Articles | Volume 6, issue 2
https://doi.org/10.5194/ascmo-6-177-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-6-177-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
10 Nov 2020
| 10 Nov 2020
A protocol for probabilistic extreme event attribution analyses
Sjoukje Philip
CORRESPONDING AUTHOR
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Sarah Kew
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Geert Jan van Oldenborgh
CORRESPONDING AUTHOR
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Friederike Otto
Environmental Change Institute, University of Oxford, Oxford, UK
Robert Vautard
LSCE/IPSL, laboratoire CEA/CNRS/UVSQ, 91191 Gif-sur-Yvette CEDEX, France
Karin van der Wiel
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Andrew King
ARC Centre of Excellence for Climate Extremes, School of Earth Sciences, University of Melbourne, Melbourne 3010, Australia
Fraser Lott
Met Office Hadley Centre, Exeter, UK
Julie Arrighi
Red Cross Red Crescent Climate Centre, The Hague, the Netherlands
Roop Singh
Red Cross Red Crescent Climate Centre, The Hague, the Netherlands
Maarten van Aalst
Red Cross Red Crescent Climate Centre, The Hague, the Netherlands
Related authors
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
Short summary
Short summary
Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
Short summary
Short summary
The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Sjoukje Philip, Sarah Sparrow, Sarah F. Kew, Karin van der Wiel, Niko Wanders, Roop Singh, Ahmadul Hassan, Khaled Mohammed, Hammad Javid, Karsten Haustein, Friederike E. L. Otto, Feyera Hirpa, Ruksana H. Rimi, A. K. M. Saiful Islam, David C. H. Wallom, and Geert Jan van Oldenborgh
Hydrol. Earth Syst. Sci., 23, 1409–1429, https://doi.org/10.5194/hess-23-1409-2019, https://doi.org/10.5194/hess-23-1409-2019, 2019
Short summary
Short summary
In August 2017 Bangladesh faced one of its worst river flooding events in recent history. For the large Brahmaputra basin, using precipitation alone as a proxy for flooding might not be appropriate. In this paper we explicitly test this assumption by performing an attribution of both precipitation and discharge as a flooding-related measure to climate change. We find the change in risk to be of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach.
Geert Jan van Oldenborgh, Sjoukje Philip, Sarah Kew, Michiel van Weele, Peter Uhe, Friederike Otto, Roop Singh, Indrani Pai, Heidi Cullen, and Krishna AchutaRao
Nat. Hazards Earth Syst. Sci., 18, 365–381, https://doi.org/10.5194/nhess-18-365-2018, https://doi.org/10.5194/nhess-18-365-2018, 2018
Short summary
Short summary
On 19 May 2016 a temperature of 51.0 °C in Phalodi (northwest India) set a new Indian record. In 2015 a very lethal heat wave had occurred in the southeast. We find that in India the trend in extreme temperatures due to greenhouse gases is largely cancelled by increasing air pollution and irrigation. The health impacts of heat waves do increase due to higher humidity and air pollution. This implies that we expect heat waves to become much hotter as soon as air pollution is brought under control.
Karin van der Wiel, Sarah B. Kapnick, Geert Jan van Oldenborgh, Kirien Whan, Sjoukje Philip, Gabriel A. Vecchi, Roop K. Singh, Julie Arrighi, and Heidi Cullen
Hydrol. Earth Syst. Sci., 21, 897–921, https://doi.org/10.5194/hess-21-897-2017, https://doi.org/10.5194/hess-21-897-2017, 2017
Short summary
Short summary
During August 2016, heavy precipitation led to devastating floods in south Louisiana, USA. Here, we analyze the climatological statistics of the precipitation event, as defined by its 3-day total over 12–14 August. Using observational data and high-resolution global coupled model experiments, we find for a comparable event on the central US Gulf Coast an average return period of about 30 years and the odds being increased by at least 1.4 since 1900 due to anthropogenic climate change.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Andrew D. King, Tilo Ziehn, Matthew Chamberlain, Alexander R. Borowiak, Josephine R. Brown, Liam Cassidy, Andrea J. Dittus, Michael Grose, Nicola Maher, Seungmok Paik, Sarah E. Perkins-Kirkpatrick, and Aditya Sengupta
Earth Syst. Dynam., 15, 1353–1383, https://doi.org/10.5194/esd-15-1353-2024, https://doi.org/10.5194/esd-15-1353-2024, 2024
Short summary
Short summary
Governments are targeting net-zero emissions later this century with the aim of limiting global warming in line with the Paris Agreement. However, few studies explore the long-term consequences of reaching net-zero emissions and the effects of a delay in reaching net-zero. We use the Australian Earth system model to examine climate evolution under net-zero emissions. We find substantial changes which differ regionally, including continued Southern Ocean warming and Antarctic sea ice reduction.
Friederike E. L. Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Geert Jan van Oldenborgh, and Robert Vautard
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 159–171, https://doi.org/10.5194/ascmo-10-159-2024, https://doi.org/10.5194/ascmo-10-159-2024, 2024
Short summary
Short summary
To assess the role of climate change in individual weather events, different lines of evidence need to be combined in order to draw robust conclusions about whether observed changes can be attributed to anthropogenic climate change. Here we present a transparent method, developed over 8 years, to combine such lines of evidence in a single framework and draw conclusions about the overarching role of human-induced climate change in individual weather events.
Sebastian Sippel, Clair Barnes, Camille Cadiou, Erich Fischer, Sarah Kew, Marlene Kretschmer, Sjoukje Philip, Theodore G. Shepherd, Jitendra Singh, Robert Vautard, and Pascal Yiou
Weather Clim. Dynam., 5, 943–957, https://doi.org/10.5194/wcd-5-943-2024, https://doi.org/10.5194/wcd-5-943-2024, 2024
Short summary
Short summary
Winter temperatures in central Europe have increased. But cold winters can still cause problems for energy systems, infrastructure, or human health. Here we tested whether a record-cold winter, such as the one observed in 1963 over central Europe, could still occur despite climate change. The answer is yes: it is possible, but it is very unlikely. Our results rely on climate model simulations and statistical rare event analysis. In conclusion, society must be prepared for such cold winters.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024, https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
Short summary
Short summary
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Vikki Thompson, Sjoukje Y. Philip, Izidine Pinto, and Sarah F. Kew
EGUsphere, https://doi.org/10.5194/egusphere-2024-1136, https://doi.org/10.5194/egusphere-2024-1136, 2024
Short summary
Short summary
In October 2023 Storm Babet brought flooding and strong winds to the UK. We show that similar events are more likely when the North Atlantic sea surface temperatures are higher. The North Atlantic exhibits multidecadal variability impacting the sea surface temperatures. This suggests that trends in storms similar to Babet are driven by multidecadal variability more than climate change. Increasing our knowledge of the causes of extreme weather can allow us to prepare and adapt for future changes.
Rosa Pietroiusti, Inne Vanderkelen, Friederike E. L. Otto, Clair Barnes, Lucy Temple, Mary Akurut, Philippe Bally, Nicole P. M. van Lipzig, and Wim Thiery
Earth Syst. Dynam., 15, 225–264, https://doi.org/10.5194/esd-15-225-2024, https://doi.org/10.5194/esd-15-225-2024, 2024
Short summary
Short summary
Heavy rainfall in eastern Africa between late 2019 and mid 2020 caused devastating floods and landslides and drove the levels of Lake Victoria to a record-breaking maximum in May 2020. In this study, we characterize the spatial extent and impacts of the floods in the Lake Victoria basin and investigate how human-induced climate change influenced the probability and intensity of the record-breaking lake levels and flooding by applying a multi-model extreme event attribution methodology.
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, https://doi.org/10.5194/esd-15-131-2024, 2024
Short summary
Short summary
The 2022 summer was accompanied by widespread soil moisture deficits, including an unprecedented drought in Europe. Combining several observation-based estimates and models, we find that such an event has become at least 5 and 20 times more likely due to human-induced climate change in western Europe and the northern extratropics, respectively. Strong regional warming fuels soil desiccation; hence, projections indicate even more potent future droughts as we progress towards a 2 °C warmer world.
