Emergence of heat extremes attributable to anthropogenic influences

ArticleinGeophysical Research Letters · March 2016with 402 Reads
Cite this publication
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.

Do you want to read the rest of this article?

Request Full-text Paper PDF
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • Friederike E. L. Otto
    • Tim Cowan
      Tim Cowan
    • Gabriele C Hegerl
      Gabriele C Hegerl
    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.
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • David J Frame
      David J Frame
    • Ed Hawkins
      Ed Hawkins
    • Manoj Joshi
    A common proxy for the adaptive capacity of a community to the impacts of future climate change is the range of climate variability which they have experienced in the recent past. This study presents an interpretation of such a framework for monthly temperatures. Our results demonstrate that emergence into genuinely 'unfamiliar' climates will occur across nearly all months of the year for low-income nations by the second half of the 21st century under an RCP8.5 warming scenario. However, high income countries commonly experience a large seasonal cycle, owing to their position in the middle latitudes: as a consequence, temperature emergence for transitional months translates only to more-frequent occurrences of heat historically associated with the summertime. Projections beyond 2050 also show low-income countries will experience 2–10 months per year warmer than the hottest month experienced in recent memory, while high-income countries will witness between 1–4 months per year hotter than any month previously experienced. While both results represent significant departures that may bring substantive societal impacts if greenhouse gas emissions continue unabated, they also demonstrate that spatial patterns of emergence will compound existing differences between high and low income populations, in terms of their capacity to adapt to unprecedented future temperatures.
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • Sophie C. Lewis
    • Sarah E. Perkins-Kirkpatrick
    • Friederike E. L. Otto
    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.
  • Article
    • Ary Hoffmann
      Ary Hoffmann
    • Paul D Rymer
      Paul D Rymer
    • Margaret Byrne
      Margaret Byrne
    • Stephen E Williams
      Stephen E Williams
    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.
  • Article
    Full-text available
    • Thomas L Frölicher
      Thomas L Frölicher
    • Erich M Fischer
      Erich M Fischer
    • Nicolas Gruber
      Nicolas Gruber
    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.
  • Article
    • Benjamin J. Henley
      Benjamin J. Henley
    • Andrew David King
      Andrew David King
    Global temperature is rapidly approaching the 1.5°C Paris target. In the absence of external cooling influences, such as volcanic eruptions, temperature projections are centered on a breaching of the 1.5°C target, relative to 1850–1900, before 2029. The phase of the Interdecadal Pacific Oscillation (IPO) will regulate the rate at which mean temperature approaches the 1.5°C level. A transition to the positive phase of the IPO would lead to a projected exceedance of the target centered around 2026. If the Pacific Ocean remains in its negative decadal phase, the target will be reached around 5 years later, in 2031. Given the temporary slowdown in global warming between 2000 and 2014, and recent initialized decadal predictions suggestive of a turnaround in the IPO, a sustained period of rapid temperature rise might be underway. In that case, the world will reach the 1.5°C level of warming several years sooner than if the negative IPO phase persists.
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • Peter B. Gibson
    • David J Frame
      David J Frame
    • Sam M. Dean
    Previous studies evaluating anthropogenic influences on the meteorological drivers of drought have found mixed results owing to (1) the complex physical mechanisms which lead to the onset of drought, (2) differences in the characteristics and timescales of drought for different regions of the world, and (3) different approaches to the question of attribution. For a mid-latitude, temperate climate like New Zealand, strongly modulated by oceanic influences, summer droughts last on the order of three months, and are less strongly linked to persistent temperature anomalies than continental climates. Here, we demonstrate the utility of a novel approach for characterizing the meteorological conditions conducive to extreme drought over the North Island of New Zealand, using the January-March 2013 event as a case study. Specifically, we consider the use of self-organizing map (SOM) techniques in a multi-member coupled climate model ensemble to capture changes in daily circulation, between two 41-year periods (1861-1901 and 1993-2033). Comparisons are made with seasonal pressure and precipitation indices. Our results demonstrate robust (>99% confidence) increases in the likelihood of observing circulation patterns like those of the 2013 drought in the recent-climate simulations when compared with the early-climate simulations. Best-guess estimates of the fraction of attributable risk range from 0.2 to 0.4, depending on the metric used and threshold considered. Contributions to uncertainty in these attribution statements are discussed.
