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Emergence of heat extremes attributable to anthropogenic influences
Abstract
Climate scientists have demonstrated that a substantial fraction of the probability of numerous recent extreme events may be attributed to human-induced climate change. However, it is likely that for temperature extremes occurring over previous decades a fraction of their probability was attributable to anthropogenic influences. We identify the first record-breaking warm summers and years for which a discernible contribution can be attributed to human influence. We find a significant human contribution to the probability of record-breaking global temperature events as early as the 1930s. Since then, all the last 16 record-breaking hot years globally had an anthropogenic contribution to their probability of occurrence. Aerosol-induced cooling delays the timing of a significant human contribution to record-breaking events in some regions. Without human-induced climate change recent hot summers and years would be very unlikely to have occurred.
... Events attributable to climate change are being detected at the present-day level of global warming of about 1.1°C above the pre-industrial period (King, Black, et al. 2016;Herring et al. 2018;Otto et al. 2020). As a result of unabated greenhouse gas emissions and current rates of warming, the global mean temperature is rising by about 0.2°C per decade (IPCC 2018), which causes more pronounced sea-level rise, heat, floods, droughts and other manifestations of climate change (Nauels et al. 2019;Dottori et al. 2018;Schleussner, Deryng, et al. 2018;IPCC 2018). ...
... The recent IPCC Special Report on Global Warming of 1.5°C (IPCC 2018) has underscored the substantial differences in climate impacts between 1.5°C and 2°C that could materialize already before mid-century. Tropical regions will be bearing the brunt of these differences (Schleussner, Lissner, et al. 2016;Schleussner, Deryng, et al. 2018;King and Harrington 2018) and will also be the regions where the anthropogenic climate change is emerging the fastest against the background of natural variability (King, Black, et al. 2016 Uncertainties related to trajectories of future vulnerability have been found to dominate climate impacts in the near term (Hallegatte et al. 2015), but will also shape the end-of-century climate impacts (Hinkel, Vuuren, et al. 2012 ...
... Many areas of the world are experiencing intensifying climate impacts while trying to achieve multiple socio-economic development goals. The effects of anthropogenic climate change will be felt in these regions already in the near term(King, Black, et al. 2016), implying that adaptation actions are inevitable to reduce damages before the mitigation efforts show effect. With the need for adaptation apparent on both near and long-term time scales, it is important to understand the factors which act as barriers to building adaptive capacity and regard them in conjunction with broader development objectives. ...
Bei den Schätzungen der künftigen Auswirkungen bleiben die globalen Ungleichheiten der sozioökonomischen Bedingungen meist unberücksichtigt, die für die tatsächliche Fähigkeit der Systeme, viele der Anpassungsmaßnahmen umzusetzen, entscheidend sein werden. Um das zu erwartende Ausmaß der Anpassung auf der Grundlage wirtschaftlicher, finanzieller, menschlicher, technologischer und anderer Kapazitäten besser bestimmen zu können, sollten Projektionen der Klimaauswirkungen und der daraus resultierenden Verluste und Schäden die Koevolution zwischen Klimagefahren und sozioökonomischer Entwicklung berücksichtigen. In dieser Arbeit werden verschiedene Bereiche der Klimawissenschaft miteinander verknüpft, um ein Instrumentarium zur besseren Darstellung der Anpassung in quantitativen Modellierungsinstrumenten anzubieten. Der Ansatz bettet die sozioökonomischen Barrieren in den Szenariorahmen der Shared Socioeconomic Pathways (SSPs) ein, um quantitative Pfade der Anpassungsfähigkeit zu erstellen. Die Integration der Anpassungsfähigkeit in den Szenarioraum ermöglicht eine differenziertere Operationalisierung der Anpassung in der quantitativen Modellierung. Im ersten Teil der Arbeit werden zwei Erweiterungen des Szenariorahmens vorgestellt, die sich auf Indikatoren für die Regierungsführung und die Gleichstellung der Geschlechter als zwei der wichtigsten Hindernisse für die Anpassung konzentrieren. Im zweiten Teil werden zwei Anwendungen der Anpassungsfähigkeit für die Sektoren Gesundheit und Landwirtschaft vorgestellt, die den Zusammenhang zwischen sozioökonomischen Bedingungen und der unterschiedlichen Anfälligkeit für mögliche Klimastressoren aufzeigen. Das hier vorgestellte Toolkit eignet sich in erster Linie für den Einsatz in quantitativen Bewertungen von Auswirkungen und alternativen politischen Optionen, um anpassungsrelevante Informationen einzubeziehen, damit der Klimawandel unter verschiedenen sozioökonomischen Szenarien robuster dargestellt werden kann.
... whether observational records are being analysed or the type of climate modelling framework used to interrogate these changes. However, limited research (King et al. 2016) has considered how this factual-versus-counterfactual binary framework can be expanded upon to consider the evolution of risks from events witnessed over the last century, despite the fact that many of these historical events also caused significant damages at the time. Is it the case that only events which are occurring today carry a statistically detectable signal of anthropogenic climate change, or have there been events in the past which were already more likely to occur as a result of human influences at that time? ...
... Meanwhile, for every 20-year period since 1976-1995, there are substantive increases in the likelihood of witnessing such circulation analogues, with probability ratios reaching between three and six for in the most recent decades. While these results appear to qualitatively resemble corresponding changes in the Atlantic Meridional Oscillation over the same period (Sanderson et al. 2017), decomposing the relative effects of low-frequency modes of variability versus changes to European aerosol or greenhouse gas emissions (King et al. 2016;Undorf et al. 2018) is beyond the scope of this analysis. ...
... b Shows equivalent results but for the 1000-member bootstrap ensemble only ratios through the twentieth century, are proportionally more likely to emerge for those extreme events which persisted over a longer number of days. Such results are qualitatively equivalent to previous research finding a robust anthropogenic signal in the occurrence of exceptionally hot years over a specific location, yet finding a negligible attributable signal when looking at any of the constituent seasons (King et al. 2016): the former distribution is inherently narrower, so less of a signal is required for statistically significant differences to emerge. ...
The science of extreme event attribution has rapidly expanded in recent years, with numerous studies dedicated to determining whether and to what extent anthropogenic climate change has increased the likelihood of specific extreme weather events occurring. However, the majority of such studies have focussed on extreme events which have occurred in the recent past (usually within the past 10 years) while minimal research efforts have considered the multitude of high-impact extreme climatic events which occurred throughout the instrumental record. This study proposes a framework to quantify how the likelihood of witnessing meteorological characteristics reminiscent of the 1947 Central European heatwave have evolved over time. We specifically examine circulation analogues as a tool to understand the relative role of dynamical and thermodynamic contributions to changes in the probability of experiencing similar heatwave events. Using a reanalysis-based dataset, our results show changes in the frequency of 1947-like extreme heat throughout the twentieth century to be highly sensitive to methodological choices, particularly in the context of disaggregating dynamic and thermodynamic changes in the risk of extreme heat. Evidence also suggests clear decadal variability in the occurrence of circulation patterns conducive to the 1947 heatwaves. Finally, we discuss how to appropriately consider the time-evolution of attribution statements, as well as the broader limitations of employing circulation analogues as a method to interrogate the dynamical contribution to the probability ratio of an extreme event.
... Climate change is also increasing the frequency, intensity and duration of marine heatwaves, which are defined as prolonged periods of anomalously high sea surface temperature . Thirty-five percent of coastal marine environments have already experienced more intense and frequent extreme temperatures since the start of the 20th century (Lima and Wethey 2012), with heatwaves expected to further increase in severity and frequency as climate change advances (King et al. 2016;Frölicher et al. 2018). In addition to causing rapid warming, higher atmospheric CO 2 concentrations increase the CO 2 content of seawater, by increasing the uptake of CO 2 at the ocean's surface (Doney et al. 2009). ...
... Coastal habitats are more susceptible to heatwaves and elevated CO 2 events than the open ocean (Hoegh-Guldberg et al. 2014). Additionally, nearshore environments are expected to experience more severe and frequent heatwaves in the future, even under the most conservative CO 2 emission scenarios (King et al. 2016;Frölicher et al. 2018). In the Indo-Pacific region, notable heatwaves have occurred on Ningaloo Reef, Western Australia in 2011 (+ 3 °C average over 5 weeks) (Pearce and Feng 2013), the northeast Pacific in 2013-2015 (reaching + 2.5 °C, February 2014) (Di Lorenzo and Mantua 2016) and across northern Australia in 2016-2017 (reaching + 2 °C and lasting for 3 months) (Benthuysen et al. 2018). ...
As climate change advances, coastal marine ecosystems are predicted to experience increasingly frequent and intense heatwaves. At the same time, already variable CO2 levels in coastal habitats will be exacerbated by ocean acidification. High temperature and elevated CO2 levels can be stressful to marine organisms, especially during critical early life stages. Here, we used a fully cross-factored experiment to test the effects of simulated heatwave conditions (+ 4 °C) and elevated CO2 (1000 µatm) on the aerobic physiology and swimming performance of juvenile Australasian snapper, Chrysophrys auratus, an ecologically and economically important mesopredatory fish. Both elevated temperature and elevated CO2 increased resting metabolic rate of juvenile snapper, by 21–22% and 9–10%, respectively. By contrast, maximum metabolic rate was increased by elevated temperature (16–17%) and decreased by elevated CO2 (14–15%). The differential effects of elevated temperature and elevated CO2 on maximum metabolic rate resulted in aerobic scope being reduced only in the elevated CO2 treatment. Critical swimming speed also increased with elevated temperature and decreased with elevated CO2, matching the results for maximum metabolic rate. Periods of elevated CO2 already occur in the coastal habitats occupied by juvenile snapper, and these events will be exacerbated by ongoing ocean acidification. Our results show that elevated CO2 has a greater effect on metabolic rates and swimming performance than heatwave conditions for juvenile snapper, and could reduce their overall performance and potentially have negative consequences for population recruitment.
... Currently, event attribution studies mostly focus on a single event that occurred very recently. While King et al (2016) examined historical hot extremes, finding a significant human contribution to the probability of record-breaking global temperature events as early as in the 1930s, examining historical extreme precipitation has been lacking. Here, we conduct an attribution study on the four most destructive extreme precipitation events in the MLYRV since the early 20th century. ...
With the recurrence of high-impact extreme weather and climate events and the growing demands by the public to know the causes after the events, event attribution has emerged as a frontier of climate change research. Typically, an event attribution study focuses on one individual extreme event that has just occurred. Studies rarely examine human influence on multiple extreme events in different times of the past. Here we conduct a comprehensive attribution analysis on a number of the heaviest precipitation events in the Yangtze River Valley (YRV) during the past 100 years. We start by defining extreme precipitation events as the heaviest precipitation over a fixed area size that is of direct relevance to flood preparedness and management. When examining the events over the historical time, we allow the precise locations of the area to change in different years. Four extremely strong events are identified, and they happened in the summer of 1931, 1954, 1998 and 2020. A clear difference in the impacts of greenhouse gases (GHGs) and anthropogenic aerosols (AAs) on the events was found. Their impacts were negligible in the early period and became more and more discernible since the late 20th century. The temporal change of human influence on the events shows gradual strengthening impacts of GHGs and AAs with time. Their competing effects led to a slight human influence and then gradually increasing influence on extreme precipitation after the 21st century. GHGs have exerted a larger influence on short-duration precipitation events while AAs have had a larger influence on monthly mean precipitation. The more extreme the precipitation event, the clearer the anthropogenic influence.
... India has recently witnessed a rise in moist heat extremes, which adversely impacted public health (Im et al., 2017;Mazdiyasni et al., 2017;Mishra et al., 2017Mishra et al., , 2020. Due to rising temperature and population, moist heat stress is projected to increase under the warming climate (Coffel et al., 2017;King et al., 2016;Knutson & Ploshay, 2016;T. K. R. Matthews et al., 2017a). ...