Henrique M. D. Goulart, Irene Benito Lazaro, Linda van Garderen, Karin van der Wiel, Dewi Le Bars, Elco Koks, and Bart van den Hurk
Nat. Hazards Earth Syst. Sci., 24, 29–45, https://doi.org/10.5194/nhess-24-29-2024, https://doi.org/10.5194/nhess-24-29-2024, 2024
Short summary
Short summary
We explore how Hurricane Sandy (2012) could flood New York City under different scenarios, including climate change and internal variability. We find that sea level rise can quadruple coastal flood volumes, while changes in Sandy's landfall location can double flood volumes. Our results show the need for diverse scenarios that include climate change and internal variability and for integrating climate information into a modelling framework, offering insights for high-impact event assessments.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
Short summary
Short summary
The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri
Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
Short summary
Short summary
A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
Sigrid Jørgensen Bakke, Niko Wanders, Karin van der Wiel, and Lena Merete Tallaksen
Nat. Hazards Earth Syst. Sci., 23, 65–89, https://doi.org/10.5194/nhess-23-65-2023, https://doi.org/10.5194/nhess-23-65-2023, 2023
Short summary
Short summary
In this study, we developed a machine learning model to identify dominant controls of wildfire in Fennoscandia and produce monthly fire danger probability maps. The dominant control was shallow-soil water anomaly, followed by air temperature and deep soil water. The model proved skilful with a similar performance as the existing Canadian Forest Fire Weather Index (FWI). We highlight the benefit of using data-driven models jointly with other fire models to improve fire monitoring and prediction.
Sjoukje Y. Philip, Sarah F. Kew, Geert Jan van Oldenborgh, Faron S. Anslow, Sonia I. Seneviratne, Robert Vautard, Dim Coumou, Kristie L. Ebi, Julie Arrighi, Roop Singh, Maarten van Aalst, Carolina Pereira Marghidan, Michael Wehner, Wenchang Yang, Sihan Li, Dominik L. Schumacher, Mathias Hauser, Rémy Bonnet, Linh N. Luu, Flavio Lehner, Nathan Gillett, Jordis S. Tradowsky, Gabriel A. Vecchi, Chris Rodell, Roland B. Stull, Rosie Howard, and Friederike E. L. Otto
Earth Syst. Dynam., 13, 1689–1713, https://doi.org/10.5194/esd-13-1689-2022, https://doi.org/10.5194/esd-13-1689-2022, 2022
Short summary
Short summary
In June 2021, the Pacific Northwest of the US and Canada saw record temperatures far exceeding those previously observed. This attribution study found such a severe heat wave would have been virtually impossible without human-induced climate change. Assuming no nonlinear interactions, such events have become at least 150 times more common, are about 2 °C hotter and will become even more common as warming continues. Therefore, adaptation and mitigation are urgently needed to prepare society.
Kathrin Wehrli, Fei Luo, Mathias Hauser, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, Dim Coumou, Wilhelm May, Philippe Le Sager, Frank Selten, Olivia Martius, Robert Vautard, and Sonia I. Seneviratne
Earth Syst. Dynam., 13, 1167–1196, https://doi.org/10.5194/esd-13-1167-2022, https://doi.org/10.5194/esd-13-1167-2022, 2022
Short summary
Short summary
The ExtremeX experiment was designed to unravel the contribution of processes leading to the occurrence of recent weather and climate extremes. Global climate simulations are carried out with three models. The results show that in constrained experiments, temperature anomalies during heatwaves are well represented, although climatological model biases remain. Further, a substantial contribution of both atmospheric circulation and soil moisture to heat extremes is identified.
Daniel M. Gilford, Andrew Pershing, Benjamin H. Strauss, Karsten Haustein, and Friederike E. L. Otto
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 135–154, https://doi.org/10.5194/ascmo-8-135-2022, https://doi.org/10.5194/ascmo-8-135-2022, 2022
Short summary
Short summary
We developed a framework to produce global real-time estimates of how human-caused climate change affects the likelihood of daily weather events. A multi-method approach provides ensemble attribution estimates accompanied by confidence intervals, creating new opportunities for climate change communication. Methodological efficiency permits daily analysis using forecasts or observations. Applications with daily maximum temperature highlight the framework's capacity on daily and global scales.
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences, 19, 1979–1993, https://doi.org/10.5194/bg-19-1979-2022, https://doi.org/10.5194/bg-19-1979-2022, 2022
Short summary
Short summary
Droughts and heatwaves are expected to occur more often in the future, but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extreme occurrences and a vegetation model to analyse these effects. Tree coverage and associated plant productivity increase under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single droughts or heatwaves.
Linh N. Luu, Robert Vautard, Pascal Yiou, and Jean-Michel Soubeyroux
Earth Syst. Dynam., 13, 687–702, https://doi.org/10.5194/esd-13-687-2022, https://doi.org/10.5194/esd-13-687-2022, 2022
Short summary
Short summary
This study downscales climate information from EURO-CORDEX (approx. 12 km) output to a higher horizontal resolution (approx. 3 km) for the south of France. We also propose a matrix of different indices to evaluate the high-resolution precipitation output. We find that a higher resolution reproduces more realistic extreme precipitation events at both daily and sub-daily timescales. Our results and approach are promising to apply to other Mediterranean regions and climate impact studies.
Henrique M. D. Goulart, Karin van der Wiel, Christian Folberth, Juraj Balkovic, and Bart van den Hurk
Earth Syst. Dynam., 12, 1503–1527, https://doi.org/10.5194/esd-12-1503-2021, https://doi.org/10.5194/esd-12-1503-2021, 2021
Short summary
Short summary
Agriculture is sensitive to weather conditions and to climate change. We identify the weather conditions linked to soybean failures and explore changes related to climate change. Additionally, we build future versions of a historical extreme season under future climate scenarios. Results show that soybean failures are likely to increase with climate change. Future events with similar physical conditions to the extreme season are not expected to increase, but events with similar impacts are.
Jean-Eudes Petit, Jean-Charles Dupont, Olivier Favez, Valérie Gros, Yunjiang Zhang, Jean Sciare, Leila Simon, François Truong, Nicolas Bonnaire, Tanguy Amodeo, Robert Vautard, and Martial Haeffelin
Atmos. Chem. Phys., 21, 17167–17183, https://doi.org/10.5194/acp-21-17167-2021, https://doi.org/10.5194/acp-21-17167-2021, 2021
Short summary
Short summary
The COVID-19 outbreak led to lockdowns at national scales in spring 2020. Large cuts in emissions occurred, but the quantitative assessment of their role from observations is hindered by weather and interannual variability. That is why we developed an innovative methodology in order to best characterize the impact of lockdown on atmospheric chemistry. We find that a local decrease in traffic-related pollutants triggered a decrease of secondary aerosols and an increase in ozone.
Folmer Krikken, Flavio Lehner, Karsten Haustein, Igor Drobyshev, and Geert Jan van Oldenborgh
Nat. Hazards Earth Syst. Sci., 21, 2169–2179, https://doi.org/10.5194/nhess-21-2169-2021, https://doi.org/10.5194/nhess-21-2169-2021, 2021
Short summary
Short summary
In this study, we analyse the role of climate change in the forest fires that raged through large parts of Sweden in the summer of 2018 from a meteorological perspective. This is done by studying observationally constrained data and multiple climate models. We find a small reduced probability of such events, based on reanalyses, but a small increased probability due to global warming up to now and a more robust increase in the risk for such events in the future, based on climate models.
Gijs van Kempen, Karin van der Wiel, and Lieke Anna Melsen
Nat. Hazards Earth Syst. Sci., 21, 961–976, https://doi.org/10.5194/nhess-21-961-2021, https://doi.org/10.5194/nhess-21-961-2021, 2021
Short summary
Short summary
In this study, we combine climate model results with a hydrological model to investigate uncertainties in flood and drought risk. With the climate model, 2000 years of
current climatewas created. The hydrological model consisted of several building blocks that we could adapt. In this way, we could investigate the effect of these hydrological building blocks on high- and low-flow risk in four different climate zones with return periods of up to 500 years.
Geert Jan van Oldenborgh, Folmer Krikken, Sophie Lewis, Nicholas J. Leach, Flavio Lehner, Kate R. Saunders, Michiel van Weele, Karsten Haustein, Sihan Li, David Wallom, Sarah Sparrow, Julie Arrighi, Roop K. Singh, Maarten K. van Aalst, Sjoukje Y. Philip, Robert Vautard, and Friederike E. L. Otto
Nat. Hazards Earth Syst. Sci., 21, 941–960, https://doi.org/10.5194/nhess-21-941-2021, https://doi.org/10.5194/nhess-21-941-2021, 2021
Short summary
Short summary
Southeastern Australia suffered from disastrous bushfires during the 2019/20 fire season, raising the question whether these have become more likely due to climate change. We found no attributable trend in extreme annual or monthly low precipitation but a clear shift towards more extreme heat. However, this shift is underestimated by the models. Analysing fire weather directly, we found that the chance has increased by at least 30 %, but due to the underestimation it could well be higher.