  • Article
    • Wei Chen
      Wei Chen
    • Buwen Dong
    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.
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • Dave Frame
    • Andrew D. King
    • Friederike E. L. Otto
    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.
  • Article
    • Thuy-Huong Nguyen
    • Seung-Ki Min
      Seung-Ki Min
    • Seungmok Paik
      Seungmok Paik
    • Donghyun Lee
      Donghyun Lee
    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.
  • Article
    Full-text available
    • Luke Harrington
      Luke Harrington
    • Friederike E. L. Otto
    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.
  • Article
    • Andrew David King
      Andrew David King
    Record-breaking temperatures attract attention from the media, so understanding how and why the rate of record breaking is changing may be useful in communicating the effects of climate change. A simple methodology designed for estimating the anthropogenic influence on rates of record breaking in a given time series is proposed here. The frequency of hot and cold record-breaking temperature occurrences is shown to be changing due to the anthropogenic influence on the climate. Using ensembles of model simulations with and without human-induced forcings, it is demonstrated that the effect of climate change on global record-breaking temperatures can be detected as far back as the 1930s. On local scales, a climate change signal is detected more recently at most locations. The anthropogenic influence on the increased occurrence of hot record-breaking temperatures is clearer than it is for the decreased occurrence of cold records. The approach proposed here could be applied in rapid attribution studies of record extremes to quantify the influence of climate change on the rate of record breaking in addition to the climate anomaly being studied. This application is demonstrated for the global temperature record of 2016 and the Central England temperature record in 2014.
  • Article
    • Andrew David King
      Andrew David King
    • David J. Karoly
      David J. Karoly
    • Benjamin J. Henley
      Benjamin J. Henley
    To avoid more severe impacts from climate change, there is international agreement to strive to limit warming to below 1.5 °C. However, there is a lack of literature assessing climate change at 1.5 °C and the potential benefits in terms of reduced frequency of extreme events. Here, we demonstrate that existing model simulations provide a basis for rapid and rigorous analysis of the effects of different levels of warming on large-scale climate extremes, using Australia as a case study. We show that limiting warming to 1.5 °C, relative to 2 °C, would perceptibly reduce the frequency of extreme heat events in Australia. The Australian continent experiences a variety of high-impact climate extremes that result in loss of life, and economic and environmental damage. Events similar to the record-hot summer of 2012-2013 and warm seas associated with bleaching of the Great Barrier Reef in 2016 would be substantially less likely, by about 25% in both cases, if warming is kept to lower levels. The benefits of limiting warming on hydrometeorological extremes are less clear. This study provides a framework for analysing climate extremes at 1.5 °C global warming. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
  • Article
    • Buwen Dong
    • Rowan Sutton
    • Len Christopher Shaffrey
      Len Christopher Shaffrey
    • Nicholas P. Klingaman
    There is still no consensus about the best methodology for attributing observed changes in climate or climate events. One widely used approach relies on experiments in which the time periods of interest are simulated using an atmospheric general circulation model (AGCM) forced by prescribed sea surface temperatures (SSTs), with and without estimated anthropogenic influences. A potential limitation of such experiments is the lack of explicit atmosphere-ocean coupling; therefore a key question is whether the attribution statements derived from such studies are in fact robust. In this research the authors have carried out climate model experiments to test attribution conclusions in a situation where the answer is known-a so-called perfect model approach. The study involves comparing attribution conclusions for decadal changes derived from experiments with a coupled climate model (specifically an AGCM coupled to an ocean mixed-layer model) with conclusions derived from parallel experiments with the same AGCM forced by SSTs derived from the coupled model simulations. Results indicate that attribution conclusions for surface air temperature changes derived from AGCM experiments are generally robust and not sensitive to air-sea coupling. However, changes in seasonal mean and extreme precipitations, and circulation in some regions, show large sensitivity to air-sea coupling, notably in the summer monsoons over East Asia and Australia. Comparison with observed changes indicates that the coupled simulations generally agree better with observations. These results demonstrate that the AGCM-based attribution method has limitations and may lead to erroneous attribution conclusions in some regions for local circulation and mean and extreme precipitation. The coupled mixed-layer model used in this study offers an alternative and, in some respects, superior tool for attribution studies.