Moist heat stress can lead to the inability of the human body to cool itself due to the impact of high temperature and humidity. The co-occurrence of tropical cyclones (TCs) and moist heat stress has considerable implications for India's dense population and infrastructure. However, the crucial linkage between TCs and moist heat extremes remains unrecognized. We used the cyclone eAtlas and ERA5 reanalysis to examine the temporally compounding TC and moist heat extremes over India from 1980 to 2021. We find that TC-Heat stress events in India have increased recently, which can be attributed to the high-intensity TCs originating from the Arabian Sea. The risk of TC-Heat stress events is higher (than in other parts of the world) in India due to an overlap of peak moist heat and TCs occurrence during the pre-monsoon (April-June) season. Landfalling TCs alter the thermodynamic environment causing the moist heat to peak over the region with increased frequency and intensity. The direct and compounded influence of TCs on moist heat can have substantial implications.
... A significant number of coral reef fish commence spawning just before, or during, the warmer months of the year (Domeier and Colin 1997;Russell 2001); therefore, larvae develop during periods most susceptible to marine heatwaves (MHW). Climate change is causing average sea surface temperature to rise and increasing the frequency and occurrence MHWs in summer (King et al. 2016;Hoegh-Guldberg et al. 2018;Pörtner et al. 2019). Abnormally warm days in marine environments have increased approximately 50% over the last century (Oliver et al. 2018), with the probability of a MHW occurring currently being ~ 9 times higher than in preindustrial times (Frölicher et al. 2018). ...
The success of individuals during the pelagic larval phase is critical to maintaining healthy and viable populations of coral reef fishes; however, it is also the most environmentally sensitive and energetically demanding life stage. Climate change is increasing the frequency and intensity of marine heatwaves, which could have significant effects on the development and survival of larval coral reef fishes. However, little is known about how the larvae of pelagic-spawning coral reef fishes will be affected due to the difficulty of spawning and rearing these species in captivity. In this study, we tested how elevated temperatures, similar to those occurring during a marine heatwave, affected the yolk utilization, growth, and survival of larval, Lutjanus carponotatus , a common mesopredatory fish on Indo-west Pacific coral reefs. Eggs and larvae were reared at a current-day average summer temperature (28.5 °C) and two elevated temperatures (30 °C and 31.5 °C) until 14 d post-hatch (dph). Larvae in the elevated temperatures depleted their yolk reserves 39% faster than at the control temperature. The standard length of larvae was 55% (30 °C) and 92% (31.5 °C) longer in the elevated temperature treatments than the control temperature at 14 dph. Conversely, survival of larvae was 54% (30 °C) and 68% (31.5 °C) lower at elevated temperatures compared with the control temperature. This study provides new insights as to how the early life stages of coral reef fishes could be affected by ocean warming and marine heatwaves, with implications for their population dynamics.
... The changes in LULC and ESV losses result in increased GHG emissions in the atmosphere.Several studies quantified the impacts of human-led increased GHG emissions on extreme heat events. For example, researchers claimed that along with several past records of extreme heat events, the record-breaking heat events in Australia that occurred in summer of1997-1998 and 2012-2013 were largely attributed to Chapter 3: Identifying the major land use changes that occur in peri-urban areas and their implications on climate change risk 147 anthropogenic influences(King et al., 2016). On that very point, the record-breaking Australian hot summers of1997-1998 and 2012-2013 are estimated to have a minimum of seven-fold and five-fold increase, respectively, caused by anthropogenic climate change(Lewis & Karoly, 2013).Furthermore, our analysis reveals that during the last decade (2010-2020), along with the declining precipitation trend, extreme heat events have also intensified and surpassed the previous record of extreme hot events. ...
... With such a wide range of climates, Australia also experiences a great diversity of climatic extremes [2,5,7]. Australia regularly experiences extremes in precipitation and temperature: from severe droughts to intense precipitation [8][9][10][11][12][13] and from increases in hot extremes and decreases in cold extremes [14][15][16]. These extremes have a substantial impact on Australia's unique flora and fauna [17], agriculture [18], urban infrastructure [19], and human health [20]. ...
Australia experiences a variety of climate extremes that result in loss of life and economic and environmental damage. This paper provides a first evaluation of the performance of state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs) in simulating climate extremes over Australia. Here, we evaluate how well 37 individual CMIP6 GCMs simulate the spatiotemporal patterns of 12 climate extremes over Australia by comparing the GCMs against gridded observations (Australian Gridded Climate Dataset). This evaluation is crucial for informing, interpreting, and constructing multimodel ensemble future projections of climate extremes over Australia, climate-resilience planning, and GCM selection while conducting exercises like dynamical downscaling via GCMs. We find that temperature extremes (maximum-maximum temperature -TXx, number of summer days -SU, and number of days when maximum temperature is greater than 35 °C -Txge35) are reasonably well-simulated in comparison to precipitation extremes. However, GCMs tend to overestimate (underestimate) minimum (maximum) temperature extremes. GCMs also typically struggle to capture both extremely dry (consecutive dry days -CDD) and wet (99th percentile of precipitation -R99p) precipitation extremes, thus highlighting the underlying uncertainty of GCMs in capturing regional drought and flood conditions. Typically for both precipitation and temperature extremes, UKESM1-0-LL, FGOALS-g3, and GCMs from Met office Hadley Centre (HadGEM3-GC31-MM and HadGEM3-GC31-LL) and NOAA (GFDL-ESM4 and GFDL-CM4) consistently tend to show good performance. Our results also show that GCMs from the same modelling group and GCMs sharing key modelling components tend to have similar biases and thus are not highly independent.
... Observations have shown that the frequency, intensity, and duration of extreme heat events have increased significantly around the world over the past decades (Perkins-Kirkpatrick and Lewis 2020, Ma and Yuan 2021, Markonis et al 2021, Mukherjee and Mishra 2021. Numerous studies have attributed the increased extreme heat events to anthropogenic global warming caused by cumulative of anthropogenic greenhouse gas (GHG) emissions (Stott et al 2004, Otto et al 2012, Perkins et al 2014, King et al 2016, Wang et al 2021. ...
To mitigate global warming and the resulting climate risk, many countries have accelerated the optimization of industrial structures and mixture of energy type in an attempt to achieve carbon neutrality by the second half of the 21st century. Here, we present the first assessment of the quantitative benefits of population exposure to extreme heat (defined by the heat index) during 2040-2049 under two scenarios of global carbon neutrality by 2060 and 2050, i.e., moderate green (MODGREEN) and strong green (STRGREEN) recovery scenarios, relative to the baseline scenario of Shared Socioeconomic Pathway (SSP) 2-4.5. Global mean extreme heat days increase by 12.1 days/year (108%) during 2040-2049 under the SSP2-4.5 scenario relative to the historical period (1995-2014). The aggravating extreme heat events could be mitigated by as much as 12% and 18% during 2040-2049 under the MODGREEN and STRGREEN scenarios, respectively. Following changes in extreme heat days, global population exposure to extreme heat is mitigated by 27.3 billion person-days (7%) in the MODGREEN scenario and 39.9 billion person-days (11%) in the STRGREEN scenario during 2040-2049 relative to the SSP2-4.5 scenario. Such benefits from these low-carbon policies are larger in regional hotspots, including India and Northern Africa, which have experienced high population growth and have extremely limited medical infrastructure. Moreover, an early carbon neutrality (2050 vs. 2060) could avoid 12.6 billion person-days exposure to extreme heat during 2040-2049. Our results provide an important scientific support for governments to drive early policymaking for climate change mitigation.
... Heat extremes are a natural part of our climate system but are getting hotter and longer in duration because of human-induced climate change (1). Heat extremes pose a threat to human and ecological health (2,3), and the chance of extreme heat events has increased in most regions around the world (4)(5)(6). Excess mortality due to extreme heat is well documented, with an average of 6 heat-related deaths per 100,000 residents each year in North America estimated for 2000-2019 (7). Heat impacts are magnified in cities, and with nearly 70% of the worlds' population expected to live in cities by 2050, the risks posed by extreme heat events will also increase (8,9). ...
In June 2021, western North America experienced a record-breaking heat wave outside the distribution of previously observed temperatures. While it is clear that the event was extreme, it is not obvious whether other areas in the world have also experienced events so far outside their natural variability. Using a novel assessment of heat extremes, we investigate how extreme this event was in the global context. Characterizing the relative intensity of an event as the number of standard deviations from the mean, the western North America heat wave is remarkable , coming in at over four standard deviations. Throughout the globe, where we have reliable data, only five other heat waves were found to be more extreme since 1960. We find that in both reanalyses and climate projections , the statistical distribution of extremes increases through time, in line with the distribution mean shift due to climate change. Regions that, by chance, have not had a recent extreme heat wave may be less prepared for potentially imminent events.
... Curiously, the decline of alien trout species in the mid and lower reaches of many Murray-Darling Basin rivers was arguably one of the first clear biological signals of anthropogenic global warming in south-eastern Australia, and aligns neatly with the first anthropogenic climate change signal detected in Australian climatic records (i.e. 1930s) (King et al. 2016). It is important in present day contemplations of alien trout impacts to recall that their dominance and attendant impacts once extended to the middle and even lower reaches of rivers in past decades. ...
CONTEXT: The Murray–Darling Basin—Australia’s largest river system—is heavily dominated by alien fish. Native fish species have suffered numerous localised extinctions and ~47% are listed on federal and/or state threatened species lists.
AIMS: This paper explores the hypothesis that alien fish and alien fish stockings can be the primary cause of decline and localised extinction of large-bodied native fish species, as opposed to habitat degradation and river regulation. The Lower Goodradigbee River, which is unregulated, in excellent instream health over the great majority of its course, and replete with high quality habitat, is utilised as a case study.
Methods: I investigated the hypothesis by synthesising historical records with contemporary scientific research and recent field observations. The role of alien fish species, particularly alien trout species (Oncorhynchus mykiss and Salmo trutta) and constant stockings of them, were closely examined.
RESULTS: Data support the hypothesis that domination by alien trout species and their continual stocking have lead to historical declines and localised extinctions of large-bodied native fish species. Continued alien trout stockings, along with more recent invasions of alien carp (Cyprinus carpio) and alien redfin perch (Perca fluviatilis), are inhibiting native fish recovery. A suspected field sighting of the alien fish pathogen atypical Aeromonas salmonicida is reported, and the status of the declining native crayfish Murray cray (Euastacus armatus), and potential alien fish impacts upon them, are examined.
CONCLUSIONS: The impacts of alien fish and alien fish stocking in Australia require major re-evaluation and dedicated research.
IMPLICATIONS: It is strongly recommended that stocking of alien trout into the Lower Goodradigbee River for angling cease in order to conserve surviving native fish and Murray cray populations. Conservation stockings to effect a Murray cod (Maccullochella peelii) recovery in the Lower Goodradigbee River are warranted.
... warmer than those experienced in 1950 in the Goondiwindi and Walgett regions of the Northern Grains Region (NGR; Crimp and Howden 2019). This shift to hotter temperatures and more extreme high-temperature events has occurred across all seasons of the year and has led to many record-breaking hot summers and years (King et al. 2016). ...