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph A. Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Earth Syst. Dynam., 12, 151–172, https://doi.org/10.5194/esd-12-151-2021, https://doi.org/10.5194/esd-12-151-2021, 2021
Short summary
Short summary
We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on LASSO regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
Short summary
Short summary
Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
Carley E. Iles, Robert Vautard, Jane Strachan, Sylvie Joussaume, Bernd R. Eggen, and Chris D. Hewitt
Geosci. Model Dev., 13, 5583–5607, https://doi.org/10.5194/gmd-13-5583-2020, https://doi.org/10.5194/gmd-13-5583-2020, 2020
Short summary
Short summary
We investigate how increased resolution affects the simulation of European climate extremes for global and regional climate models to inform modelling strategies. Precipitation extremes become heavier with higher resolution, especially over mountains, wind extremes become somewhat stronger, and for temperature extremes warm biases are reduced over mountains. Differences with resolution for the global model appear to come from downscaling effects rather than improved large-scale circulation.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
Short summary
Short summary
Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
Sophie C. Lewis, Sarah E. Perkins-Kirkpatrick, and Andrew D. King
Adv. Stat. Clim. Meteorol. Oceanogr., 5, 133–146, https://doi.org/10.5194/ascmo-5-133-2019, https://doi.org/10.5194/ascmo-5-133-2019, 2019
Short summary
Short summary
Extreme temperature and precipitation events in Australia have caused significant socio-economic and environmental impacts. Determining the factors contributing to these extremes is an active area of research. This paper describes a set of studies that have examined the causes of extreme climate events in recent years in Australia. Ideally, this review will be useful for the application of these extreme event attribution approaches to climate and weather extremes occurring elsewhere.
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
Short summary
Short summary
The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Sjoukje Philip, Sarah Sparrow, Sarah F. Kew, Karin van der Wiel, Niko Wanders, Roop Singh, Ahmadul Hassan, Khaled Mohammed, Hammad Javid, Karsten Haustein, Friederike E. L. Otto, Feyera Hirpa, Ruksana H. Rimi, A. K. M. Saiful Islam, David C. H. Wallom, and Geert Jan van Oldenborgh
Hydrol. Earth Syst. Sci., 23, 1409–1429, https://doi.org/10.5194/hess-23-1409-2019, https://doi.org/10.5194/hess-23-1409-2019, 2019
Short summary
Short summary
In August 2017 Bangladesh faced one of its worst river flooding events in recent history. For the large Brahmaputra basin, using precipitation alone as a proxy for flooding might not be appropriate. In this paper we explicitly test this assumption by performing an attribution of both precipitation and discharge as a flooding-related measure to climate change. We find the change in risk to be of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach.
Erik Kjellström, Grigory Nikulin, Gustav Strandberg, Ole Bøssing Christensen, Daniela Jacob, Klaus Keuler, Geert Lenderink, Erik van Meijgaard, Christoph Schär, Samuel Somot, Silje Lund Sørland, Claas Teichmann, and Robert Vautard
Earth Syst. Dynam., 9, 459–478, https://doi.org/10.5194/esd-9-459-2018, https://doi.org/10.5194/esd-9-459-2018, 2018
Short summary
Short summary
Based on high-resolution regional climate models we investigate European climate change at 1.5 and 2 °C of global warming compared to pre-industrial levels. Considerable near-surface warming exceeding that of the global mean is found for most of Europe, already at the lower 1.5 °C of warming level. Changes in precipitation and near-surface wind speed are identified. The 1.5 °C of warming level shows significantly less change compared to the 2 °C level, indicating the importance of mitigation.
Didin Agustian Permadi, Nguyen Thi Kim Oanh, and Robert Vautard
Atmos. Chem. Phys., 18, 3321–3334, https://doi.org/10.5194/acp-18-3321-2018, https://doi.org/10.5194/acp-18-3321-2018, 2018
Short summary
Short summary
This research quantified impacts resulted in the future (2030) from emission reduction measures for Southeast Asia (SEA) countries. Emission scenarios were developed based on current policies in Indonesia and Thailand. Impacts were quantified in terms of the avoided number of premature death and reduction in radiative forcing resulted from the emission reduction measures.
Didin Agustian Permadi, Nguyen Thi Kim Oanh, and Robert Vautard
Atmos. Chem. Phys., 18, 2725–2747, https://doi.org/10.5194/acp-18-2725-2018, https://doi.org/10.5194/acp-18-2725-2018, 2018
Short summary
Short summary
This research quantified the emissions of toxic air pollutants and climate forcing agents from Southeast Asia in 2007. The emission results were used for model simulation of particulate matter air quality. The model outputs were reasonably comparable to available ground level measurement data for both meteorology and air quality. The aerosol optical depth (AOD) for total aerosol and for black carbon alone was calculated and compared to satellite AOD.
Geert Jan van Oldenborgh, Sjoukje Philip, Sarah Kew, Michiel van Weele, Peter Uhe, Friederike Otto, Roop Singh, Indrani Pai, Heidi Cullen, and Krishna AchutaRao
Nat. Hazards Earth Syst. Sci., 18, 365–381, https://doi.org/10.5194/nhess-18-365-2018, https://doi.org/10.5194/nhess-18-365-2018, 2018
Short summary
Short summary
On 19 May 2016 a temperature of 51.0 °C in Phalodi (northwest India) set a new Indian record. In 2015 a very lethal heat wave had occurred in the southeast. We find that in India the trend in extreme temperatures due to greenhouse gases is largely cancelled by increasing air pollution and irrigation. The health impacts of heat waves do increase due to higher humidity and air pollution. This implies that we expect heat waves to become much hotter as soon as air pollution is brought under control.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
Short summary
Short summary
This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Erin Coughlan de Perez, Elisabeth Stephens, Konstantinos Bischiniotis, Maarten van Aalst, Bart van den Hurk, Simon Mason, Hannah Nissan, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 21, 4517–4524, https://doi.org/10.5194/hess-21-4517-2017, https://doi.org/10.5194/hess-21-4517-2017, 2017
Short summary
Short summary
Disaster managers would like to use seasonal forecasts to anticipate flooding months in advance. However, current seasonal forecasts give information on rainfall instead of flooding. Here, we find that the number of extreme events, rather than total rainfall, is most related to flooding in different regions of Africa. We recommend several forecast adjustments and research opportunities that would improve flood information at the seasonal timescale in different regions.
Augustin Colette, Camilla Andersson, Astrid Manders, Kathleen Mar, Mihaela Mircea, Maria-Teresa Pay, Valentin Raffort, Svetlana Tsyro, Cornelius Cuvelier, Mario Adani, Bertrand Bessagnet, Robert Bergström, Gino Briganti, Tim Butler, Andrea Cappelletti, Florian Couvidat, Massimo D'Isidoro, Thierno Doumbia, Hilde Fagerli, Claire Granier, Chris Heyes, Zig Klimont, Narendra Ojha, Noelia Otero, Martijn Schaap, Katarina Sindelarova, Annemiek I. Stegehuis, Yelva Roustan, Robert Vautard, Erik van Meijgaard, Marta Garcia Vivanco, and Peter Wind
Geosci. Model Dev., 10, 3255–3276, https://doi.org/10.5194/gmd-10-3255-2017, https://doi.org/10.5194/gmd-10-3255-2017, 2017
Short summary
Short summary
The EURODELTA-Trends numerical experiment has been designed to assess the capability of chemistry-transport models to capture the evolution of surface air quality over the 1990–2010 period in Europe. It also includes sensitivity experiments in order to analyse the relative contribution of (i) emission changes, (ii) meteorological variability, and (iii) boundary conditions to air quality trends. The article is a detailed presentation of the experiment design and participating models.
Benoit P. Guillod, Richard G. Jones, Andy Bowery, Karsten Haustein, Neil R. Massey, Daniel M. Mitchell, Friederike E. L. Otto, Sarah N. Sparrow, Peter Uhe, David C. H. Wallom, Simon Wilson, and Myles R. Allen
Geosci. Model Dev., 10, 1849–1872, https://doi.org/10.5194/gmd-10-1849-2017, https://doi.org/10.5194/gmd-10-1849-2017, 2017
Short summary
Short summary
The weather@home climate modelling system uses the computing power of volunteers around the world to generate a very large number of climate model simulations. This is particularly useful when investigating extreme weather events, notably for the attribution of these events to anthropogenic climate change. A new version of weather@home is presented and evaluated, which includes an improved representation of the land surface and increased horizontal resolution over Europe.
Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 17–31, https://doi.org/10.5194/ascmo-3-17-2017, https://doi.org/10.5194/ascmo-3-17-2017, 2017
Short summary
Short summary
The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.
