the limited knowledge on processes and mechanisms involved in changing environmental systems, and the widely different concepts applied in the scientific literature. In order to facilitate current and future assessments, this paper describes the current conceptual framework of the field and outlines a number of conceptual challenges. Based on this, it proposes workable cross-disciplinary definitions, concepts, and standards. The paper is specifically intended to serve as a baseline for continued development of a consistent cross-disciplinary framework that will facilitate integrated assessment of the detection and attribution of climate change impacts.

Comprehending the causal relationships between shifting climatic patterns, dynamic vegetation cover, and altered hydrological cycles constitutes a fundamental prerequisite for developing adaptive strategies in water resources governance. We analyze changes in baseflow (BF) and stormflow (SF) in 3,388 watersheds globally in the response to changes in precipitation characteristics, vegetation (Normalized Difference Vegetation Index, NDVI), temperature, potential evapotranspiration, and the aridity index from 1982 to 2016, based on Random Forest Model simulations and Shapley Additive Explanations. We also evaluate the effects of anthropogenic climate change on changes in baseflow index (BFI, the ratio of baseflow to total streamflow) using the signal‐to‐noise ratio (SNR) method applied to multi‐model simulations from ISIMIP2b. Results show that the BF and SF in the majority of watersheds show consistent trends, but they also show the opposite trends in specific seasons. Over 60% of watersheds in the Northern Hemisphere experienced a decrease in BF contribution to the total streamflow during the June‐July‐August season. Minimum temperature and NDVI are the most important factors influencing changes in BF and SF. Minimum and maximum temperature, precipitation seasonality, and precipitation intensity show negative effects on the BF, and the impact of vegetation on the BFI varies from region to region. The contribution of BF to the total streamflow decreases significantly at the global scale under the impact of anthropogenic climate change, according to the SNR analysis. The interaction of climate and vegetation changes on changes in BF and SF should take into account to regional adaptation of climate change for the utilization of groundwater and surface water resources.

In July 2021, Typhoon In‐Fa produced record‐breaking extreme precipitation events (hereafter referred to as the 2021 EPEs) in central and eastern China, and caused serious socioeconomic losses and casualties. However, it is still unknown whether the 2021 EPEs can be attributed to anthropogenic climate change (ACC) and how the occurrence probabilities of precipitation events of a similar magnitude might evolve in the future. The 2021 EPEs in central (eastern) China occurred in the context of no linear trend (a significantly increasing trend at a rate of 4.44%/decade) in the region‐averaged Rx5day (summer maximum 5‐day accumulated precipitation) percentage precipitation anomaly (PPA), indicating that global warming might have no impact on the 2021 EPE in central China but might have impacted the 2021 EPE in eastern China by increasing the long‐term trend of EPEs. Using the scaled generalized extreme value distribution, we detected a slightly negative (significantly positive) association of the Rx5day PPA time series in central (eastern) China with the global mean temperature anomaly, suggesting that global warming might have no (a detectable) contribution to the changes in occurrence probability of precipitation extremes like the 2021 EPEs in central (eastern) China. Historical attributions (1961–2020) showed that the likelihood of the 2021 EPE in central/eastern China decreased/increased by approximately +47% (−23% to +89%)/+55% (−45% to +201%) due to ACC. By the end of the 21st century, the likelihood of precipitation extremes similar to the 2021 EPE in central/eastern China under SSP585 is 14 (9–19)/15 (9–20) times higher than under historical climate conditions. Plain Language Summary Central and eastern China experienced record‐breaking extreme precipitation events (EPEs) in July 2021. The summer maximum 5‐day accumulated precipitation (Rx5day) of the 2021 EPE in central (eastern) China exceeded the climatology during 1981–2010 by 116.8% (96.1%). Under climate conditions of 1961 and 2021 and based on observations, the 2021 EPE was estimated to be a 1‐in‐76‐year event and 1‐in‐212‐year event in central China, respectively, and a 1‐in‐>10,000‐year and a 1‐in‐256‐year event in eastern China, respectively. Here, we estimate the contribution of anthropogenic climate change (ACC) to precipitation extremes of a similar magnitude to the 2021 EPEs and project how their probability might change in the future, based on climate projections from Coupled Model Intercomparison Project Phase 6. We estimate that ACC is responsible for +47%/+55% of the decrease/increase in the occurrence probability of the 2021 EPE in central/eastern China. By the end of the 21st century under a high emission scenario, the probability of occurrence of precipitation extremes similar to the 2021 EPE in central/eastern China is projected to be 14/15 times larger than under historical climate conditions. Our results highlight that EPEs in central and eastern China are becoming more frequent and more extreme in response to increasing greenhouse gas emissions. Key Points Global warming might have no (a detectable) contribution to the occurrence probability of a precipitation extreme like the 2021 extreme precipitation event (EPE) in central (eastern) China Anthropogenic climate change contributed to +47%/+55% of the decrease/increase in the occurrence probability of the 2021 EPE in central/eastern China By the end of the 21st century, the likelihood of such event in central/eastern China would be increased by 14/15 times under SSP585