A temperature-controlled glasshouse study was conducted to evaluate the influence of elevated temperature (eT – 34/24 ± 2°C) on the growth and glyphosate susceptibility of windmill grass (Chloris truncata R.Br.), common sowthistle (Sonchus oleraceus L.), and flaxleaf fleabane [Conyza bonariensis (L.) Cronquist]; and to determine the morpho-physiological factors involved in differential glyphosate tolerance under eT. Results showed that elevation of temperature from ambient temperature (aT – 28/20 ± 2°C) to 34/24 ± 2°C increased growth and biomass production of C. truncata. In contrast, eT suppressed growth of S. oleraceus and C. bonariensis, resulting in fewer, thicker, and smaller leaves with reduced stomatal conductivity and less total plant biomass. In terms of herbicide susceptibility, the responses to glyphosate under different temperature regimes were species- and rate-specific. Slight variations in glyphosate susceptibility were observed when sprayed at sub-lethal rates at eT. Under eT, C. truncata, S. oleraceus, and C. bonariensis required 1.5, 2.0-, and 1.6-times higher glyphosate rates, respectively, to suppress biomass by 50% compared with plants grown at aT. Depending upon the species and glyphosate rate, differences in leaf characteristics (i.e. leaf chlorophyll content, leaf area/thickness, and stomatal conductance) could have promoted or delayed glyphosate activity under eT over the period, especially at sub-lethal rates. Overall, the glyphosate efficacy was unaffected since herbicide within the recommended rates completely controlled all tested weed species under both temperatures.
... The consecutive occurrence of daytime and nighttime hot extremes (COHs) is widely used as a measure of the persistence of an extremely hot spell to explain spatial and temporal variations in excess mortality during heatwaves (Chen and Zhai 2017;Raymond et al. 2020;Wang et al. 2020a, b;Xu et al. 2019). Previous studies found that prolonged heat could strongly amplify health effects by inhibiting the recovery from the daytime heat and by exacerbating the impact through sleep deprivation (Chen et al. 2018;Ho et al. 2017;King et al. 2016;Meehl and Tebaldi 2004;Pal and Eltahir 2015). COHs are often measured using daily or hourly near-surface air temperature (AT) as a single indicator (Chen and Zhai 2017;Horton et al. 2016;Vaidyanathan et al. 2016;Wang et al. 2020a, b). ...
Climate change leads to a more frequent occurrence of hot days (HDs) and hot nights (HNs). The consecutive occurrence of HDs and HNs (COHs) is often used as a measure of the persistence of an extremely hot spell. Nonetheless, the combined effect of air temperature and relative humidity on the changing COHs has never been studied. In this paper, we use an ensemble of global climate models and multiple thermal indices to robustly examine the combined effect of air temperature and relative humidity on COHs globally on an hourly basis. Our findings reveal that COHs show an increasing trend in the future and a strong latitudinal gradient increasing from high latitudes to the equator. Compared to COHs based on air temperature, the frequency of COHs based on perceived temperature is amplified by the combined effects of high temperature and humidity for both boreal and austral summers. To investigate the underlying mechanisms, we examine two different diurnal temperature ranges (DTRs), derived from air temperature and perceived temperature, for their corresponding types of COHs. Both DTRs are projected to increase in the future relative to the historical period from 1980 to 2004, but the DTR changes derived from perceived temperature are consistently larger than those derived from air temperature. Due to the nonlinearity in thermal indices, the perceived temperature in HDs and HNs rising faster than air temperature leads to a larger increase in perceived COHs. The COHs are further amplified by the increasing number of HNs and HDs that occur consecutively under wet conditions.
... The number of days exceeding the 90th percentile threshold (baseline period, have doubled between 1960 and 2017 across the European land area 11 , largely attributed to human-induced climate change [12][13][14] . According to Stott et al. 15 and IPCC 16 , it is likely that the human influence has more than doubled the risk of some past heatwaves, such as the 2003 European heatwave. ...
Extreme heat undermines the working capacity of individuals, resulting in lower productivity, and thus economic output. Here we analyse the present and future economic damages due to reduced labour productivity caused by extreme heat in Europe. For the analysis of current impacts, we focused on heatwaves occurring in four recent anomalously hot years (2003, 2010, 2015, and 2018) and compared our findings to the historical period 1981–2010. In the selected years, the total estimated damages attributed to heatwaves amounted to 0.3–0.5% of European gross domestic product (GDP). However, the identified losses were largely heterogeneous across space, consistently showing GDP impacts beyond 1% in more vulnerable regions. Future projections indicate that by 2060 impacts might increase in Europe by a factor of almost five compared to the historical period 1981–2010 if no further mitigation or adaptation actions are taken, suggesting the presence of more pronounced effects in the regions where these damages are already acute.
... A large part of regional manifestations of the Early 20th Century Warming occurred outside of the Arctic, including across the USA, western Europe, and the north and south Atlantic . There are indications that first record-breaking warm summers in 1930s can be attributed to human influence (King et al., 2016). ...
The Early 20th Century Warming (ETCW) in the northern high latitudes was comparable in magnitude to the present-day warming, yet occurred at a time when the growth in atmospheric greenhouse gases was rising significantly less than in the last 40 years. The causes of ETCW remain a matter of debate. The key issue is to assess the contribution of internal variability and external natural and human impacts to this climate anomaly. This paper provides an overview of plausible mechanisms related to the early warming period that involve different factors of internal climate variability and external forcing. Based on the vast variety of related studies, it is difficult to attribute ETCW in the Arctic to any of major internal variability mechanisms or external forcings alone. Most likely it was caused by a combined effect of long-term natural climate variations in the North Atlantic and North Pacific with a contribution of the natural radiative forcing related to the reduced volcanic activity and variations of solar activity as well as growing greenhouse gases concentration in the atmosphere due to anthropogenic emissions.
... It could be seen from Fig. 6 that FAR results of models significantly differ, which shows the appropriateness of individual assessment of the models. Unlike many of the attribution studies that have large scales, such as Fischer and Knutti (2015) and King et al. (2016), this study implements a local scale study, necessary for urban flood analyses. Restricting the analysis to a grid cell of global climate models for local impact studies however leads to a high level of internal variability compared to larger scales. ...
This study proposes a framework for the attribution analysis of urban flooding to historical anthropogenic change impacts using real (historical) and counterfactual (natural) simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) general circulation models (GCMs). A cluster analysis is implemented to select independent GCMs and to decrease the high computational time of the urban flood modeling. A two-step spatiotemporal statistical downscaling based on the generalized extreme value (GEV) distribution parameters is performed to meet the requirement of a fine-scale precipitation resolution for the urban flood simulations. Using the downscaled distribution parameters, the intensity-duration-frequency (IDF) curves and composite design storms for four return periods of 2, 10, 20 and 50 years are created to be used as the inputs of an InfoWorks ICM hydrodynamic model for a case study in Antwerp city, Belgium. The fraction of attributable risk (FAR) framework and the causal counterfactual probability theory are used to quantify anthropogenic climate influences on urban pluvial flooding. The results show that the GEV parameters of location and scale nicely follow the power relation, providing an opportunity for the temporal downscaling of precipitation extremes. A disagreement is found between the GCMs on the contribution of anthropogenic climate factors on pluvial flooding, some illustrating a higher probability of flooding due to anthropogenic climate impacts, and some a lower one. It can therefore be concluded that the urban flooding in Antwerp is not attributable to anthropogenic climate impacts.
... The metric FAR is better at representing a fraction of the probability of a particular HSW attributed to external influence. We extend the FAR framework to the global scale (Angélil et al., 2014;Fischer & Knutti, 2015;Frolicher et al., 2018;King et al., 2016) to determine how many fractions of HSWs occurring are attributable to human influence. Note that "fraction of HSWs" throughout the text should be interpreted as an anthropogenic contribution to the probability of HSWs, rather than some HSWs being anthropogenic and some not (Fischer & Knutti, 2015). ...
Wet bulb globe temperature (WBGT), a combined measure of temperature and humidity effects on thermal comfort, is used to define heat stress waves (HSWs). While emerging research has raised concerns on future changes in heat stress, for the first time, this study examines spatiotemporal changes in multiple HSW characteristics (intensity, duration, frequency, and cumulative mean intensity) in the 21st century under three emissions scenarios. It is the sustained nature of HSWs that impose more adverse impacts than extreme heat on a single day. HSWs are expected to be more intense, persistent, frequent, and influential due to anthropogenic influence. Models project the largest increases in multiple HSW characteristics will occur over the tropics and subtropics. The exception is maximum intensity, which displays a relative uniform increase over most global land areas. Analysis of regional population exposure to HSWs under different climate and socioeconomic scenarios emphasizes the importance of aggressive mitigation to minimize the potential impacts of HSWs. We further investigate how different regional HSW characteristics are projected to change relative to increasing global mean surface temperature (GMST). Our results confirm the varying rates and different trajectories at which regional HSWs change, independent of forcing pathway, strongly related to GMST. On both globally aggregated and regional scales, the maximum intensity and GMST are highly linearly associated, with an approximately 1:1 increase. However, the other three HSW characteristics are projected to change at a nonlinear rate per degree of GMST increase in general and display large regional variation in the rates of their changes.
... Although changes in both temperature (Kim et al., 2015;Seung-Ki, Min et al., 2013) and precipitation (Min et al., 2011;Zhang et al., 2013) extremes have been attributed at the global scale and large regional scale (King et al., 2016;Wang et al., 2017;Zwiers et al., 2010) to anthropogenic changes to the composition of the atmosphere, we do not evaluate model performance of simulating trends due to the high natural variability at sub-continental scales (Kay et al., 2015). ...
Using a non-stationary Generalized Extreme Value statistical method, we calculate selected extreme daily temperature and precipitation indices and their 20 year return values from the CMIP5 and CMIP6 historically forced climate models. We evaluate model performance of these indices and their return values in replicating similar quantities calculated from gridded land based daily observations. We find that at their standard resolutions, there are no meaningful differences between the two generations of models in their quality of simulated extreme daily temperature and precipitation.
... The TOE is defined as the time at which the climate change signal emerges from the natural variability of a given reference period, and this information is essential for developing timely climate change adaptation and mitigation strategies. Most existing studies focusing on the TOE have been conducted based on global climate projections (e.g., Giorgi and Bi 2009;King et al. 2015King et al. , 2016Knutson and Ploshay 2016;Sui et al. 2014). These studies have laid good foundations towards an understanding of the broad patterns of TOE, highlighting substantial differences across selected climate models and emission scenarios. ...
The information of when and where region-specific patterns in both mean and extreme temperatures leading to heat stress will emerge from the present-day climate variability is important to plan adaptation options, but to date studies on this issue still remain limited and fragmented. Here, we estimate the time of emergence (TOE) of temperature and wet-bulb temperature (Tw), a better indication of heat stress, using fine-scale, long-term regional climate model projections under the RCP2.6 and RCP8.5 scenarios across six different domains. Differently from previous studies, the TOE is determined using three methods applied on impact-relevant variables: two different signal-to-noise frameworks based on summer mean temperature and Tw and a statistical test to identify significant differences in daily extreme distributions. The TOE response to RCP2.6 and RCP8.5 with respect to the end of 20th century variability differs significantly regardless of which TOE metric is applied. For summer mean temperature, the land fraction reaching TOE is expected to exceed 90% by the 2050s under the RCP8.5, whereas the increase rate of land exposure to TOE tends to stagnate over time under the RCP2.6 so that more than 40% of land will not experience TOE by the end of the 21st century. Compared to temperature, the TOE of Tw is reached earlier in most of the wet tropics but is delayed in hot and dry regions because of the nonlinear response of Tw to humidity. For both temperature and Tw, the TOE appears earlier in regions with low baseline variability, such as in the tropics. Despite the uncertainties arising from the choice of TOE metrics, the vast majority of regions in Africa and southeast Asia experience TOE in the early 21st century under both the RCP2.6 and RCP8.5 scenarios, which stresses the urgent need for developing adequate adaptation strategies in these regions.
... Several studies quantified the impacts of human-led increased GHG emissions on extreme heat events. For example, researchers claimed that along with several past records of extreme heat events, the record-breaking heat events in Australia that occurred in summer of 1997-1998 and 2012-2013 were largely attributed to anthropogenic influences [65]. On that very point, the record-breaking Australian hot summers of 1997-1998 and 2012-2013 are estimated to have a minimum of seven-fold and five-fold increase, respectively, caused by anthropogenic climate change [66]. ...