Karin van der Wiel, Sarah B. Kapnick, Geert Jan van Oldenborgh, Kirien Whan, Sjoukje Philip, Gabriel A. Vecchi, Roop K. Singh, Julie Arrighi, and Heidi Cullen
Hydrol. Earth Syst. Sci., 21, 897–921, https://doi.org/10.5194/hess-21-897-2017, https://doi.org/10.5194/hess-21-897-2017, 2017
Short summary
Short summary
During August 2016, heavy precipitation led to devastating floods in south Louisiana, USA. Here, we analyze the climatological statistics of the precipitation event, as defined by its 3-day total over 12–14 August. Using observational data and high-resolution global coupled model experiments, we find for a comparable event on the central US Gulf Coast an average return period of about 30 years and the odds being increased by at least 1.4 since 1900 due to anthropogenic climate change.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
Short summary
Short summary
The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Mitchell T. Black, David J. Karoly, Suzanne M. Rosier, Sam M. Dean, Andrew D. King, Neil R. Massey, Sarah N. Sparrow, Andy Bowery, David Wallom, Richard G. Jones, Friederike E. L. Otto, and Myles R. Allen
Geosci. Model Dev., 9, 3161–3176, https://doi.org/10.5194/gmd-9-3161-2016, https://doi.org/10.5194/gmd-9-3161-2016, 2016
Short summary
Short summary
This study presents a citizen science computing project, known as weather@home Australia–New Zealand, which runs climate models on thousands of home computers. By harnessing the power of volunteers' computers, this project is capable of simulating extreme weather events over Australia and New Zealand under different climate scenarios.
Erin Coughlan de Perez, Bart van den Hurk, Maarten K. van Aalst, Irene Amuron, Deus Bamanya, Tristan Hauser, Brenden Jongma, Ana Lopez, Simon Mason, Janot Mendler de Suarez, Florian Pappenberger, Alexandra Rueth, Elisabeth Stephens, Pablo Suarez, Jurjen Wagemaker, and Ervin Zsoter
Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, https://doi.org/10.5194/hess-20-3549-2016, 2016
Short summary
Short summary
Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.
Geert Jan van Oldenborgh, Sjoukje Philip, Emma Aalbers, Robert Vautard, Friederike Otto, Karsten Haustein, Florence Habets, Roop Singh, and Heidi Cullen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-308, https://doi.org/10.5194/hess-2016-308, 2016
Manuscript not accepted for further review
Short summary
Short summary
Extreme rain caused flooding in France and Germany at the end of May 2016. After such an event the question is always posed to what extent it can be attributed to anthropogenic climate change. Using observations and five model ensembles we give a first answer. For the 3-day precipitation extremes over the Seine and Loire basins that caused the flooding all methods agree that the probability has increased by a factor of about two. For 1-day precipitation extremes in Germany the methods disagree.
Li Liu, Fabien Solmon, Robert Vautard, Lynda Hamaoui-Laguel, Csaba Zsolt Torma, and Filippo Giorgi
Biogeosciences, 13, 2769–2786, https://doi.org/10.5194/bg-13-2769-2016, https://doi.org/10.5194/bg-13-2769-2016, 2016
Short summary
Short summary
To study the distribution of airborne ragweed pollen in changing environments and associated health risks over Europe, we introduce an approach with explicit treatment of pollen ripening, release and dispersion due to environmental drivers in an online modelling framework where climate is integrated with dispersion and vegetation production. From a simulated pollen season and concentration pattern health risks are evaluated through calculation of exposure time above health-relevant threshold levels.
Konstantinos Markakis, Myrto Valari, Magnuz Engardt, Gwendoline Lacressonniere, Robert Vautard, and Camilla Andersson
Atmos. Chem. Phys., 16, 1877–1894, https://doi.org/10.5194/acp-16-1877-2016, https://doi.org/10.5194/acp-16-1877-2016, 2016
Short summary
Short summary
The overall climate benefit at both cities and pollutants is −2 to −10 % depending on metric. Over the city of Paris local mitigation of NOx emissions increases future ozone due to titration inhibition. Climate is the most influential factor for maximum ozone in Paris, which is particularly interesting from a health impact perspective. Over urban areas with major regional contribution (e.g. Stockholm) the bias due to coarse emission inventory may lead to policy misclassification.
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
Short summary
Short summary
We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
G. J. van Oldenborgh, F. E. L. Otto, K. Haustein, and H. Cullen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-13197-2015, https://doi.org/10.5194/hessd-12-13197-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
On 4–6 December 2015, the storm 'Desmond' caused very heavy rainfall in northern England and Scotland, which led to widespread flooding. We provide an initial assessment of the influence of anthropogenic climate change on the likelihood of precipitation events like this. We use three independent methods of extreme event attribution based on observations and two climate models. All methods agree that the effect of climate change is positive, making events like this about 40% (5–80%) more likely.
J. M. Eden, G. J. van Oldenborgh, E. Hawkins, and E. B. Suckling
Geosci. Model Dev., 8, 3947–3973, https://doi.org/10.5194/gmd-8-3947-2015, https://doi.org/10.5194/gmd-8-3947-2015, 2015
Short summary
Short summary
Our paper reports on a simple regression-based system for producing probabilistic forecasts of seasonal climate. We discuss the physical motivation behind the statistical relationships underpinning our empirical model and provide a validation of hindcasts produced for the last half century. The generation of probabilistic forecasts on a global scale along with the use of the long-term trend as a source of skill constitutes a novel approach to empirical forecasting of seasonal climate.
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
Short summary
Short summary
Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
E. Coughlan de Perez, B. van den Hurk, M. K. van Aalst, B. Jongman, T. Klose, and P. Suarez
Nat. Hazards Earth Syst. Sci., 15, 895–904, https://doi.org/10.5194/nhess-15-895-2015, https://doi.org/10.5194/nhess-15-895-2015, 2015
Short summary
Short summary
How can we use weather or climate forecasts to avoid disasters? This article offers a framework for determining when it is "worth" taking action to try to avoid a potential disaster. Considering forecast probabilities, actions, and funding constraints, we propose a novel forecast-based financing system that would automatically trigger action based on forecasts of increased risks.
E. Katragkou, M. García-Díez, R. Vautard, S. Sobolowski, P. Zanis, G. Alexandri, R. M. Cardoso, A. Colette, J. Fernandez, A. Gobiet, K. Goergen, T. Karacostas, S. Knist, S. Mayer, P. M. M. Soares, I. Pytharoulis, I. Tegoulias, A. Tsikerdekis, and D. Jacob
Geosci. Model Dev., 8, 603–618, https://doi.org/10.5194/gmd-8-603-2015, https://doi.org/10.5194/gmd-8-603-2015, 2015
K. Markakis, M. Valari, A. Colette, O. Sanchez, O. Perrussel, C. Honore, R. Vautard, Z. Klimont, and S. Rao
Atmos. Chem. Phys., 14, 7323–7340, https://doi.org/10.5194/acp-14-7323-2014, https://doi.org/10.5194/acp-14-7323-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
L. Menut, R. Vautard, A. Colette, D. Khvorostyanov, A. Potier, L. Hamaoui-Laguel, N. Viovy, and M. Thibaudon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-10891-2014, https://doi.org/10.5194/acpd-14-10891-2014, 2014
Revised manuscript not accepted
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
S. F. Kew, F. M. Selten, G. Lenderink, and W. Hazeleger
Nat. Hazards Earth Syst. Sci., 13, 2017–2029, https://doi.org/10.5194/nhess-13-2017-2013, https://doi.org/10.5194/nhess-13-2017-2013, 2013
A. Colette, B. Bessagnet, R. Vautard, S. Szopa, S. Rao, S. Schucht, Z. Klimont, L. Menut, G. Clain, F. Meleux, G. Curci, and L. Rouïl
Atmos. Chem. Phys., 13, 7451–7471, https://doi.org/10.5194/acp-13-7451-2013, https://doi.org/10.5194/acp-13-7451-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
Related subject area
Climate research
Identifying time patterns of highland and lowland air temperature trends in Italy and the UK across monthly and annual scales
Formally combining different lines of evidence in extreme-event attribution
Environmental sensitivity of the Caribbean economic growth rate
Spatial patterns and indices for heat waves and droughts over Europe using a decomposition of extremal dependency
Changes in the distribution of annual maximum temperatures in Europe
Evaluating skills and issues of quantile-based bias adjustment for climate change scenarios
Comparing climate time series – Part 4: Annual cycles
Statistical reconstruction of European winter snowfall in reanalysis and climate models based on air temperature and total precipitation
A multi-method framework for global real-time climate attribution
Analysis of the evolution of parametric drivers of high-end sea-level hazards
Comparing climate time series – Part 3: Discriminant analysis
Spatial heterogeneity in rain-bearing winds, seasonality and rainfall variability in southern Africa's winter rainfall zone
Spatial heterogeneity of 2015–2017 drought intensity in South Africa's winter rainfall zone
A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level
A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5
The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models
A new energy-balance approach to linear filtering for estimating effective radiative forcing from temperature time series
Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany
Possible impacts of climate change on fog in the Arctic and subpolar North Atlantic
Approaches to attribution of extreme temperature and precipitation events using multi-model and single-member ensembles of general circulation models
Comparison and assessment of large-scale surface temperature in climate model simulations
Future climate emulations using quantile regressions on large ensembles
Downscaling probability of long heatwaves based on seasonal mean daily maximum temperatures
Estimates of climate system properties incorporating recent climate change
The joint influence of break and noise variance on the break detection capability in time series homogenization
A space–time statistical climate model for hurricane intensification in the North Atlantic basin
Building a traceable climate model hierarchy with multi-level emulators
Chalachew Muluken Liyew, Elvira Di Nardo, Rosa Meo, and Stefano Ferraris
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 173–194, https://doi.org/10.5194/ascmo-10-173-2024, https://doi.org/10.5194/ascmo-10-173-2024, 2024
Short summary
Short summary
Global warming is a big issue: it is necessary to know more details to make a forecast model and plan adaptation measures. Warming varies in space and time and models often average it over large areas. However, it shows great variations between months of the year. It also varies between regions of the world and between lowland and highland regions. This paper uses statistical and machine learning techniques to quantify such differences between Italy and the UK at different altitudes.