Hailstones and extreme precipitation generate substantial economic losses across the United States (US) and the globe. Their strong association with short‐lived, intense convective storms poses a great challenge in predicting their future changes. Here, we conducted model simulations at 1.2 km grid spacing for severe convective storms with large hail and heavy precipitation that occurred in two typical types of synoptic‐scale environments in spring seasons over the central US under both current and future climate conditions. We find that the responses of large hail (diameters >2.5 cm) to anthropogenic climate change (ACC) are markedly different between the hailstorms developed in the two types of synoptic‐scale environments, with over 110% increase in large hail occurrences for the frontal systems, whereas less than 30% increase for the Great Plains low‐level jet (GPLLJ) systems. This is explained by the larger increase in convective intensity and updraft width and a smaller increase in warm cloud depth in the frontal storms compared with the GPLLJ storms. Interestingly, the occurrences and intensity of heavy precipitation (rain rate >20 mm hr−1) in both types of systems are similarly sensitive to ACC (e.g., 40% and 33% increases in the occurrences for the frontal and GPLLJ systems, respectively). These results advance our knowledge of hail projection and have important implications for managing risks for future hail. Plain Language Summary Severe convective storms (SCSs) and associated weather hazards have caused significant property damage and economic losses worldwide. In a warming climate, how storms that presently produce hazardous weather will change and how anthropogenic warming will affect particular hazard types (e.g., hail) remain highly uncertain. Through high‐resolution (1.2‐km grid spacing) simulations of hailstorms in spring over the central United States for both current and future climate, we show that the hailstorms developed in the two typical types of synoptic environments have a contrasting response to climate warming. The hailstorms developed in the frontal environment are sensitive to future warming and produce much more occurrences of large hail, whereas those developed in the GPLLJ environment are not sensitive to climate warming. This study presents an important concept to study and understand the impacts of climate warming on hailstorms based on the synoptic weather systems for a specific region. Key Points Synoptic‐scale environments regulate the response of hail to anthropogenic climate change (ACC) The occurrence of large hail is sensitive to ACC in the frontal storms while they are not in the GPLLJ storms An enhanced trough and a small increase in warm cloud depth in the future climate explain the large impact on frontal storms

Agricultural research has fostered productivity growth, but the historical influence of anthropogenic climate change (ACC) on that growth has not been quantified. We develop a robust econometric model of weather effects on global agricultural total factor productivity (TFP) and combine this model with counterfactual climate scenarios to evaluate impacts of past climate trends on TFP. Our baseline model indicates that ACC has reduced global agricultural TFP by about 21% since 1961, a slowdown that is equivalent to losing the last 7 years of productivity growth. The effect is substantially more severe (a reduction of ~26–34%) in warmer regions such as Africa and Latin America and the Caribbean. We also find that global agriculture has grown more vulnerable to ongoing climate change.Agricultural productivity has increased historically, but the impact of climate change on productivity growth is not clear. In the last 60 years, anthropogenic climate change has reduced agricultural total factor production globally by 21%, with stronger impacts in warmer regions.