Urban expansions to adjoining greenfield sites, particularly in metropolitan regions, have become a global occurrence. Such urbanization practice results in a significant loss in ecosystem services and triggers climate change—where these changes in land cover and emissions of certain pollutants are the fundamental drivers of climate change. Despite its crucial importance, little is known on how to quantify the impact of local drivers on anthropogenic climate change. This study aims to address the question of how the impacts of local drivers on anthropogenic climate change can be measured. The study utilizes a remote sensing approach to investigate the impacts of a period of over 30 years (1989–2019) in Brisbane, Australia and its adjoining local government areas. The methodological steps of the study are two-fold. First, we measure the greenfield development and corresponding ecosystem services losses and, then, we quantify the risk of such losses attributable to direct and indirect anthropogenic climate change. The findings of the study reveal the followings: (a) the utilized remote sensing method is a useful technique in quantifying the impacts of climate change; (b) over the last 30-year period, Brisbane and its adjoining areas encountered a total loss of about USD 4.5 billion in ecosystem services, due to direct and indirect anthropogenic climate change; (c) peri-urban areas encountered the biggest losses in ecosystem service values; (d) peri-urban areas experienced the highest greenhouse gas emission production levels, and; (e) ecosystem services should be backed up by robust urban management policies—this is critical for mitigating climate change.
... Extreme heat events often carry urban signature in which anthropogenic stressors play a critical role (King et al., 2016;Stott et al., 2004). For example, owing to the synergistic interplay of extreme heat and urban heat island (UHI) effect (Jiang et al., 2019), cities throughout the United States have experienced heat waves with increasing intensity and duration over the last few decades (Habeeb et al., 2015). ...
Plain Language Summary
Critical transitions have been identified in global and regional climate systems, during which a small perturbation can lead to a qualitative change. They are notoriously difficult to predict and can have potential catastrophic impacts on ecosystems and human society. However, certain characteristics may exist prior to such transitions and can serve as the early‐warning signals to predict critical transitions in climate systems. Here we investigate the early‐warning signals in global warming and regional heat waves based on temperature records. We identify clear early‐warning signals before the early 20th century global warming period and several heat waves during recent years. The early‐warning signals for heat waves are possibly due to the interplay of multiple environmental determinants, such as the drying soil during droughts and the heat accumulated in the atmosphere. Furthermore, we observe differences in the early‐warning signals between urban and rural temperature records. Our study highlights the presence of early‐warning signals days (years) prior to heat waves (abrupt global warming). With the higher frequency and intensity of heat wave events in a warming future, the results can be used to design mitigation and adaptation strategies beforehand to attenuate their negative impacts (such as heat stress) and proactively combat climate change.
... The number of unusually warm days (Tx90pct) increased by up to 10 days per decade between 1960 and 2018 in most of southern Europe and Scandinavia and a substantial fraction of the probability of recent heatwaves can be attributed to human-induced climate change (7). Heatwaves are projected to become more frequent and to last longer across Europe during this century (8). ...
The biophysical impact of extreme temperatures on the performance of workers is manifested by altering human physiology and cognition processes. This has a negative effect on the work capacity of the labour force, leading to temporarily lower labour productivity and economic output. Inspired by the emerging literature on bottom-up assessments of climate risks, this paper proposes a method that estimates , upon leveraging local-level heat stress impacts, the economy-wide cost of heatwaves by integrating regional-and sector-specific productivity losses into a regionalised general equilibrium model, thus enabling for market adaptation mechanisms. We study the most representative heatwave events occurring in Europe in the last two decades and analyse the implications of climate change to this area by combining highly resolved climate and socioeconomic projections. Our approach features a very detailed spatial and temporal precision: i) 274 regions (EU+EFTA countries) simultaneously analysed; ii) Wet Bulb Globe Temperature (WBGT) indicator retrieved every hour; iii) economic sectors classified according to their different heat exposure (in-door/outdoor activities and metabolic intensity load); iv) different heat-exposure functions analysed; v) two climate scenarios compared and; vi) average estimate costs for the period 2035-2064 produced. The integrated modelling tool proposed here can also help to assess the implementation of regional-sectoral occupational health and adaptation plans at the workplace. Heat stress | Labour productivity | CGE | Extreme weather | Climate change | Adaptation The environment has a clear influence on the way humans behave and perform. For example, air pollution (1) or excessive heat (2) negatively affect how daily routines are developed. This is manifested through biophysical and cognitive impacts that affect the capacity of learning (3) and interferes with the decision-making process (4). The negative consequences of heat exposure are expected to increase in the near future due to climate change (5). Quantifying the economic impact of these externalities on human activity is key to combat their effect with the design of effective adaptation plans and policies.
... The recent IPCC Special Report on Global Warming of 1.5 °C (ref. 1 ) has underscored the substantial differences in climate impacts between 1.5 °C and 2 °C that could materialize before mid-century. Tropical regions will bear the brunt of these differences [32][33][34] and will be the regions where the anthropogenic climate change is emerging the fastest against the background of natural variability 35 . Thus, while vulnerable countries will be striving for sustainable development and improving their adaptive capacity, climate impacts will continue to intensify. ...
Weak governance is one of the key obstacles for sustainable development. Undoubtedly, improvement of governance comes with a broad range of co-benefits, including countries’ abilities to respond to pressing global challenges such as climate change. However, beyond the qualitative acknowledgement of its importance, quantifications of future pathways of governance are still lacking. This study provides projections of future governance in line with the Shared Socioeconomic Pathways. We find that under a ‘rocky road’ scenario, 30% of the global population would still live in countries characterized by weak governance in 2050, while under a ‘green road’ scenario, weak governance would be almost entirely overcome over the same time frame. On the basis of pathways for governance, we estimate the adaptive capacity of countries to climate change. Limits to adaptive capacity exist even under optimistic pathways beyond mid-century. Our findings underscore the importance of accounting for governance in assessments of climate change impacts.
... Presently, temperature and precipitation amounts exceeding the range of historical variability are becoming increasingly more frequent (Hansen et al., 2012;Mora et al., 2013). Although the influence of surface temperature changes on average climate quantities (Hartmann et al., 2013) and changes in climate extremes (e.g., Betts et al., 2018;King et al., 2016;Sillmann et al., 2017) are both active fields of research, it is not yet clear how much of these changes that relate to forced shifts in mean climatology and how much that can be attributed to internal climate variability (Alexander & Perkins, 2013;Wills et al., 2018). Additionally, as GMST changes, so may the processes that underlie intrinsic variability on smaller spatial and temporal scales (Fatichi et al., 2016;Giorgi, 2002). ...
The climate is an aggregate of the mean and variability of a range of meteorological variables, notably temperature (T) and precipitation (P). While the impacts of an increase in global mean surface temperature (GMST) are commonly quantified through changes in regional means and extreme value distributions, a concurrent shift in the shapes of the distributions of daily T and P is arguably equally important. Here, we employ a 30‐member ensemble of coupled climate model simulations (CESM1 LENS) to consistently quantify the changes of regionally and seasonally resolved probability density functions (PDFs) of daily T and P as function of GMST. Focusing on aggregate regions covering both populated and rural zones, we identify large regional and seasonal diversity in the PDFs and quantify where CESM1 projects the most noticeable changes compared to the preindustrial era. As global temperature increases, Europe and the US are projected to see a rapid reduction in wintertime cold days, and East Asia to experience a strong increase in intense summertime precipitation. Southern Africa may see a shift to a more intrinsically variable climate, but with little change in mean properties. The sensitivities of Arctic and African intrinsic variability to GMST are found to be particularly high. Our results highlight the need to further quantify future changes to daily temperature and precipitation distributions as an integral part of preparing for the societal and ecological impacts of climate change and show how large ensemble simulations can be a useful tool for such research.
... Studies have adopted various approaches to understanding future extremes and provide valuable information about possible future changes in extremes typically of a magnitude that has already been observed. These approaches include, for example, i) quantifying changes in the characteristics of extremes attributable to specific forcings (e.g., King et al., 2017;Nangombe et al., 2018), ii) assessing changes in the frequency or duration of extremes in the future (e.g., Perkins, 2015), iii) process-based (dynamic and land-surface) understandings of changes (Zappa and Shepherd, 2017) and iv) determining the time in the future when current extremes can no longer be considered an outcome of natural climates (e.g., King et al., 2016). ...
Local- and regional-scale heat extremes can increase at a significantly greater rate than global mean changes, presenting challenges for human health, infrastructure, industry and ecosystems. We examine changes in regional absolute temperature extremes for a suite of global regions under 1.5 °C and 2 °C of warming above pre-industrial levels, as described by the Paris Agreement. We focus on area-average values of observed monthly averages of daily maximum and minimum temperatures in 12 regions and calculate the most extreme monthly records observed. Next, using a large ensemble (HAPPI; Half a Degree Additional warming, Prognosis, and Projected Impacts) of decade-long simulations both of the present day and stabilised at these higher warming thresholds, we explore how changes in temperature extremes temperatures scale with global mean warming in these timeslice simulations. In the models, we focus on the 99th percentile values of monthly maximum temperatures and the 1st percentile of the monthly minimum temperatures. We define and identify hotspots of warming for various global mean warming levels, where projected changes in regional extremes are greater than global mean temperature changes. We identify overall hotspots of extremes, which are regions where the tail of the temperature distribution (above 99th percentile) warms at a faster rate than the rest of the temperature distribution in response to mean global warming increase. For monthly maximum temperatures, Central Europe, North Asia, West and East North America experience the greatest projected increases in extremes relative to means, and for monthly minimum temperatures, Central, West, East and North Asia, and East North America are identified as extremes hotspots. Although the scaling of increasing extremes with global mean temperatures is regionally variable, all regions benefit from the reduced severity of monthly maximum temperatures under lower global warming thresholds.
... Furthermore, over the last century droughts and floods killed at least eleven and seven million people respectively while half a billion people were left requiring emergency aid 9 . Extreme heat events have impacted millions more 10 . Such factors fuel conflict and migration, and have stalled achievement of the United Nations Sustainable Development Goals 11 . ...
Drawing on recent advances, I examine the significance, and practical implications, of Central African forest for Africa’s climate and water.
... The potential effects of industrial carbon dioxide emissions on global temperature have been discussed since the late 19th century (Fleming, 1998), so the concept of global warming existed during both the historical and modern warming periods. Retrospective analyses show that warming effects were felt by the 1930s (King et al., 2016), and observed warming was described in the context of global climate change both in the contemporary scientific literature (Callendar, 1938) and the popular press (Molena, 1912;Talman, 1930). However, scientific consensus around global warming did not exist in the 1940s and 50s, and our historical observations reflect this uncertainly, expressing both an awareness and skepticism of climate change (Table 2). ...
Climate‐driven warming has both social and ecological effects on marine fisheries. While recent changes due to anthropogenic global warming have been documented, similar basin‐wide changes have occurred in the past due to natural temperature fluctuations. Here, we document the effects of rapidly changing water temperatures along the United States’ east coast using observations from fisheries newspapers during a warming phase (1945–1951) and subsequent cooling phase (1952–1960) of the Atlantic Multidecadal Oscillation, which we compared to similar recent observations of warming waters (1998–2017). Historical warming and cooling events affected the abundance of species targeted by fishing, the prevalence of novel and invasive species, and physical access to targeted species. Fishing communities viewed historical cooling waters twice as negatively as they did warming waters (72% vs. 35% of observations). Colder waters were associated with a decrease in fishing opportunity due to storminess, while warming waters were associated with the potential for new fisheries. In contrast, recent warming waters were viewed as strongly negative by fishing communities (72% of observations), associated with disease, reductions in abundances of target species, and shifts in distributions across jurisdictional lines. This increasing perception that warming negatively affects local fisheries may be due to an overall reduction of opportunity in fisheries over the past half century, an awareness of the relative severity of warming today, larger changes in American culture, or a combination of these factors. Negative perceptions of recent warming waters’ effects on fisheries suggest that fishing communities are currently finding the prospect of climate adaptation difficult.