  • Article
    • Luke Harrington
      Luke Harrington
    There is significant public and scientific interest in understanding whether and to what extent the severity and frequency of extreme events have increased in response to human influences on the climate system. As the science underpinning the field of event attribution continues to rapidly develop, there are growing expectations of faster and more accurate attribution statements to be delivered, even in the days to weeks after an extreme event occurs. As the research community looks to respond, a variety of approaches have been suggested, each with varying levels of conditioning to the observed state of the climate when the event of interest has occurred. One such approach to utilise unconditioned multi-model ensembles requires pre-computing estimates of the change in probability of occurrence for a wide range of possible ‘events’. In this study, we consider differences between event-as-class attribution statements with changes in the probability density of the distribution at the event threshold of interest. For the majority of extreme event attribution studies, it is likely that the two metrics are comparable once uncertainty estimates are considered. However, results show these two metrics can produce divergent answers from each other for moderate climatological anomalies if the present-day climate distribution experiences a substantial change in the underlying signal-to-noise ratio. As the emergent signals of climate change becomes increasingly clear, this study highlights the need for clear and explicit framing in the context of applying pre-computed attribution statements, particularly if attribution perspectives are to be included within the framework of future climate services.
  • Article
    Full-text available
    • Sebastian Sippel
      Sebastian Sippel
    • Jakob Zscheischler
      Jakob Zscheischler
    • Miguel D Mahecha
      Miguel D Mahecha
    • Sonia I Seneviratne
      Sonia I Seneviratne
    The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land–atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land–atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land–atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T–ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T–ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C – but this remains a local effect in regions that are highly sensitive to land–atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.
  • Article
    • Donghyun Lee
      Donghyun Lee
    • Seung-Ki Min
      Seung-Ki Min
    • Changyong Park
      Changyong Park
    • Hyun-Suk Kang
    Time of Emergence (ToE) is the time at which the signal of climate change emerges from the background noise of natural climate variability, and can provide useful information for climate change impacts and adaptations. This study examines future ToEs for daily maximum and minimum temperatures over the Northeast Asia using five Regional Climate Models (RCMs) simulations driven by single Global Climate Model (GCM) under two Representative Concentration Pathways (RCP) emission scenarios. Noise is defined based on the interannual variability during the present-day period (1981-2010) and warming signals in the future years (2021-2100) are compared against the noise in order to identify ToEs. Results show that ToEs of annual mean temperatures occur between 2030s and 2040s in RCMs, which essentially follow those of the driving GCM. This represents the dominant influence of GCM boundary forcing on RCM results in this region. ToEs of seasonal temperatures exhibit larger ranges from 2030s to 2090s. The seasonality of ToE is found to be determined majorly by noise amplitudes. The earliest ToE appears in autumn when the noise is smallest while the latest ToE occurs in winter when the noise is largest. The RCP4.5 scenario exhibits later emergence years than the RCP8.5 scenario by 5-35 years. The significant delay in ToEs by taking the lower emission scenario provides an important implication for climate change mitigation. Daily minimum temperatures tend to have earlier emergence than daily maximum temperature but with low confidence. It is also found that noise thresholds can strongly affect ToE years, i.e. larger noise threshold induces later emergence, indicating the importance of noise estimation in the ToE assessment.
  • Conference Paper
    • Pieter P. Tans
  • the Cold Spring of 2013 in the United Kingdom
    the Cold Spring of 2013 in the United Kingdom. Bull. Am. Meteorol. Soc. 95, S79–S82 (2014).
    • M R Allen
    Allen, M. R. (2003), Liability for climate change, Nature, 401, 642.
    • N Christidis
    • G S Jones
    • P A Stott
    Christidis, N., G. S. Jones, and P. A. Stott (2015), Dramatically increasing chance of extremely hot summers since the 2003 European heatwave, Nat. Clim. Change, 5, 46–50.
    • A D King
    • S C Lewis
    • S E Perkins
    • L V Alexander
    • M G Donat
    • D J Karoly
    • M T Black
    King, A. D., S. C. Lewis, S. E. Perkins, L. V. Alexander, M. G. Donat, D. J. Karoly, and M. T. Black (2013), Limited evidence of anthropogenic influence on the 2011-12 extreme rainfall over Southeast Australia, Bull. Am. Meteorol. Soc., 94(9), S55–S58.