Friederike E. L. Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Geert Jan van Oldenborgh, and Robert Vautard
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 159–171, https://doi.org/10.5194/ascmo-10-159-2024, https://doi.org/10.5194/ascmo-10-159-2024, 2024
Short summary
Short summary
To assess the role of climate change in individual weather events, different lines of evidence need to be combined in order to draw robust conclusions about whether observed changes can be attributed to anthropogenic climate change. Here we present a transparent method, developed over 8 years, to combine such lines of evidence in a single framework and draw conclusions about the overarching role of human-induced climate change in individual weather events.
Mark R. Jury
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 95–104, https://doi.org/10.5194/ascmo-10-95-2024, https://doi.org/10.5194/ascmo-10-95-2024, 2024
Short summary
Short summary
A unique link is found between the Caribbean GDP growth rate and the tropical climate system. Although the Pacific El Niño–Southern Oscillation governs some aspects of this link, the Walker circulation and associated humidity over the equatorial Atlantic emerge as leading predictors of economic prosperity in the central Antilles islands.
Svenja Szemkus and Petra Friederichs
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 29–49, https://doi.org/10.5194/ascmo-10-29-2024, https://doi.org/10.5194/ascmo-10-29-2024, 2024
Short summary
Short summary
This paper uses the tail pairwise dependence matrix (TPDM) proposed by Cooley and Thibaud (2019), which we extend to the description of common extremes in two variables. We develop an extreme pattern index (EPI), a pattern-based aggregation to describe spatially extended weather extremes. Our results show that the EPI is suitable for describing heat waves. We extend the EPI to describe extremes in two variables and obtain an index to describe compound precipitation deficits and heat waves.
Graeme Auld, Gabriele C. Hegerl, and Ioannis Papastathopoulos
Adv. Stat. Clim. Meteorol. Oceanogr., 9, 45–66, https://doi.org/10.5194/ascmo-9-45-2023, https://doi.org/10.5194/ascmo-9-45-2023, 2023
Short summary
Short summary
In this paper we consider the problem of detecting changes in the distribution of the annual maximum temperature, during the years 1950–2018, across Europe.
We find that, on average, the temperature that would be expected to be exceeded
approximately once every 100 years in the 1950 climate is expected to be exceeded once every 6 years in the 2018 climate. This is of concern due to the devastating effects on humans and natural systems that are caused by extreme temperatures.
Fabian Lehner, Imran Nadeem, and Herbert Formayer
Adv. Stat. Clim. Meteorol. Oceanogr., 9, 29–44, https://doi.org/10.5194/ascmo-9-29-2023, https://doi.org/10.5194/ascmo-9-29-2023, 2023
Short summary
Short summary
Climate model output has systematic errors which can be reduced with statistical methods. We review existing bias-adjustment methods for climate data and discuss their skills and issues. We define three demands for the method and then evaluate them using real and artificially created daily temperature and precipitation data for Austria to show how biases can also be introduced with bias-adjustment methods themselves.
Timothy DelSole and Michael K. Tippett
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 187–203, https://doi.org/10.5194/ascmo-8-187-2022, https://doi.org/10.5194/ascmo-8-187-2022, 2022
Short summary
Short summary
Most climate time series contain annual and diurnal cycles. However, an objective criterion for deciding whether two time series have statistically equivalent annual and diurnal cycles is lacking, particularly if the residual variability is serially correlated. Such a criterion would be helpful in deciding whether a new version of a climate model better simulates such cycles. This paper derives an objective rule for such decisions based on a rigorous statistical framework.
Flavio Maria Emanuele Pons and Davide Faranda
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 155–186, https://doi.org/10.5194/ascmo-8-155-2022, https://doi.org/10.5194/ascmo-8-155-2022, 2022
Short summary
Short summary
The objective motivating this study is the assessment of the impacts of winter climate extremes, which requires accurate simulation of snowfall. However, climate simulation models contain physical approximations, which result in biases that must be corrected using past data as a reference. We show how to exploit simulated temperature and precipitation to estimate snowfall from already bias-corrected variables, without requiring the elaboration of complex, multivariate bias adjustment techniques.
Daniel M. Gilford, Andrew Pershing, Benjamin H. Strauss, Karsten Haustein, and Friederike E. L. Otto
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 135–154, https://doi.org/10.5194/ascmo-8-135-2022, https://doi.org/10.5194/ascmo-8-135-2022, 2022
Short summary
Short summary
We developed a framework to produce global real-time estimates of how human-caused climate change affects the likelihood of daily weather events. A multi-method approach provides ensemble attribution estimates accompanied by confidence intervals, creating new opportunities for climate change communication. Methodological efficiency permits daily analysis using forecasts or observations. Applications with daily maximum temperature highlight the framework's capacity on daily and global scales.
Alana Hough and Tony E. Wong
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 117–134, https://doi.org/10.5194/ascmo-8-117-2022, https://doi.org/10.5194/ascmo-8-117-2022, 2022
Short summary
Short summary
We use machine learning to assess how different geophysical uncertainties relate to the severity of future sea-level rise. We show how the contributions to coastal hazard from different sea-level processes evolve over time and find that near-term sea-level hazards are driven by thermal expansion and the melting of glaciers and ice caps, while long-term hazards are driven by ice loss from the major ice sheets.
Timothy DelSole and Michael K. Tippett
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 97–115, https://doi.org/10.5194/ascmo-8-97-2022, https://doi.org/10.5194/ascmo-8-97-2022, 2022
Short summary
Short summary
A common problem in climate studies is to decide whether a climate model is realistic. Such decisions are not straightforward because the time series are serially correlated and multivariate. Part II derived a test for deciding wether a simulation is statistically distinguishable from observations. However, the test itself provides no information about the nature of those differences. This paper develops a systematic and optimal approach to diagnosing differences between stochastic processes.
Willem Stefaan Conradie, Piotr Wolski, and Bruce Charles Hewitson
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 31–62, https://doi.org/10.5194/ascmo-8-31-2022, https://doi.org/10.5194/ascmo-8-31-2022, 2022
Short summary
Short summary
Cape Town is situated in a small but ecologically and climatically highly diverse and vulnerable pocket of South Africa uniquely receiving its rain mostly in winter. We show complex structures in the spatial patterns of rainfall seasonality and year-to-year changes in rainfall within this domain, tied to spatial differences in the rain-bearing winds. This allows us to develop a new spatial subdivision of the region to help future studies distinguish spatially distinct climate change responses.
Willem Stefaan Conradie, Piotr Wolski, and Bruce Charles Hewitson
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 63–81, https://doi.org/10.5194/ascmo-8-63-2022, https://doi.org/10.5194/ascmo-8-63-2022, 2022
Short summary
Short summary
The
Day Zerowater crisis affecting Cape Town after the severe 2015–2017 drought motivated renewed research interest into causes and projections of rainfall variability and change in this water-stressed region. Unusually few wet months and very wet days characterised the Day Zero Drought. Its extent expanded as it shifted gradually north-eastward, concurrent with changes in the weather systems driving drought. Our results emphasise the need to consider the interplay between drought drivers.
Erica L. Ashe, Nicole S. Khan, Lauren T. Toth, Andrea Dutton, and Robert E. Kopp
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 1–29, https://doi.org/10.5194/ascmo-8-1-2022, https://doi.org/10.5194/ascmo-8-1-2022, 2022
Short summary
Short summary
We develop a new technique to integrate realistic uncertainties in probabilistic models of past sea-level change. The new framework performs better than past methods (in precision, accuracy, bias, and model fit) because it enables the incorporation of previously unused data and exploits correlations in the data. This method has the potential to assess the validity of past estimates of extreme sea-level rise and highstands providing better context in which to place current sea-level change.