... Ricke and colleagues (Ricke et al. 2016) have noted that many other specific impacts (like coral reef bleaching) follow a sigmoidal pattern of response, whereby the magnitude of change occurs rapidly with some amount of initial global warming, followed by progressively fewer additional changes after the exceedance of some threshold (since fewer healthy reefs remain to suffer subsequent temperature rises). Evidence also suggests that the evolution of the fraction of attributable risk associated with some specific extreme weather events will follow this saturation pathway (King et al. 2016;Harrington and Otto 2018). While there will be impacts that behave differently, if warming increases to the point that every new event will be more severe than some historical definition of 'extreme', then the percentage of damages from any of these new events which can be attributed to the underlying warming signal will often converge towards 100% (Christiansen 2015). ...
Addressing questions of loss and damage from climate change in courts is limited by many scientific, legal and political challenges. However, modifying existing extreme event attribution frameworks to resolve the evolution of the impacts of climate change over time will improve our understanding of the largest scientific uncertainties.
... Indeed, 2016 was identified as the hottest year in all 34 reputable global temperature datasets ( Knutson et al. 2018), and "seventeen of the 18 warmest 35 years on record have all been witnessed during this century" (WMO 2018). Consequently, several 36 studies have employed techniques from the field of probabilistic event attribution to quantify the 37 role of anthropogenic greenhouse gas emissions in changing the likelihood of experiencing such 38 record-breaking hot years ( King et al. 2016;Kam et al. 2016;Mann et al. 2017;King 2017;Knutson et 39 al. 2018). ...
Global-average temperatures are a powerful metric for both long-term climate change policy, and also to measure the aggregate fluctuations in weather experienced around the world. However, here we show how the consideration of anomalies in annual temperatures at the global land-average scale, particularly during extremely hot years, tends to overestimate the perceived severity of extreme heat actually felt by local communities during these events. Thus, when global-mean temperatures are used as a proxy to infer the role of climate change on the likelihood of witnessing hot years, the component of extreme event risk attributed to human influence can also be overstated. This study suggests multiple alternative approaches to characterise extreme weather events which have complex spatial signatures, each of which improve the representation of perceived experiences from the event when compared with the default approach of using area-averaged time-series. However, as the definition of an extreme event becomes more specific to the observed characteristics witnessed, changes are needed in the way researchers discuss the likelihood of witnessing 'similar events' with future climate change. Using the example of the 2016 hot year, we propose an alternative framework, termed the 'Time of Maximum Similarity', to show that events like the record-breaking annual temperatures of 2016 are most likely to be witnessed between 2010-2037, with hot years thereafter becoming significantly more severe than the heat of 2016.
... While it can be hard to attribute one extreme event to recent anthropogenic climate change, this is changing through developments in attribution science (e.g. King et al. 2016;Stott et al. 2017) but will often still require innovative ways of collecting long-term biological data such as citizen science programmes. ...
The effects of anthropogenic climate change on biodiversity are well known for some high‐profile Australian marine systems, including coral bleaching and kelp forest devastation. Less well‐published are the impacts of climate change being observed in terrestrial ecosystems, although ecological models have predicted substantial changes are likely. Detecting and attributing terrestrial changes to anthropogenic factors is difficult due to the ecological importance of extreme conditions, the noisy nature of short‐term data collected with limited resources, and complexities introduced by biotic interactions. Here, we provide a suite of case studies that have considered possible impacts of anthropogenic climate change on Australian terrestrial systems. Our intention is to provide a diverse collection of stories illustrating how Australian flora and fauna are likely responding to direct and indirect effects of anthropogenic climate change. We aim to raise awareness rather than be comprehensive. We include case studies covering canopy dieback in forests, compositional shifts in vegetation, positive feedbacks between climate, vegetation and disturbance regimes, local extinctions in plants, size changes in birds, phenological shifts in reproduction and shifting biotic interactions that threaten communities and endangered species. Some of these changes are direct and clear cut, others are indirect and less clearly connected to climate change; however, all are important in providing insights into the future state of terrestrial ecosystems. We also highlight some of the management issues relevant to conserving terrestrial communities and ecosystems in the face of anthropogenic climate change.
... The FAR was initially introduced to represent a fraction of the probability of individual observed events 33,37 . Here, we extend the FAR framework to the global scale 34,38,39 to represent the probability for a class of events exceeding a certain threshold over the globe. For a given MHW, the probability ratio can be interpreted as a change in the odds of the occurrence of local SST anomalies exceeding a certain local threshold. ...
Marine heatwaves (MHWs) are periods of extreme warm sea surface temperature that persist for days to months1 and can extend up to thousands of kilometres2. Some of the recently observed marine heatwaves revealed the high vulnerability of marine ecosystems3-11 and fisheries12-14 to such extreme climate events. Yet our knowledge about past occurrences15 and the future progression of MHWs is very limited. Here we use satellite observations and a suite of Earth system model simulations to show that MHWs have already become longer-lasting and more frequent, extensive and intense in the past few decades, and that this trend will accelerate under further global warming. Between 1982 and 2016, we detect a doubling in the number of MHW days, and this number is projected to further increase on average by a factor of 16 for global warming of 1.5 degrees Celsius relative to preindustrial levels and by a factor of 23 for global warming of 2.0 degrees Celsius. However, current national policies for the reduction of global carbon emissions are predicted to result in global warming of about 3.5 degrees Celsius by the end of the twenty-first century16, for which models project an average increase in the probability of MHWs by a factor of 41. At this level of warming, MHWs have an average spatial extent that is 21 times bigger than in preindustrial times, last on average 112 days and reach maximum sea surface temperature anomaly intensities of 2.5 degrees Celsius. The largest changes are projected to occur in the western tropical Pacific and Arctic oceans. Today, 87 per cent of MHWs are attributable to human-induced warming, with this ratio increasing to nearly 100 per cent under any global warming scenario exceeding 2 degrees Celsius. Our results suggest that MHWs will become very frequent and extreme under global warming, probably pushing marine organisms and ecosystems to the limits of their resilience and even beyond, which could cause irreversible changes.
... Weather and climate extremes with high impacts on society have received more attention recently (SedláčekJ and Knutti 2014; Bador et al. 2016;King et al. 2016;Lehner et al. 2016;Lin et al. 2016;Schleussner et al. 2016) as hottest-recorded temperatures, droughts, and floods have appeared with higher frequency. Therefore, it is important to effectively inform policy makers and communities impacted on the benefits of greenhouse gas mitigation; regions that will gain benefits from ToE delay and types of extreme events. ...
This study conducted an updated time of emergence (ToE) analysis of regional precipitation changes over land regions across the globe using multiple climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5). ToEs were estimated for 14 selected hotspots over two seasons of April to September (AS) and October to March (OM) from three RCP scenarios representing low (RCP2.6), medium (RCP4.5), and high (RCP8.5) emissions. Results from the RCP8.5 scenario indicate that ToEs would occur before 2040 over seven hotspots including three northern high-latitude regions (OM wettening), East Africa (OM wettening), South Asia (AS wettening), East Asia (AS wettening) and South Africa (AS drying). The Mediterranean (both OM and AS drying) is expected to experience ToEs in the mid-twenty-first century (2040-2080). In order to measure possible benefits from taking low-emission scenarios, ToE differences were examined between the RCP2.6 scenario and the RCP4.5 and RCP8.5 scenarios. Significant ToE delays from 26 years to longer than 67 years were identified over East Africa (OM wettening), the Mediterranean (both AS and OM drying), South Asia (AS wettening), and South Africa (AS drying). Further, we investigated ToE differences between CMIP3-based and CMIP5-based models using the same number of models for the comparable scenario pairs (SRESA2 vs. RCP8.5, and SRESB1 vs. RCP4.5). Results were largely consistent between two model groups, indicating the robustness of ToE results. Considerable differences in ToEs (larger than 20 years) between two model groups appeared over East Asia and South Asia (AS wettening) and South Africa (AS drying), which were found due to stronger signals in CMIP5 models. Our results provide useful information on the timing of emerging signals in regional and seasonal hydrological changes, having important implications for associated adaptation and mitigation plans.
Seit der industriellen Revolution haben Menschen durch Verbrennung von fossilen Energieträgern die Treibhausgaskonzentration in der Atmosphäre erhöht. Die daraus folgende Erderwärmung hat weitreichende Folgen für das Klima, unter anderem häufigere und intensivere Wetterextreme. Wegen ihrer gravierenden Auswirkungen auf die Gesellschaft, ist es von allgemeinem Interesse zu verstehen, wie der menschengemachte Klimawandel diese Wetterextreme beeinflusst. In dieser kumulativen Dissertation analysiere ich erst zwei komplexe Wettereignisse, die die Nahrungsmittelproduktion in Europa beeinträchtigen: Frosttage nach dem Beginn der Apfelblüte und Feuchte Frühsommerperioden nach warmen Wintern. In einer dritten Studie untersuche ich wie dynamische Klimaveränderungen in den mittleren Breiten der Nordhalbkugel zu beständigerem Sommerwetter beitragen. Schließlich beschäftige ich mich mit tropischen Stürmen im Nordatlantik und damit, wie sie von der globalen Erwärmung beeinflusst werden. Eine zentrale methodische Herausforderung in diesem Forschungsfeld ist, dass Wetterextreme per Definition selten sind und dass es aufgrund der starken internen Klimavariabilität schwierig ist, die Veränderungen zu quantifizieren, die auf den menschgemachten Klimawandel zurück zu führen sind. In dieser Arbeit verfolge ich zweigegenläufige Ansätze um mit dieser Herausforderung um zu gehen: 1) Ich verwende große Klimasimulationsensembles um den Effekt der internen Klimavariabilität aus zu glätten und dadurch die erzwungenen Veränderungen beim Apfelfrost und in der Persistenz zu ergründen. 2) Mit Methoden, die auf Beobachtungsdaten beruhen, quantifiziere ich den Einfluss der internen Klimavariabilität auf tropische Zyklone um dann einschätzen zu können, in welchem Maß der beobachtete Anstieg der tropischen Zyklonaktivität im Atlantik der internen Klimavariabilität oder erzwungenen Veränderungen zugeschrieben werden kann.
Urban air pollution is already a massive health problem, the extent of which has only recently been identified. Cities produce the majority of air pollution that affects our health. With new research identifying that there is no safe level of air pollution, trends in rapid urbanisation worldwide suggest that the overwhelming majority of the world’s population is breathing air that does not meet international guidelines. However, city dwellers’ health is not just affected by air pollution. The problem is compounded by climate extremes exacerbated by both urban heat and global climate change. Combined, these factors have significant detrimental and interconnected synergistic impacts on the health of a city and its inhabitants. This chapter examines how urbanisation can modify the meteorological conditions in a city, and as a consequence, the long-term local climate. In addition, this chapter examines how these regional and global impacts on climate can impact, and be impacted by, air pollution. Although cities make a significant contribution to emissions of both ambient and greenhouse gas air pollutants, they are also pivotal in providing solutions. This interaction between ambient air pollution, urban climate and climate change in our cities is discussed with regard to the seminal role that our cities could take to help, rather than harm, inhabitants’ health and well-being through supportive and forward thinking integrated urban design that will contribute to healthier cities.
High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the ‘Reasons for Concern’ framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5–2 °C and very high risks between 2–3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.
This chapter has two aims. First, it explores the implications of current and
future losses and damages from climate change on public finances. These
affect the ability of governments to pursue sustainable development and
poverty reduction priorities under a changing climate. Second, it examines
the critical roles of finance in reducing and managing the risks of losses and
damages, namely in risk reduction, retention and transfer. The chapter also
provides insights on the landscape of development finance directly or
indirectly supporting these efforts, recognising the important role of
humanitarian finance in supporting relief.