    • P Pall
    • T Aina
    • D A Stone
    • P A Stott
    • T Nozawa
    • A G J Hilberts
    • D Lohmann
    • M R Allen
    Pall, P., T. Aina, D. A. Stone, P. A. Stott, T. Nozawa, A. G. J. Hilberts, D. Lohmann, and M. R. Allen (2011), Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000, Nature, 470, 382–385.
    • A D King
    • G J Van Oldenborgh
    • D J Karoly
    • S C Lewis
    • H M Cullen
    King, A. D., G. J. van Oldenborgh, D. J. Karoly, S. C. Lewis, and H. M. Cullen (2015b), Attribution of the record high Central England temperature of 2014 to anthropogenic influences, Environ. Res. Lett., 10, 054002.
  • Article
    • Nikolaos Christidis
    • P. A. Stott
      P. A. Stott
    • Andrew Ciavarella
    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.
  • Article
    • Andrew David King
      Andrew David King
    • David J. Karoly
      David J. Karoly
    • Markus G. Donat
    • Lisa Alexander
      Lisa Alexander
    The record heat of 2013 across inland eastern Australia was caused by a combination of anthropogenic warming and extreme drought.
  • Article
    • P. A. Stott
      P. A. Stott
    • Gabriele C Hegerl
      Gabriele C Hegerl
    • Stephanie C. Herring
    • Francis W. Zwiers
  • Article
    • Stephanie C. Herring
    • Martin P. Hoerling
    • James P. Kossin
    • P. A. Stott
      P. A. Stott
    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.
  • Article
    Full-text available
    • Sarah E Perkins-Kirkpatrick
      Sarah E Perkins-Kirkpatrick
    • Peter B. Gibson
    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.
  • Article
    Full-text available
    • Andrew David King
      Andrew David King
    • G. Donat Markus
    • Erich M Fischer
      Erich M Fischer
    • E. Perkins Sarah
    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.
  • Article
    • Alton Park Williams
      Alton Park Williams
    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.
  • Article
    • Nikolaos Christidis
    • Gareth S. Jones
    • P. A. Stott
      P. A. Stott
    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.
  • Article
    • Seung-Ki Min
      Seung-Ki Min
    • Yeon-Hee Kim
      Yeon-Hee Kim
    • Maeng-ki Kim
      Maeng-ki Kim
    • Changyong Park
      Changyong Park
    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.
  • Article
    • Yeon-Hee Kim
      Yeon-Hee Kim
    • Seung-Ki Min
      Seung-Ki Min
    • Xuebin Zhang
      Xuebin Zhang
    • Yu-Shiang Tung
      Yu-Shiang Tung
    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.
  • Article
    Full-text available
    • Erich M Fischer
      Erich M Fischer
    • Reto Knutti
      Reto Knutti
    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.
  • Climate Change Turns
    • A D King
    • D J Karoly
    • M G Donat
    • L Alexander
    King, A. D., Karoly, D. J., Donat, M. G. & Alexander, L. V. Climate Change Turns
  • Article
    Full-text available
    • Deepti Singh
    • Daniel E. Horton
      Daniel E. Horton
    • Michael Tsiang
      Michael Tsiang
    • Noah S Diffenbaugh
      Noah S Diffenbaugh
    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.
  • Article
    • Sophie C. Lewis
    • David J. Karoly
      David J. Karoly
    [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.
  • Article
    • Gabriele C Hegerl
      Gabriele C Hegerl
    • Nikolaos Christidis
    • Simone Morak
    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.
  • Article
    • Thomas C. Peterson
    • P. A. Stott
      P. A. Stott
    • Stephanie C. Herring
    • Seung-Ki Min
      Seung-Ki Min
    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.
  • Article
    • Akiyo Yatagai
      Akiyo Yatagai
    • Kenji Kamiguchi
      Kenji Kamiguchi
    • Osamu Arakawa
    • Akio Kitoh
    A daily gridded precipitation dataset for the period 1951-2007 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's water resources) project. APHRODITE's daily gridded precipitation is presently the only long-term continental-scale high-resolution daily product. Our product is based on data collected at 5000 to 12,000 stations, which represents 2.3 to 4.5 times the data available through the Global Telecommunication System (GTS) network that are 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 forecasts. We released APHRO_V1101 datasets for Monsoon Asia, the Middle East and Russia (on 0.5 × 0.5 degree and 0.25 × 0.25 degree grids) and the APHRO_JP_V1005 dataset for Japan (on a 0.05 × 0.05 degree grid) on the website (http://www.chikyu.ac.jp/precip/ and http://aphrodite.suiri.tsukuba.ac.jp/). The major differences of APHRO_V1101 to that of the previous version (APHRO_V1003R1) are 1) improved quality control (QC) scheme and more input data (Belarus, Bhutan, South Korea, Saudi Arabia, Thailand, Taiwan and E-Obs). We are developing a daily gridded temperature dataset for Asia and a flag to discriminate between rain and snow will be added to the APHRODITE daily precipitation product. The combination of daily mean temperature, precipitation and rain/snow information in this high-resolution gridded format would be useful as input to river-flow models, crop models and many other situations where water resources must be estimated.