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change.Current and future climate change is expected to impact human health, both indirectly and directly, through increasing temperatures. Climate change has already had an impact and is responsible for 37% of warm-season heat-related deaths between 1991 and 2018, with increases in mortality observed globally.

An assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.

Studies showing that scepticism about anthropogenic climate change is shaped, in part, by conspiratorial and conservative ideologies are based on data primarily collected in the United States. Thus, it may be that the ideological nature of climate change beliefs reflects something distinctive about the United States rather than being an international phenomenon. Here we find that positive correlations between climate scepticism and indices of ideology were stronger and more consistent in the United States than in the other 24 nations tested. This suggests that there is a political culture in the United States that offers particularly strong encouragement for citizens to appraise climate science through the lens of their worldviews. Furthermore, the weak relationships between ideology and climate scepticism in the majority of nations suggest that there is little inherent to conspiratorial ideation or conservative ideologies that predisposes people to reject climate science, a finding that has encouraging implications for climate mitigation efforts globally.

Climate change is expected to impact the functioning of the entire Earth system. However, detecting changes in ecosystem dynamics and attributing such change to anthropogenic climate change has proved difficult. Here we analyse the vegetation dynamics of 100 sites representative of the diversity of terrestrial ecosystem types using remote-sensing data spanning the past 40 years and a dynamic model of plant growth, forced by climate reanalysis data. We detect a change in vegetation activity for all ecosystem types and find these changes can be attributed to trends in climate-system parameters. Ecosystems in dry and warm locations responded primarily to changes in soil moisture, whereas ecosystems in cooler locations responded primarily to changes in temperature. We find that the effects of CO2 fertilization on vegetation are limited, potentially due to masking by other environmental drivers. Observed trend switching is widespread and dominated by shifts from greening to browning, suggesting many of the ecosystems studied are accumulating less carbon. Our study reveals a clear fingerprint of climate change in the change exhibited by terrestrial ecosystems over recent decades.An analysis fusing satellite data with a process-based model of plant growth attributes changes in vegetation activity across terrestrial ecosystems to climatic changes.

Models show that even if global temperature rise can be limited to 1.5 degrees Celsius, only about 65 per cent of glacier mass will remain in the high mountains of Asia by the end of this century, and if temperatures rise by more than this the effects will be much more extreme. Climate target confronts glacier fate The Paris Agreement advocates that humanity should consider limiting global warming to no more than 1.5 degrees Celsius (°C) above pre-industrial temperatures, well below the previously discussed threshold of 2 °C. The announcement sparked a surge of research to understand the practicality and implications of the lower limit. Here, Philip Kraaijenbrink and colleagues simulate the effect of warming on the glaciers in the high mountains of Asia and show that, in a world that warms by just 1.5 °C, about 65 per cent of glacier mass will remain by 2100. But keeping warming below the 1.5 °C threshold is an ambitious goal. At the other extreme, scenarios that include continued high rates of greenhouse gas production instead suggest that only about 35 per cent of mass will remain by 2100. Glaciers in the high mountains of Asia (HMA) make a substantial contribution to the water supply of millions of people 1 , 2 , and they are retreating and losing mass as a result of anthropogenic climate change 3 at similar rates to those seen elsewhere 4 , 5 . In the Paris Agreement of 2015, 195 nations agreed on the aspiration to limit the level of global temperature rise to 1.5 degrees Celsius ( °C) above pre-industrial levels. However, it is not known what an increase of 1.5 °C would mean for the glaciers in HMA. Here we show that a global temperature rise of 1.5 °C will lead to a warming of 2.1 ± 0.1 °C in HMA, and that 64 ± 7 per cent of the present-day ice mass stored in the HMA glaciers will remain by the end of the century. The 1.5 °C goal is extremely ambitious and is projected by only a small number of climate models of the conservative IPCC’s Representative Concentration Pathway (RCP)2.6 ensemble. Projections for RCP4.5, RCP6.0 and RCP8.5 reveal that much of the glacier ice is likely to disappear, with projected mass losses of 49 ± 7 per cent, 51 ± 6 per cent and 64 ± 5 per cent, respectively, by the end of the century; these projections have potentially serious consequences for regional water management and mountain communities.