Signal-to-noise (S/N) ratios are a useful method to assess the significance of future climate change relative to past experiences. Most assessments of climate change emergence have focused on S/N ratios of annual mean temperatures. However, averaging the daily experiences of weather across space or time removes the climate variability actually felt by individuals, and thus presents a less informative view of the speed of current climate change. For example, S/N ratios of annual-mean temperatures experienced by the global population after only 1 ◦C of warming are larger than emergent changes in daily temperatures after 3 ◦C of warming, and generally four times more significant when comparing the same warming threshold. Here, I examine the emergence of S/N ratios in temperature at decision-relevant scales, with a focus on daily temperatures where people live. I find that 2 ◦C of global warming will lead to between 30% and >90% of the global population experiencing the emergence of unusual daily temperatures (>1σ), while it is very unlikely (90% confidence) that more than 60% of the global population will also experience the emergence of unfamiliar daily temperatures (>2σ).
Carbon nitride, as one of the metal-free photocatalysts, has aroused wide attention due to its low cost, easy preparation, and excellent optical response. However, challenges of the high recombination rate of electron-hole pair hindered their potential applications. Here, boron-doped carbon nitride nanotubes were designed and prepared by a simple hydrothermal and calcination route. Compared with the bulk carbon nitride, the control strategy forms the ordered nanotube structure, which greatly improved their specific surface area, exposed more active sites, and enhanced the graphitization degree. The transient fluorescence lifetime of tubular carbon nitride is twice as long as that of pure carbon nitride. Furthermore, boron doping carbon nitride nanotubes exhibited a 1.5-fold increase in a lifetime over tubular carbon nitride, which acts a synergistic role with nanotube architecture to further increases the carrier concentration and hinder the recombination of photogenerated electron-hole. Under the irradiation of visible light, the amount of hydrogen evolution of the optimum photocatalyst has achieved 22.1 mmol∙g⁻¹∙h⁻¹, which was 64 times that of the bulk carbon nitride and exhibited excellent stability. This work provides a promising strategy for the development of non-metallic doped carbon nitride nanotube photocatalysts for hydrogen evolution.
This briefing is a collaborative effort of the Lancet Countdown on Health and Climate Change, a global academic collaboration focused on tracking the links between health and climate change through a series of more than 45 indicators, and the European Environment Agency (EEA), an European Union agency tasked to provide sound, independent information on the environment. SUMMARY IMPACT AND POLICY CONTEXT » European countries are increasingly affected by weather and climate extremes, which lead to fatalities and affect human health and well-being. For example, more European countries suffered from wildfires in 2018 than previously recorded, including several in north and central Europe. » Vulnerability to heat extremes continues to rise in the World Health Organization (WHO) European Region, primarily due to a growing urban population, increasing incidence of underlying chronic conditions, and a growing number of people living to old age. In terms of mortality, the hot summer of 2003 resulted in an estimated 70,000 excess deaths in Europe, whilst the 2015 heatwaves caused over 3,275 deaths in France alone. Global excess mortality attributable to heat exposure in people over 65 is estimated to have increased by more than 50% during the period 2000-2018. » Climate change is altering ecological conditions, and some areas are becoming more suitable for various infectious diseases. In 2018, the environmental suitability for the transmission of dengue by its mosquito vector in European countries increased by over 40% compared to the 1950-1954 baseline. In the past five years, the proportion of coastline suitable for the transmission of Vibrio bacteria, which can cause gastroenteritis through the consumption of contaminated seafood and potentially lethal wound infections through direct exposure, has increased by 61% in the Baltic region, compared to a 1980s baseline. » Climate change impacts are addressed through key European Union (EU) strategies on adaptation and on health as well as through topic-specific policies. Emerging policies and initiatives under the European Green Deal suggest increasing integration between climate action and human health and well-being.
Climate change is modifying the way we design and operate water infrastructure, including reservoirs. A particular issue is that current infrastructure and reservoir management rules will likely operate under changing conditions different to those used in their design. Thus, there is a big need to identify the obsolescence of current operation rules under climate change, without compromising the proper treatment of uncertainty. Acknowledging that decision making benefits from the scientific knowledge, mainly when presented in a simple and easy-to-understand manner, such identification—and the corresponding uncertainty—must be clearly described and communicated. This paper presents a methodology to identify, in a simple and useful way, the time when current reservoir operation rules fail under changing climate by properly treating and presenting its aleatory and epistemic uncertainties and showing its deep uncertainty. For this purpose, we use a reliability–resilience–vulnerability framework with a General Circulation Models (GCM) ensemble under the four Representative Concentration Pathways (RCP) scenarios to compare the historical and future long-term reservoir system performances under its current operation rule in the Limarí basin, Chile, as a case study. The results include percentiles that define the uncertainty range, showing that during the 21st century there are significant changes at the time-based reliability by the 2030s, resilience between the 2030s and 2040s, volume-based reliability by the 2080s, and the maximum failure by the 2070s. Overall, this approach allows the identification of the timing of systematic failures in the performance of water systems given a certain performance threshold, which contributes to the planning, prioritization and implementation timing of adaptation alternatives.
The aim of the study is to determine statistical estimates for the distributions of average monthly and annual temperatures, as well as monthly and annual precipitation for the North-Western Black Sea coast during the climatic change intensification epoch. Parameters of the normal distribution for temperature, two- and three-parametric gamma distribution for precipitation, as well as trend characteristics, are analyzed. To determine the deviation of the values from the previous climatic period, the data of the Climate Cadastre of Ukraine (1961–1990) were used.
The results of the statistical analysis show that steady trend towards an increase in annual air temperatures exists at all stations during the period (2000-2018). In the time course of these characteristics, there is a clearly pronounced separation into two periods with the transition point in 2007. The average monthly air temperatures for the period generally exceed the same values for 1961-1990, and this is especially evident for the summer months.
Time distributions of monthly precipitation are spatially heterogeneous. It was found for Odesa that the maxima are observed in January, July and September, in contrast to other stations, at which the maximum amount of precipitation is registered in the summer months. Also, at the Odesa, the monthly precipitation in most months exceeds the same values for 1961-1990. Annual precipitation during 2000-2018 has a lot of regularities and differences, among which, for example, a common feature is the presence of maxima in 2010. In accordance with the general period trend characteristics, a tendency to an increase in the annual precipitation was found in the very south (Izmail station) only, and it has been especially pronounced since 2009. However, their mean values are lesser than in the Climate Cadastre of Ukraine; this is also observed for the stations Lyubashivka and Mykolaiv. On the contrary, at stations located on the coast (Odesa, Ochakiv), the annual precipitation exceeds of values from the Cadastre.
Based on the analysis carried out, it can be concluded that all persistent tendencies to changes in the values of the considered climatic characteristics are associated with a possible change in the atmospheric circulation over the considered territory.
Air temperatures (Ta) are rising in a changing climate, increasing extreme temperature events. Examining how Ta increases are influencing extreme temperatures at the soil surface and belowground in the soil profile can refine our understanding of the ecological consequences of rising temperatures. In this paper, we validate surface and soil temperature (Ts: 0–100-cm depth) simulations in the SOILWAT2 model for 29 locations comprising 5 ecosystem types in the central and western USA. We determine the temperature characteristics of these locations from 1980 to 2015, and explore simulations of Ta and Ts change over 2030–2065 and 2065–2100 time periods using General Circulation Model (GCM) projections and the RCP 8.5 emissions scenario. We define temperature extremes using a nonstationary peak over threshold method, quantified from standard deviations above the mean (0-σ: an event >∼ 51% of extreme events; 2-σ:>∼98%). Our primary objective is to contrast the magnitude (∘C) and frequency of occurrence of extreme temperature events between the twentieth and twenty-first century. We project that temperatures will increase substantially in the twenty-first century. Extreme Ta events will experience the largest increases by magnitude, and extreme Ts events will experience the largest increases by proportion. On average, 2-σ extreme Ts events will increase by 3.4 ∘C in 2030–2065 and by 5.3 ∘C in 2065–2100. Increases in extreme Ts events will often exceed + 10 ∘C at 0–20 cm by 2065–2100, and at 0–100 cm will often exceed 5.0 standard deviations above 1980–2015 values. 2-σ extreme Ts events will increase from 0.9 events per decade in 1980–2015 to 23 events in 2030–2065 and 38 events in 2065–2100. By 2065–2100, the majority of months will experience extreme events that co-occur at 0–100 cm, which did not occur in 1980–2015. These projections illustrate the non-analog temperature increases that ecosystems will experience in the twenty-first century as a result of climate change.
Intensive irrigation in India has been demonstrated to decrease surface temperature, but the influence of irrigation on humidity and extreme moist heat stress is not well understood. Here we analysed a combination of in situ and satellite-based datasets and conducted meteorological model simulations to show that irrigation modulates extreme moist heat. We found that intensive irrigation in the region cools the land surface by 1 °C and the air by 0.5 °C. However, the decreased sensible heat flux due to irrigation reduces the planetary boundary layer height, which increases low-level moist enthalpy. Thus, irrigation increases the specific and relative humidity, which raises the moist heat stress metrics. Intense irrigation over the region results in increased moist heat stress in India, Pakistan, and parts of Afghanistan—affecting about 37–46 million people in South Asia—despite a cooler land surface. We suggest that heat stress projections in India and other regions dominated by semi-arid and monsoon climates that do not include the role of irrigation overestimate the benefits of irrigation on dry heat stress and underestimate the risks.
Substantial warming occurred across North America, Europe and the Arctic over the early twentieth century1, including an increase in global drought2, that was partially forced by rising greenhouse gases (GHGs)3. The period included the 1930s Dust Bowl drought4–7 across North America’s Great Plains that caused widespread crop failures4,8, large dust storms9 and considerable out-migration10. This coincided with the central United States experiencing its hottest summers of the twentieth century11,12 in 1934 and 1936, with over 40 heatwave days and maximum temperatures surpassing 44 °C at some locations13,14. Here we use a large-ensemble regional modelling framework to show that GHG increases caused slightly enhanced heatwave activity over the eastern United States during 1934 and 1936. Instead of asking how a present-day heatwave would behave in a world without climate warming, we ask how these 1930s heatwaves would behave with present-day GHGs. Heatwave activity in similarly rare events would be much larger under today’s atmospheric GHG forcing and the return period of a 1-in-100-year heatwave summer (as observed in 1936) would be reduced to about 1-in-40 years. A key driver of the increasing heatwave activity and intensity is reduced evaporative cooling and increased sensible heating during dry springs and summers. The United States experienced two of its hottest recorded summers in 1934 and 1936, amplified by drier soils associated with the Dust Bowl drought. A large regional climate model ensemble estimates present-day GHGs would cause similarly extreme, 1-in-100-year heatwaves to occur about every 40 years.
The use of machine vision technologies to detect the density of colored yarn-dyed woven fabric has significantly accelerated during the last two decades. Unlike previous studies, this paper proposes an algorithm based on a multi-directional illumination image fusion technology to weaken the color signals in the interlace region of yarn-dyed fabric using the three-dimensional surface structure of the fabric. Four gray-scale images are first sampled using four directional light sources with a square distribution, and the four images are then fused through different discrete wavelet transform methods to enhance the image contrast between the float yarns and their adjacent interstices. A Butterworth filter, Gaussian pyramid, and Hough transform are applied to the fused image sequentially to improve the accuracy of the skew detection such that a gray-scale projection can be carried out along the yarn direction to locate the position of the weft and warp yarns. Finally, the local weighted regression algorithm with an adaptive width factor is adopted for smoothing the projection curve and improving the accuracy of the yarn density detection. For optimization of the proposed method, the effects of the illumination direction angle, image fusion method, fabric color, and weave pattern on the density measurements were investigated. The experimental results show that the proposed method works well and achieves an acceptable level of accuracy regarding the yarn density detection for yarn-dyed fabric.