Katherine Dagon, Benjamin M. Sanderson, Rosie A. Fisher, and David M. Lawrence
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 223–244, https://doi.org/10.5194/ascmo-6-223-2020, https://doi.org/10.5194/ascmo-6-223-2020, 2020
Short summary
Short summary
Uncertainties in land model projections are important to understand in order to build confidence in Earth system modeling. In this paper, we introduce a framework for estimating uncertain land model parameters with machine learning. This method increases the computational efficiency of this process relative to traditional hand tuning approaches and provides objective methods to assess the results. We further identify key processes and parameters that are important for accurate land modeling.
Mark D. Risser and Michael F. Wehner
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 115–139, https://doi.org/10.5194/ascmo-6-115-2020, https://doi.org/10.5194/ascmo-6-115-2020, 2020
Short summary
Short summary
Evaluation of modern high-resolution global climate models often does not account for the geographic location of the underlying weather station data. In this paper, we quantify the impact of geographic sampling on the relative performance of climate model representations of precipitation extremes over the United States. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance.
Donald P. Cummins, David B. Stephenson, and Peter A. Stott
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 91–102, https://doi.org/10.5194/ascmo-6-91-2020, https://doi.org/10.5194/ascmo-6-91-2020, 2020
Short summary
Short summary
We have developed a novel and fast statistical method for diagnosing effective radiative forcing (ERF), a measure of the net effect of greenhouse gas emissions on Earth's energy budget. Our method works by inverting a recursive digital filter energy balance representation of global climate models and has been successfully validated using simulated data from UK Met Office climate models. We have estimated time series of historical ERF by applying our method to the global temperature record.
Meagan Carney and Holger Kantz
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 61–77, https://doi.org/10.5194/ascmo-6-61-2020, https://doi.org/10.5194/ascmo-6-61-2020, 2020
Short summary
Short summary
Extremes in weather can have lasting effects on human health and resource consumption. Studying the recurrence of these events on a regional scale can improve response times and provide insight into a changing climate. We introduce a set of clustering tools that allow for regional clustering of weather recordings from stations across Germany. We use these clusters to form regional models of summer temperature extremes and find an increase in the mean from 1960 to 2018.
Richard E. Danielson, Minghong Zhang, and William A. Perrie
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 31–43, https://doi.org/10.5194/ascmo-6-31-2020, https://doi.org/10.5194/ascmo-6-31-2020, 2020
Short summary
Short summary
Visibility is estimated for the 21st century using global and regional climate model output. A baseline decrease in visibility in the Arctic (10 %) is more notable than in the North Atlantic (< 5 %). We develop an adjustment that yields greater consistency among models and explore the justification of our ad hoc adjustment toward ship observations during the historical period. Baseline estimates are found to be sensitive to the representation of temperature and humidity.
Sophie C. Lewis, Sarah E. Perkins-Kirkpatrick, and Andrew D. King
Adv. Stat. Clim. Meteorol. Oceanogr., 5, 133–146, https://doi.org/10.5194/ascmo-5-133-2019, https://doi.org/10.5194/ascmo-5-133-2019, 2019
Short summary
Short summary
Extreme temperature and precipitation events in Australia have caused significant socio-economic and environmental impacts. Determining the factors contributing to these extremes is an active area of research. This paper describes a set of studies that have examined the causes of extreme climate events in recent years in Australia. Ideally, this review will be useful for the application of these extreme event attribution approaches to climate and weather extremes occurring elsewhere.
Raquel Barata, Raquel Prado, and Bruno Sansó
Adv. Stat. Clim. Meteorol. Oceanogr., 5, 67–85, https://doi.org/10.5194/ascmo-5-67-2019, https://doi.org/10.5194/ascmo-5-67-2019, 2019
Matz A. Haugen, Michael L. Stein, Ryan L. Sriver, and Elisabeth J. Moyer
Adv. Stat. Clim. Meteorol. Oceanogr., 5, 37–55, https://doi.org/10.5194/ascmo-5-37-2019, https://doi.org/10.5194/ascmo-5-37-2019, 2019
Short summary
Short summary
This work uses current temperature observations combined with climate models to project future temperature estimates, e.g., 100 years into the future. We accomplish this by modeling temperature as a smooth function of time both in the seasonal variation as well as in the annual trend. These smooth functions are estimated at multiple quantiles that are all projected into the future. We hope that this work can be used as a template for how other climate variables can be projected into the future.
Rasmus E. Benestad, Bob van Oort, Flavio Justino, Frode Stordal, Kajsa M. Parding, Abdelkader Mezghani, Helene B. Erlandsen, Jana Sillmann, and Milton E. Pereira-Flores
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 37–52, https://doi.org/10.5194/ascmo-4-37-2018, https://doi.org/10.5194/ascmo-4-37-2018, 2018
Short summary
Short summary
A new study indicates that heatwaves in India will become more frequent and last longer with global warming. Its results were derived from a large number of global climate models, and the calculations differed from previous studies in the way they included advanced statistical theory. The projected changes in the Indian heatwaves will have a negative consequence for wheat crops in India.
Alex G. Libardoni, Chris E. Forest, Andrei P. Sokolov, and Erwan Monier
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 19–36, https://doi.org/10.5194/ascmo-4-19-2018, https://doi.org/10.5194/ascmo-4-19-2018, 2018
Short summary
Short summary
We present new probabilistic estimates of model parameters in the MIT Earth System Model using more recent data and an updated method. Model output is compared to observed climate change to determine which sets of model parameters best simulate the past. In response to increasing surface temperatures and accelerated heat storage in the ocean, our estimates of climate sensitivity and ocean diffusivity are higher. Using a new interpolation algorithm results in smoother probability distributions.
Ralf Lindau and Victor Karel Christiaan Venema
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 1–18, https://doi.org/10.5194/ascmo-4-1-2018, https://doi.org/10.5194/ascmo-4-1-2018, 2018
Short summary
Short summary
Climate data contain spurious breaks, e.g., by relocation of stations, which makes it difficult to infer the secular temperature trend. Homogenization algorithms use the difference time series of neighboring stations to detect and eliminate this spurious break signal. For low signal-to-noise ratios, i.e., large distances between stations, the correct break positions may not only remain undetected, but segmentations explaining mainly the noise can be erroneously assessed as significant and true.
Erik Fraza, James B. Elsner, and Thomas H. Jagger
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 105–114, https://doi.org/10.5194/ascmo-2-105-2016, https://doi.org/10.5194/ascmo-2-105-2016, 2016
Short summary
Short summary
Climate influences on hurricane intensification are investigated by averaging hourly intensification rates over the period 1975–2014 in 8° by 8° latitude–longitude grid cells. The statistical effects of hurricane intensity, sea-surface temperature (SST), El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Madden–Julian Oscillation (MJO) are quantified. Intensity, SST, and NAO had a positive effect on intensification rates. The NAO effect should be further studied.
Giang T. Tran, Kevin I. C. Oliver, András Sóbester, David J. J. Toal, Philip B. Holden, Robert Marsh, Peter Challenor, and Neil R. Edwards
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 17–37, https://doi.org/10.5194/ascmo-2-17-2016, https://doi.org/10.5194/ascmo-2-17-2016, 2016
Short summary
Short summary
In this work, we combine the information from a complex and a simple atmospheric model to efficiently build a statistical representation (an emulator) of the complex model and to study the relationship between them. Thanks to the improved efficiency, this process is now feasible for complex models, which are slow and costly to run. The constructed emulator provide approximations of the model output, allowing various analyses to be made without the need to run the complex model again.
Cited articles
Allen, M. R.: Liability for climate change, Nature, 421, 891–892,
https://doi.org/10.1038/421891a, 2003. a
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and
the hydrologic cycle, Nature, 419, 224–232, https://doi.org/10.1038/nature01092, 2002. a
Annan, J. D. and Hargreaves, J. C.: Reliability of the CMIP3 ensemble,
Geophys. Res. Lett., 37, L02703, https://doi.org/10.1029/2009GL041994, 2010. a
Bellprat, O. and Doblas-Reyes, F.: Attribution of extreme weather and climate
events overestimated by unreliable climate simulations, Geophys. Res.