  • Article
    • Seung-Ki Min
      Seung-Ki Min
    • Xuebin Zhang
      Xuebin Zhang
    • Francis W. Zwiers
    • Michael F Wehner
      Michael F Wehner
    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.
  • Article
    • Yun Fan
      Yun Fan
    • Huug van den Dool
    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.
  • Article
    • Myles Allen
    Anyone with a home PC could join climate modellers in their attempt to forecast how the Earth's climate will evolve in the next century.
  • Article
    • David Jones
      David Jones
    • William Wang
    • Robert Fawcett
    In this paper, we describe a new high-quality set of historical and ongoing real- time climate analyses for Australia. These analyses have been developed for im- proving the definition of past climate variability and change over Australia and to improve on estimates of recent climate. The climate analyses cover the variables of rainfall, temperature (maximum and minimum) as well as vapour pressure at daily and monthly timescales and are complemented by remotely sensed and model- derived data described elsewhere. New robust topography-resolving analysis methods have been developed and applied to in situ observations of rainfall, temperature and vapour pressure to pro- duce analyses at a resolution of 0.05° × 0.05° (approximately 5 km × 5 km). The new methodologies are similar to those applied internationally, but in applying them to Australia we found it necessary and desirable to introduce a number of innova- tions. The resulting analyses represent substantial improvements on operational analyses currently produced by the Australian Bureau of Meteorology, and have a number of advantages over other similar data-sets currently available. Careful attention has been paid to developing systems and data-sets which are robust and useful for the monitoring of both climate variability and climate change. These systems are now running in real time and are expected to form the basis for the ongoing monitoring of Australia's surface climate variability and change by the Australian Bureau of Meteorology. The underlying data and associated error sur- faces (grids and station data) are updated in real time and are all available free of charge through the Bureau's climate website (www.bom.gov.au/climate).
  • Article
    Full-text available
    • Malcolm Haylock
    • Nynke Hofstra
      Nynke Hofstra
    • A. M. G. Klein Tank
    • Mark George New
      Mark George New
    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
  • Article
    Full-text available
    • Malcolm Haylock
    • Nynke Hofstra
      Nynke Hofstra
    • A. M. G. Klein Tank
    • Mark George New
      Mark George New
  • Article
    Full-text available
    • Karl E. Taylor
    • Stouffer Ronald
      Stouffer Ronald
    • Gerald A. Meehl
      Gerald A. Meehl
    CMIP5, as in earlier CMIP phases, calls for integrated sets of experiments that offer a multimodel perspective of simulated climate change and climate variability. Most modeling groups worldwide are participating in CMIP5, and their simulations are expected not only to be useful to research scientists in a variety of climate-related disciplines but also of relevance to national and international assessments of climate science (e.g., the IPCC AR5).
  • Article
    Full-text available
    • David Parker
      David Parker
    • T. P. Legg
    • Chris K. Folland
      Chris K. Folland
    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.
  • Article
    Full-text available
    • J.R. Hansen
    • R. Ruedy
      R. Ruedy
    • Mki. Sato
    • K. Lo
    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.
  • Article
    Full-text available
    • Pardeep Pall
      Pardeep Pall
    • T. Aina
    • Dáithí A. Stone
    • Myles R. Allen
    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%.
  • Article
    • Myles Allen
    Will it ever be possible to sue anyone for damaging the climate?
  • Article
    Full-text available
    • P. A. Stott
      P. A. Stott
    • D. A. Stone
    • M. R. Allen
    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.
  • Article
    Full-text available
    • Martin Wild
      Martin Wild
    • Hans Gilgen
    • Andreas Roesch
      Andreas Roesch
    • Anatoly Tsvetkov
      Anatoly Tsvetkov
    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.