Event attribution, which determines how anthropogenic climate change has affected the likelihood of certain types of extreme events, is of broad interest to industries, governments, and the public. Attribution results can be highly dependent on the definition of the event and the characteristics assessed, which are part of framing the attribution question. Despite a widely acknowledged sensitivity to framing, little work has been done to document the impacts on attribution and the resulting implications. Here, we use a perfect‐model approach and large ensembles of coupled climate‐model simulations to demonstrate how event attribution depends on the spatial and temporal scales used to define the event. In general, stronger attribution is found for events defined over longer time scales and larger spatial scales due to enhanced signal‐to‐noise ratios. With strong warming trends, most regions see large changes in the likelihood of temperature extremes at all scales, even at low levels of global mean temperature increase. For precipitation extremes, spatial scale plays a strong role. It may be possible to attribute changes in likelihood for extreme precipitation events defined over larger scales, but greater levels of global warming are often required before it is possible to attribute changes in the likelihood of smaller‐scale precipitation events. Care must be taken to understand the scales used in event attribution, in order to properly understand the results.
The time at which climate change signal can be clearly distinguished from noise is known as time of emergence (ToE) and is typically detected by a general circulation model (GCM) signal-to-noise ratio exceeding a certain threshold. ToE is commonly estimated at large scales from GCMs, although management decisions and adaptation strategies are implemented locally. This paper proposes a methodology to estimate ToE for both precipitation and temperature at local scales (i.e., river basin). The methodology considers local climatic conditions and unbiased GCM projections to estimate ToE by using the statistical power to find when the climate significantly differs from the historical one. The method suggests that ToE for temperature already occurred in three Chilean basins (Limarí, Maipo, and Maule). However, in terms of precipitation, an earlier ToE is clearly identified for the Maule basin, indicating that risk assessment and adaptation measures should be implemented first in this basin.
Western China experienced an extreme hot summer in 2015, breaking a number of temperature records. The summer mean surface air temperature (SAT) anomaly was twice the interannual variability. The hottest daytime temperature (TXx) and warmest night-time temperature (TNx) were the highest in China since 1964. This extreme hot summer occurred in the context of steadily increasing temperatures in recent decades. We carried out a set of experiments to evaluate the extent to which the changes in sea surface temperature (SST)/sea ice extent (SIE) and anthropogenic forcing drove the severity of the extreme summer of 2015 in western China. Our results indicate that about 65%–72% of the observed changes in the seasonal mean SAT and the daily maximum (Tmax) and daily minimum (Tmin) temperatures over western China resulted from changes in boundary forcings, including the SST/SIE and anthropogenic forcing. For the relative role of individual forcing, the direct impact of changes in anthropogenic forcing explain about 42% of the SAT warming and 60% (40%) of the increase in TNx and Tmin (TXx and Tmax) in the model response. The changes in SST/SIE contributed to the remaining surface warming and the increase in hot extremes, which are mainly the result of changes in the SST over the Pacific Ocean, where a super El Niño event occurred. Our study indicates a prominent role for the direct impact of anthropogenic forcing in the severity of the extreme hot summer in western China in 2015, although the changes in SST/SIE, as well as the internal variability of the atmosphere, also made a contribution.
In the last decade, climate mitigation policy has galvanized around staying below specified thresholds of global mean temperature, with an understanding that exceeding these thresholds may result in dangerous interference of the climate system. United Nations Framework Convention on Climate Change texts have developed thresholds in which the aim is to limit warming to well below 2 °C of warming above preindustrial levels, with an additional aspirational target of 1.5 °C. However, denoting a specific threshold of global mean temperatures as a target for avoiding damaging climate impacts implicitly obscures potentially significant regional variations in the magnitude of these projected impacts. This study introduces a simple framework to quantify the magnitude of this heterogeneity in changing climate hazards at 1.5 °C of warming, using case studies of emergent increases in temperature and rainfall extremes. For example, we find that up to double the amount of global warming (3.0 °C) is needed before people in high-income countries experience the same relative changes in extreme heat that low-income nations should anticipate after only 1.5 °C of warming. By mapping how much warming is needed in one location to match the impacts of a fixed temperature threshold in another location, this “temperature of equivalence” index is a flexible and easy-to-understand communication tool, with the potential to inform where targeted support for adaptation projects should be prioritized in a warming world.
Anthropogenic activity has increased the risk of Australian heatwaves during late autumn similar to the 2014 event by up to 23-fold, compared to climate conditions under no anthropogenic influence.
Determining the time of emergence of climates altered from their natural state by anthropogenic influences can help inform the development of adaptation and mitigation strategies to climate change. Previous studies have examined the time of emergence of climate averages. However, at the global scale, the emergence of changes in extreme events, which have the greatest societal impacts, has not been investigated before. Based on state-of-the-art climate models, we show that temperature extremes generally emerge slightly later from their quasi-natural climate state than seasonal means, due to greater variability in extremes. Nevertheless, according to model evidence, both hot and cold extremes have already emerged across many areas. Remarkably, even precipitation extremes that have very large variability are projected to emerge in the coming decades in Northern Hemisphere winters associated with a wettening trend. Based on our findings we expect local temperature and precipitation extremes to already differ significantly from their previous quasi-natural state at many locations or to do so in the near future. Our findings have implications for climate impacts and detection and attribution studies assessing observed changes in regional climate extremes by showing whether they will likely find a fingerprint of anthropogenic climate change.
In 2014, Central England experienced its warmest year in a record extending back to 1659. Using both state-of-the-art climate models and empirical techniques, our analysis shows a substantial and significant increase in the likelihood of record-breaking warm years, such as 2014, due to human influences on climate. With 90% confidence we find that anthropogenic forcings on the climate have increased the chances of record warm years in Central England by at least 13-fold. This study points to a large influence of human activities on extreme warm years despite the small region of study and the variable climate of Central England. Our analysis shows that climate change is clearly visible on the local-scale in this case.
Climate change includes not only changes in mean climate but also in weather extremes. For a few prominent heatwaves and heavy precipitation events a human contribution to their occurrence has been demonstrated. Here we apply a similar framework but estimate what fraction of all globally occurring heavy precipitation and hot extremes is attributable to warming. We show that at the present-day warming of 0.85 °C about 18% of the moderate daily precipitation extremes over land are attributable to the observed temperature increase since pre-industrial times, which in turn primarily results from human influence. For 2 °C of warming the fraction of precipitation extremes attributable to human influence rises to about 40%. Likewise, today about 75% of the moderate daily hot extremes over land are attributable to warming. It is the most rare and extreme events for which the largest fraction is anthropogenic, and that contribution increases nonlinearly with further warming. The approach introduced here is robust owing to its global perspective, less sensitive to model biases than alternative methods and informative for mitigation policy, and thereby complementary to single-event attribution. Combined with information on vulnerability and exposure, it serves as a scientific basis for assessment of global risk from extreme weather, the discussion of mitigation targets, and liability considerations.
A global survey of surface temperature anomalies occurring during 2013 (Fig. 8.1a; Supplementary Fig. S8.1) in the HadCRUT4 observations (Morice et al. 2012) reveals pronounced warm annual and seasonal mean anomalies. Two regions with prominent record or near-record annual mean warm anomalies include large regions of Australia and a region in the far western tropical Pacific encompassing the Philippines and part of the Maritime Continent (Fig. 8.1b). The 2013 anomalies appear particularly extreme during austral fall and winter (MAM, JJA) in Australia and during MAM in the far western Pacific (Supplementary Fig. S8.1). Temperatures in these two regions are further assessed in this report for the causes of this extreme warmth. Twenty-three All-Forcing (anthropogenic plus natural) models and control runs and 10 Natural-Forcing models were used from the Coupled Model Intercomparison Project phase 5 (CMIP5; Taylor et al. 2012). See Knutson et al. (2013a,b) for background on our methodology and a global assessment of low-frequency variability and trends.
Cumulative precipitation in northern India in June 2013 was a century-scale event, and evidence for increased probability in the present climate compared to the preindustrial climate is equivocal.
[1] Anthropogenic contributions to the record hot 2013 Australian summer are investigated using a suite of climate model experiments. This was the hottest Australian summer in the observational record. Australian area-average summer temperatures for simulations with natural forcings only were compared to simulations with anthropogenic and natural forcings for the period 1976–2005 and the RCP8.5 high emission simulation (2006–2020) from nine Coupled Model Intercomparison Project phase 5 models. Using fraction of attributable risk to compare the likelihood of extreme Australian summer temperatures between the experiments, it was very likely (>90% confidence) there was at least a 2.5 times increase in the odds of extreme heat due to human influences using simulations to 2005, and a fivefold increase in this risk using simulations for 2006–2020. The human contribution to the increased odds of Australian summer extremes like 2013 was substantial, while natural climate variations alone, including El Niño Southern Oscillation, are unlikely to explain the record temperature.
Extreme rainfall over southeast Australia was examined and its teleconnection with ENSO in observations and a selection of CMIP5 models. In observations, the magnitude of anomalously cool SSTs in the Nino-3.4 region has a far greater effect on Rx5day in SE Australia compared to the magnitude of anomalously warm SSTs. Five CMIP5 models were selected as the focus for the study as they possess aspects of ENSO variability and an asymmetric ENSO-extreme rainfall relationship. Using these models, it was found little evidence of significant change in the ENSO extreme rainfall relationship between 1861-90 and 1976-2005. The PDFs of Rx5day values in La Ninão seasons also show non-significant differences between the same periods. Inter-annual variability related to ENSO has played a greater role than any long-term trend on the magnitude of extreme rainfall events in southeast Australia over the period 1861-2005.
Attribution of extreme events is a challenging science and one that is currently undergoing considerable evolution. In this paper are 19 analyses by 18 different research groups, often using quite different methodologies, of 12 extreme events that occurred in 2012. In addition to investigating the causes of these extreme events, the multiple analyses of four of the events, the high temperatures in the United States, the record low levels of Arctic sea ice, and the heavy rain in northern Europe and eastern Australia, provide an opportunity to compare and contrast the strengths and weaknesses of the various methodologies. The differences also provide insights into the structural uncertainty of event attribution, that is, the uncertainty that arises directly from the differences in analysis methodology. In these cases, there was considerable agreement between the different assessments of the same event. However, different events had very different causes. Approximately half the analyses found some evidence that anthropogenically caused climate change was a contributing factor to the extreme event examined, though the effects of natural fluctuations of weather and climate on the evolution of many of the extreme events played key roles as well.
We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950–2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three-step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three-dimensional thin-plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years
The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
In 1974 Manley produced a time series of monthly average temperatures representative of central England for 1659–1973. The present paper describes how a series of homogenized daily values representative of the same region has been formed. This series starts in 1772, and is consistent with Manley's monthly average values. Between 1772 and 1876 the daily series is based on a sequence of single stations whose variance has been reduced to counter the artificial increase that results from sampling single locations. For subsequent years, the series has been produced from combinations of as few stations as can reliably represent central England in the manner defined by Manley. We have used the daily series to update Manley's published monthly series in a consistent way.
We have evaluated recent urban warming influences at the chosen stations by comparison with nearby rural stations, and have corrected the series from 1974 onwards. The corrections do not (yet) exceed 0.1°C.
We present all the monthly data from 1974, along with averages and standard deviations for 1961–1990. We also show sequences of daily central England temperature for sample years. All the daily data are available on request.
We update the Goddard Institute for Space Studies (GISS) analysis of global surface temperature change, compare alternative analyses, and address questions about perception and reality of global warming. Satellite-observed nightlights are used to identify measurement stations located in extreme darkness and adjust temperature trends of urban and peri-urban stations for non-climatic factors, verifying that urban effects on analyzed global change are small. Because the GISS analysis combines available sea surface temperature records with meteorological station measurements, we test alternative choices for the ocean data, showing that global temperature change is sensitive to estimated temperature change in polar regions where observations are limited. We use simple 12-month (and n×12) running means to improve the information content in our temperature graphs. Contrary to a popular misconception, the rate of warming has not declined. Global temperature is rising as fast in the past decade as in the prior two decades, despite year-to-year fluctuations associated with the El Nino-La Nina cycle of tropical ocean temperature. Record high global 12-month running-mean temperature for the period with instrumental data was reached in 2010.
Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 1766, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a 'wake-up call' to the impacts of climate change at the time, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail to account fully for the complex hydrometeorology associated with flooding. Here we present a multi-step, physically based 'probabilistic event attribution' framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
The summer of 2003 was probably the hottest in Europe since at latest ad 1500, and unusually large numbers of heat-related deaths were reported in France, Germany and Italy. It is an ill-posed question whether the 2003 heatwave was caused, in a simple deterministic sense, by a modification of the external influences on climate--for example, increasing concentrations of greenhouse gases in the atmosphere--because almost any such weather event might have occurred by chance in an unmodified climate. However, it is possible to estimate by how much human activities may have increased the risk of the occurrence of such a heatwave. Here we use this conceptual framework to estimate the contribution of human-induced increases in atmospheric concentrations of greenhouse gases and other pollutants to the risk of the occurrence of unusually high mean summer temperatures throughout a large region of continental Europe. Using a threshold for mean summer temperature that was exceeded in 2003, but in no other year since the start of the instrumental record in 1851, we estimate it is very likely (confidence level >90%) that human influence has at least doubled the risk of a heatwave exceeding this threshold magnitude.
Variations in solar radiation incident at Earth's surface profoundly affect the human and terrestrial environment. A decline in solar radiation at land surfaces has become apparent in many observational records up to 1990, a phenomenon known as global dimming. Newly available surface observations from 1990 to the present, primarily from the Northern Hemisphere, show that the dimming did not persist into the 1990s. Instead, a widespread brightening has been observed since the late 1980s. This reversal is reconcilable with changes in cloudiness and atmospheric transmission and may substantially affect surface climate, the hydrological cycle, glaciers, and ecosystems.
Anthropogenic climate change reduced the odds of an extremely cold UK spring in 2013 at least 30 times, as estimated from ensembles of simulations with and without human influences.
The record heat of 2013 across inland eastern Australia was caused by a combination of anthropogenic warming and extreme drought.
An improved understanding of how changes in extremes can be relevant and applied to improved decision making is discussed. The early onset of the 2014 dry season in California fueled an extraordinary jump in wildfires. Between 1 January and 20 September, the California Department of Forestry and Fire Protection reported thousands more fires than the five-year average. The results indicate that man-made global warming is likely one of the causes that will exacerbate the areal extent and frequency of extreme fire risk. Below-normal temperatures covered the Upper Midwest and Great Lakes region from November 2013 through April 2014, the longest such consecutive monthly stretch since 1995?96, culminating in the coldest winter since 1978/79. The analysis of a 134-year record of winter season temperatures indicates that a cold winter of the severity observed over the GUM region in 2013/14 would have been a once-a-decade phenomenon at the end of the 19th century, but has become extraordinarily unlikely in the early 21st century. The collective effects of anthropogenic climate change and artificial pond drainage may have played an important role in producing the extreme flood that occurred during early summer 2014 on the southeastern Canadian Prairies. The extreme 2013/14 winter storm season over much of North America was made more likely by the multiyear anomalous tropical Pacific winds associated with the recent global warming hiatus. Similarly, the all-time record number of storms over the British Isles in winter 2013/14 cannot be linked directly to anthropogenic-induced warming of the tropical west Pacific.
A suite of climate datasets and multiple representations of atmospheric moisture demand are used to calculate many estimates of the self-calibrated Palmer Drought Severity Index, a proxy for near-surface soil moisture, across California from 1901–2014 at high spatial resolution. Based on the ensemble of calculations, California drought conditions were record-breaking in 2014, but probably not record-breaking in 2012–2014, contrary to prior findings. Regionally, the 2012–2014 drought was record-breaking in the agriculturally important southern Central Valley and highly populated coastal areas. Contributions of individual climate variables to recent drought are also examined, including the temperature component associated with anthropogenic warming. Precipitation is the primary driver of drought variability but anthropogenic warming is estimated to have accounted for 8–27% of the observed drought anomaly in 2012–2014 and 5–18% in 2014. Although natural variability dominates, anthropogenic warming has substantially increased the overall likelihood of extreme California droughts.
Socio-economic stress from the unequivocal warming of the global climate system could be mostly felt by societies through weather and climate extremes. The vulnerability of European citizens was made evident during the summer heatwave of 2003 (refs,) when the heat-related death toll ran into tens of thousands. Human influence at least doubled the chances of the event according to the first formal event attribution study, which also made the ominous forecast that severe heatwaves could become commonplace by the 2040s. Here we investigate how the likelihood of having another extremely hot summer in one of the worst affected parts of Europe has changed ten years after the original study was published, given an observed summer temperature increase of 0.81 K since then. Our analysis benefits from the availability of new observations and data from several new models. Using a previously employed temperature threshold to define extremely hot summers, we find that events that would occur twice a century in the early 2000s are now expected to occur twice a decade. For the more extreme threshold observed in 2003, the return time reduces from thousands of years in the late twentieth century to about a hundred years in little over a decade.
A comparison of observations and multiple global climate model simulations indicates that extreme hot summer temperatures in Korea have become 10 times more likely due to human influence.
An attribution analysis of extreme temperature changes is conducted using updated observations (HadEX2) and multi-model climate simulation (CMIP5) datasets for an extended period of 1951-2010. Compared to previous HadEX/CMIP3-based results, which identified human contributions to the observed warming of extreme temperatures on global and regional scales, the current results provide better agreement with observations, particularly for the intensification of warm extremes. Removing the influence of two major modes of natural internal variability (the Arctic Oscillation and Pacific Decadal Oscillation) from observations further improves attribution results, reducing the model-observation discrepancy in cold extremes. An optimal fingerprinting technique is used to compare observed changes in annual extreme temperature indices of coldest night and day (TNn, TXn) and warmest night and day (TNx, TXx) with multi-model simulated changes that were simulated under natural-plus-anthropogenic and natural-only (NAT) forcings. Extreme indices are standardized for better intercomparisons between datasets and locations prior to analysis and averaged over spatial domains from global to continental regions following a previous study. Results confirm previous HadEX/CMIP3-based results in which anthropogenic (ANT) signals are robustly detected in the increase in global mean and northern continental regional means of the four indices of extreme temperatures. The detected ANT signals are also clearly separable from the response to NAT forcing, and results are generally insensitive to the use of different model samples as well as different data availability.
This study determines whether observed recent changes in the frequency of hot and cold extremes over land can be explained by climate variability or whether they show a detectable response to external influences. The authors analyze changes in the frequency of moderate-to-extreme daily temperatures-namely, the number of days exceeding the 90th percentile and the number of days not reaching the 10th percentile of daily minimum (tn90 and tn10, respectively) and maximum (tx90 and tx10, respectively) temperature-for both cold and warmseasons. The analysis is performed on a range of spatial scales and separately for boreal cold-and warm-season data. The fingerprint for external forcing is derived from an ensemble of simulations produced with the Hadley Centre Global Environmental Model, version 1 (HadGEM1), with both anthropogenic and natural forcings. The observations show an increase in warm extremes and a decrease in cold extremes in both seasons and in almost all regions that are generally well captured by the model. Some regional differences between model and observations may be due to local forcings or changes in climate dynamics. A detection analysis, using both optimized and nonoptimized fingerprints, shows that the influence of external forcing is detectable in observations for both cold and warm extremes, and cold and warm seasons, over the period 1951-2003 at the 5% level. It is also detectable separately for the Northern and Southern Hemispheres, and over most regions analyzed. The model shows a tendency to significantly overestimate changes in warm daytime extremes, particularly in summer.
Various methodologies are used to explain some extreme events of 2011 from a climate perspective. The Global Precipitation Climatology Centre (GPCC) V5 1° rainfall analyzes was used to estimate severe flooding in 2011 in Thailand. Time series of rainfall in show that the amount of rain that fell in the catchment area was not very unusual. In 2011, East Africa faced a tragic food crisis that led to famine conditions in parts of Somalia and severe food shortages in parts of Ethiopia and Somalia. Research has suggested that continued warming in the IPWP will likely contribute to more frequent East African droughts during the boreal spring and summer. In 2011, the state of Texas experienced an extraordinary heat wave and drought. A spatial, weighted average was calculated from the 27 GCM grid boxes that fell within Texas, with weights proportional to the cosine of the latitude. It was found that the conditions leading to droughts such as the one that occurred in Texas in 2011 are, at least in the case of temperature, distinctly more probable than they were 40-50 years ago.
A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, verification of high-resolution model simulations and satellite precipitation estimates, and improvement of precipitation forecasts. The APHRODITE project carries out outreach activities with Asian countries, and communicates with national institutions and world data centers. We have released open-access APHRO_V1101 datasets for monsoon Asia, the Middle East, and northern Eurasia (at 0.5° × 0.5° and 0.25° × 0.25° resolution) and the APHRO_JP_V1005 dataset for Japan (at 0.05° × 0.05° resolution; see www.chikyu.ac.jp/precip/ and http://aphrodite.suiri.tsukuba.ac.jp/). We welcome cooperation and feedback from users.
Recent studies have detected anthropogenic influences due to increases in greenhouse gases on extreme temperature changes during the latter half of the twentieth century at global and regional scales. Most of the studies, however, were based on a limited number of climate models and also separation of anthropogenic influence from natural factors due to changes in solar and volcanic activities remains challenging at regional scales. Here, the authors conduct optimal fingerprinting analyses using 12 climate models integrated under anthropogenic-only forcing or natural plus anthropogenic forcing. The authors compare observed and simulated changes in annual extreme temperature indices of coldest night and day (TNn and TXn) and warmest night and day (TNx and TXx) from 1951 to 2000. Spatial domains from global mean to continental and subcontinental regions are considered and standardization of indices is employed for better intercomparisons between regions and indices. The anthropogenic signal is detected in global and northern continental means of all four indices, albeit less robustly for TXx, which is consistent with previous findings. The detected anthropogenic signals are also found to be separable from natural forcing influence at the global scale and to a lesser extent at continental and subcontinental scales. Detection occurs more frequently in TNx and TNn than in other indices, particularly at smaller scales, supporting previous studies based on different methods. A combined detection analysis of daytime and nighttime temperature extremes suggests potential applicability to a multivariable assessment.
A station observation-based global land monthly mean surface air temperature dataset at 0.5 × 0.5 latitude-longitude resolution for the period from 1948 to the present was developed recently at the Climate Prediction Center, National Centers for Environmental Prediction. This data set is different from some existing surface air temperature data sets in: (1) using a combination of two large individual data sets of station observations collected from the Global Historical Climatology Network version 2 and the Climate Anomaly Monitoring System (GHCN + CAMS), so it can be regularly updated in near real time with plenty of stations and (2) some unique interpolation methods, such as the anomaly interpolation approach with spatially-temporally varying temperature lapse rates derived from the observation-based Reanalysis for topographic adjustment. When compared with several existing observation-based land surface air temperature data sets, the preliminary results show that the quality of this new GHCN + CAMS land surface air temperature analysis is reasonably good and the new data set can capture most common temporal-spatial features in the observed climatology and anomaly fields over both regional and global domains. The study also reveals that there are clear biases between the observed surface air temperature and the existing Reanalysis data sets, and they vary in space and seasons. Therefore the Reanalysis 2 m temperature data sets may not be suitable for model forcing and validation. The GHCN + CAMS data set will be mainly used as one of land surface meteorological forcing inputs to derive other land surface variables, such as soil moisture, evaporation, surface runoff, snow accumulation and snow melt, etc. As a byproduct, this monthly mean surface air temperature data set can also be applied to monitor surface air temperature variations over global land routinely or to verify the performance of model simulation and prediction.