Lett., 43, 2158–2164, https://doi.org/10.1002/2015GL067189,
2016. a
Bellprat, O., Guemas, V., Doblas-Reyes, F., and Donat, M. G.: Towards reliable
extreme weather and climate event attribution, Nat. Commun., 10,
1732, https://doi.org/10.1038/s41467-019-09729-2, 2019. a, b, c
Bindoff, N. L., Stott, P. A., AchutaRao, K., Allen, M. R., Gillett, N. P., Gutzler, D., Hansingo, K., Hegerl, G. C., Hu, Y., Jain, S., Mokhov, I. I., Overland, J., Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and Attribution of Climate
Change: from Global to Regional, in: Climate Change 2013: The Physical
Science Basis, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., chap. 10, pp. 867–952,
Cambridge University Press, Cambridge, UK and New York, USA, 2013. a, b, c
Brandsma, T.: Homogenization of daily temperature data of the five principal
stations in the Netherlands (version 1.0), Technical report 356, KNMI, De
Bilt, the Netherlands,
available at: http://bibliotheek.knmi.nl/knmipubTR/TR356.pdf (last access: 31 October 2018), 2016. a
Buishand, T. A.: Extreme rainfall estimation by combining data from several
sites, Hydrol. Sci. J., 36, 345–365,
https://doi.org/10.1080/02626669109492519, 1991. a
Cattiaux, J. and Ribes, A.: Defining Single Extreme Weather Events in a Climate
Perspective, B. Am. Meteorol. Soc., 99, 1557–1568,
https://doi.org/10.1175/BAMS-D-17-0281.1, 2018. a
Cheng, L., Hoerling, M., Smith, L., and Eischeid, J.: Diagnosing Human-Induced
Dynamic and Thermodynamic Drivers of Extreme Rainfall, J. Climate, 31,
1029–1051, https://doi.org/10.1175/JCLI-D-16-0919.1, 2018. a
Ciavarella, A., Christidis, N., Andrews, M., Groenendijk, M., Rostron, J.,
Elkington, M., Burke, C., Lott, F. C., and Stott, P. A.: Upgrade of the
HadGEM3-A based attribution system to high resolution and a new validation
framework for probabilistic event attribution, Weather and Climate Extremes,
20, 9–32, https://doi.org/10.1016/j.wace.2018.03.003, 2018. a
Cipullo, M. L.: High Resolution Modeling Studies of the Changing Risks or
Damage from Extratropical Cyclones, PhD thesis, North Carolina State
University, Raleigh, 2013. a
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J.,
Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P.,
Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman,
P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri,
M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L.,
Woodruff, S. D., and Worley, S. J.: The Twentieth Century Reanalysis
Project, Q. J. Roy. Meteor. Soc., 137, 1–28, https://doi.org/10.1002/qj.776,
2011. a
Copsey, D., Sutton, R., and Knight, J. R.: Recent trends in sea level pressure
in the Indian Ocean region, Geophys. Res. Lett., 33, L19712,
https://doi.org/10.1029/2006GL027175, 2006. a
Cowan, T., Hegerl, G. C., Schurer, A., Tett, S. F. B., Vautard, R., Yiou, P.,
Jézéquel, A., Otto, F. E. L., Harrington, L. J., and Ng, B.: Ocean
and land forcing of the record-breaking Dust Bowl heatwaves across central
United States, Nat. Commun., 11, 2870,
https://doi.org/10.1038/s41467-020-16676-w, 2020. a
de' Donato, F. K., Leone, M., Scortichini, M., De Sario, M., Katsouyanni, K.,
Lanki, T., Basagaña, X., Ballester, F., Åström, C., Paldy, A.,
Pascal, M., Gasparrini, A., Menne, B., and Michelozzi, P.: Changes in the
Effect of Heat on Mortality in the Last 20 Years in Nine European Cities.
Results from the PHASE Project, Int. J. Env.
Res. Pub. He., 12, 15567–15583,
https://doi.org/10.3390/ijerph121215006, 2015. a
D'Ippoliti, D., Michelozzi, P., Marino, C., de'Donato, F., Menne, B.,
Katsouyanni, K., Kirchmayer, U., Analitis, A., Medina-Ramón, M., Paldy,
A., Atkinson, R., Kovats, S., Bisanti, L., Schneider, A., Lefranc, A.,
Iñiguez, C., and Perucci, C. A.: The impact of heat waves on mortality
in 9 European cities: results from the EuroHEAT project, Environ.
Health, 9, 37, https://doi.org/10.1186/1476-069X-9-37, 2010. a
Easterling, D. R., Kunkel, K. E., F., W. M., and Sun, L.: Detection and
attribution of climate extremes in the observed record, Weather and Climate
Extremes, 11, 17–27, https://doi.org/10.1016/j.wace.2016.01.001, 2016. a
Eden, J. M., Wolter, K., Otto, F. E. L., and van Oldenborgh, G. J.:
Multi-method attribution analysis of extreme precipitation in Boulder,
Colorado, Environ. Res. Lett., 11, 124009,
https://doi.org/10.1088/1748-9326/11/12/124009, 2016. a, b, c, d
Eden, J. M., Kew, S. F., Bellprat, O., Lenderink, G., Manola, I., Omrani, H.,
and van Oldenborgh, G. J.: Extreme precipitation in the Netherlands: An
event attribution case study, Weather and Climate Extremes, 21, 90–101,
https://doi.org/10.1016/j.wace.2018.07.003, 2018. a, b, c
Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L.,
Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M.,
and Midgley, P. M. (Eds.): Managing the Risks of Extreme Events and Disasters
to Advance Climate Change Adaptation, Cambridge University Press, Cambridge,
UK, and New York, NY, USA, 2012. a, b, c
Fischer, E. M., Beyerle, U., and Knutti, R.: Robust spatially aggregated
projections of climate extremes, Nat. Clim. Change, 3, 1033–1038,
https://doi.org/10.1038/nclimate2051, 2013. a
Fischer, E. M., Beyerle, U., Schleussner, C. F., King, A. D., and Knutti, R.:
Biased Estimates of Changes in Climate Extremes From Prescribed SST
Simulations, Geophys. Res. Lett., 45, 8500–8509,
https://doi.org/10.1029/2018GL079176, 2018. a
Fouillet, A., Rey, G., Wagner, V., Laaidi, K., Empereur-Bissonnet, P.,
Le Tertre, A., Frayssinet, P., Bessemoulin, P., Laurent, F., De Crouy-Chanel,
P., Jougla, E., and Hémon, D.: Has the impact of heat waves on mortality
changed in France since the European heat wave of summer 2003? A study of
the 2006 heat wave, Int. J. Epidemiology, 37, 309–317,
https://doi.org/10.1093/ije/dym253, 2008. a
Frame, D. J., Wehner, M. F., Noy, I., and Rosier, S. M.: The economic costs of
Hurricane Harvey attributable to climate change, Clim. Change, 160, 271–281,
https://doi.org/10.1007/s10584-020-02692-8, 2020. a
Gudmundsson, L. and Seneviratne, S. I.: Anthropogenic climate change affects
meteorological drought risk in Europe, Environ. Res. Lett., 11, 044005,
https://doi.org/10.1088/1748-9326/11/4/044005, 2016. a
Hagedorn, R., Doblas-Reyes, F. J., and Palmer, T. N.: The rationale behind the
success of multi-model ensembles in seasonal forecasting – I. Basic
concept, Tellus A, 57, 219–233, https://doi.org/10.1111/j.1600-0870.2005.00103.x,
2005. a
Hanel, M., Buishand, T. A., and Ferro, C. A. T.: A nonstationary index flood
model for precipitation extremes in transient regional climate model
simulations, J. Geophys. Res.-Atmos., 114, D15107,
https://doi.org/10.1029/2009JD011712, 2009. a
Hawkins, E., Ortega, P., Suckling, E. B., A., S., Hegerl, G. C., Jones, P. D.,
Joshi, M. M., Osborn, T. J., Masson-Delmotte, V., Mignot, J., Thorne, P. W.,
and van Oldenborgh, G. J.: Estimating changes in global temperature since the
pre-industrial period, B. Am. Meteorol. Soc., 98, 1841–1856,
https://doi.org/10.1175/BAMS-D-16-0007.1, 2017. a
Hermida, A., Fletcher, F., Korell, D., and Logan, D.: SHARE, LIKE, RECOMMEND,
Journalism Studies, 13, 815–824, https://doi.org/10.1080/1461670X.2012.664430, 2012. a
Herring, S. C., Christidis, N., Hoell, A., Kassin, J. P., Schreck III, C. J.,
and Stott, P. A. E.: Explaining Extreme Events of 2016 from a Climate
Perspective, B. Am. Meteorol. Soc., 99, S1–S157, 2018. a
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res.-Atmos., 114, D21101,
https://doi.org/10.1029/2009JD011799, 2009. a, b
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dynam., 35, 841–858,
https://doi.org/10.1007/s00382-009-0698-1, 2010. a, b
Jézéquel, A., Dépoues, V., Guillemot, H., Trolliet, M.,
Vanderlinden, J.-P., and Yiou, P.: Behind the veil of extreme event
attribution, Clim. Change, 149, 367–383, https://doi.org/10.1007/s10584-018-2252-9,
2018. a
Kam, J., Knutson, T. R., and Milly, P. C. D.: Climate Model Assessment of
Changes in Winter–Spring Streamflow Timing over North America, J.
Climate, 31, 5581–5593, https://doi.org/10.1175/JCLI-D-17-0813.1, 2018. a, b
Kam, J., Stowers, K., and Kim, S.: Monitoring of Drought Awareness from Google
Trends: A Case Study of the 2011–17 California Drought, Weather Clim.
Soc., 11, 419–429, https://doi.org/10.1175/WCAS-D-18-0085.1, 2019. a
Katz, R. W., Parlange, M. B., and Naveau, P.: Statistics of extremes in
hydrology, Adv. Water Resour., 25, 1287–1304,
https://doi.org/10.1016/S0309-1708(02)00056-8, 2002. a, b, c
Kendon, E. J., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan, S. C., and
Senior, C. A.: Heavier summer downpours with climate change revealed by
weather forecast resolution model, Nat. Clim. Change, 4, 570–576,
https://doi.org/10.1038/nclimate2258, 2014. a
Kew, S. F., Philip, S. Y., Hauser, M., Hobbins, M., Wanders, N., van Oldenborgh, G. J., van der Wiel, K., Veldkamp, T. I. E., Kimutai, J., Funk, C., and Otto, F. E. L.: Impact of precipitation and increasing temperatures on drought in eastern Africa, Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-20, accepted, 2020. a
Kharin, V. V., Zwiers, F. W., and Zhang, X.: Intercomparison of Near-Surface
Temperature and Precipitation Extremes in AMIP-2 Simulations, Reanalyses, and
Observations, J. Climate, 18, 5201–5223, https://doi.org/10.1175/JCLI3597.1, 2005. a
King, A. D., Alexander, L. V., and Donat, M. G.: The efficacy of using gridded
data to examine extreme rainfall characteristics: a case study for Australia,
Int. J. Climatol., 33, 2376–2387, https://doi.org/10.1002/joc.3588,
2013a. a
King, A. D., Lewis, S. C., Perkins, S. E., Alexander, L. V., Donat, M. G.,
Karoly, D. J., and Black, M. T.: Limited Evidence of Anthropogenic Influence
on the 2011-12 Extreme Rainfall over Southeast Australia, B. Am. Meteorol. Soc., 94, S55–S58, https://doi.org/10.1175/BAMS-D-13-00085.1,
2013b. a
King, A. D., van Oldenborgh, G. J., Karoly, D. J., Lewis, S. C., and Cullen,
H.: Attribution of the record high Central England temperature of 2014 to
anthropogenic influences, Environ. Res. Lett., 10, 054002,
https://doi.org/10.1088/1748-9326/10/5/054002, 2015. a, b
King, A. D., van Oldenborgh, G. J., and Karoly, D. J.: Climate Change and El
Niño increase likelihood of Indonesian heat and drought, B. Am. Meteorol. Soc., 97, S113–S117, https://doi.org/10.1175/BAMS-D-16-0164.1, 2016. a, b
Laloyaux, P., De Boisseson, E., and Dahlgren, P.: CERA-20C: An Earth system
approach to climate reanalysis, ECMWF Newsletter, winter 2017,
available at: https://www.ecmwf.int/en/newsletter/150/meteorology/cera-20c-earth-system-approach-climate-reanalysis (last access: 19 December 2019),
2017. a
Lenderink, G. and van Meijgaard, E.: Increase in hourly precipitation extremes
beyond expectations from temperature changes, Nat. Geosci., 1, 511–514,
https://doi.org/10.1038/ngeo262, 2008. a
Lewandowsky, S., Oreskes, N., Risbey, J. S., Newell, B. R., and Smithson, M.:
Seepage: Climate change denial and its effect on the scientific community,
Global Environ. Change, 33, 1–13,
https://doi.org/10.1016/j.gloenvcha.2015.02.013, 2015. a
Lloyd, E. A. and Oreskes, N.: Climate Change Attribution: When Is It
Appropriate to Accept New Methods?, Earth's Future, 6, 311–325,
https://doi.org/10.1002/2017EF000665, 2018. a
Lott, F. C. and Stott, P. A.: Evaluating Simulated Fraction of Attributable
Risk Using Climate Observations, J. Climate, 29, 4565–4575,
https://doi.org/10.1175/JCLI-D-15-0566.1, 2016. a
Luu, L. N., Vautard, R., P., Y., van Oldenborgh, G. J., and Lenderink, G.:
Attribution of Extreme Rainfall Events in the South of France Using
EURO-CORDEX Simulations, Geophys. Res. Lett., 45, 6242–625,
https://doi.org/10.1029/2018GL077807, 2018. a, b, c, d
Manley, G.: Central England temperatures: Monthly means 1659 to 1973, Q.
J. Roy. Meteor. Soc., 100, 389–405,
https://doi.org/10.1002/qj.49710042511,
1974. a, b
Meredith, E. P., Semenov, V. A., Maraun, D., Park, W., and Chernokulsky, A. V.:
Crucial role of Black Sea warming in amplifying the 2012 Krymsk precipitation
extreme, Nat. Geosci., 8, 615 EP,
https://doi.org/10.1038/ngeo2483, 2015. a
Mitchell, D., Heaviside, C., Vardoulakis, S., Huntingford, C., Masato, G.,
Guillod, B. P., Frumhoff, P., Bowery, A., Wallom, A., and Allen, M. R.:
Attributing human mortality during extreme heat waves to anthropogenic
climate change, Environ. Res. Lett., 11, 074006,
https://doi.org/10.1088/1748-9326/11/7/074006, 2016. a, b, c
Murakami, H., Vecchi, G. A., Underwood, S., Delworth, T. L., Wittenberg, A. T.,
Anderson, W. G., Chen, J.-H., Gudgel, R. G., Harris, L. W., Lin, S.-J., and
Zeng, F.: Simulation and Prediction of Category 4 and 5 Hurricanes in the
High-Resolution GFDL HiFLOR Coupled Climate Model, J. Climate, 28,
9058–9079, https://doi.org/10.1175/JCLI-D-15-0216.1, 2015. a, b
National Academies of Sciences, Engineering, and Medicine: Attribution of
Extreme Weather Events in the Context of Climate Change, The National
Academies Press, https://doi.org/10.17226/21852, 2016. a
Omrani, H., van Oldenborgh, G. J., Lenderink, G., and Vautard, R.: New insights
on conditional attribution of extreme weather event, Clim. Dynam., under
review, 2020. a
Otto, F. E.: Attribution of Weather and Climate Events, Annu. Rev.
Env. Resour., 42, 627–646,
https://doi.org/10.1146/annurev-environ-102016-060847, 2017. a
Otto, F. E. L., Massey, N., van Oldenborgh, G. J., Jones, R. G., and Allen,
M. R.: Reconciling two approaches to attribution of the 2010 Russian heat
wave, Geophys. Res. Lett., 39, L04702, https://doi.org/10.1029/2011GL050422, 2012. a, b
Otto, F. E. L., Coelho, C. A. S., King, A., Coughlan de Perez, E., Wada, Y.,
van Oldenborgh, G. J., Haarsma, R., Haustein, K., Uhe, P., van Aalst, M.,
Aravequia, J. A., Almeida, W., and Cullen, H.: Factors other than climate
change, main drivers of 2014/15 water shortage in southeast Brazil, B. Am. Meteorol. Soc., 96, S35–S40, https://doi.org/10.1175/BAMS-D-15-00120.1, 2015. a, b, c
Otto, F. E. L., van Oldenborgh, G. J., Eden, J. M., Stott, P. A., Karoly,
D. J., and Allen, M. R.: The attribution question, Nat. Clim. Change, 6,
813–816, https://doi.org/10.1038/nclimate3089, 2016. a
Otto, F. E. L., an der Wiel, K., van Oldenborgh, G. J., Philip, S. Y., Kew,
S. F., Uhe, P., and Cullen, H.: Climate change increases the probability of
heavy rains in Northern England/Southern Scotland like those of storm
Desmond – a real-time event attribution revisited, Environ. Res. Lett.,
13, 024006, https://doi.org/10.1088/1748-9326/aa9663, 2018a. a, b, c, d, e, f
Otto, F. E. L., Philip, S. Y., Kew, S. F., Li, S., King, A. D., and Cullen, H.:
Attributing high-impact extreme events across timescales – a case study of
four different types of events, Clim. Change, 149, 399–412,
https://doi.org/10.1007/s10584-018-2258-3, 2018b. a, b, c
Otto, F. E. L., Wolski, P., Lehner, F., Tebaldi, C., van Oldenborgh, G. J.,
Hogesteeger, S., Singh, R., Holden, P., Fuckar, N. S., Odoulami, R., and New,
M.: Anthropogenic influence on the drivers of the Western Cape drought
2015–2017, Environ. Res. Lett., 13, 124010,
https://doi.org/10.1088/1748-9326/aae9f9, 2018c. a, b
Parker, D. E., Legg, T. P., and Folland, C. K.: A new daily central England
temperature series, 1772–1991, Int. J. Climatol., 12,
317–342, https://doi.org/10.1002/joc.3370120402,
1992. a
Philip, S., Sparrow, S., Kew, S. F., van der Wiel, K., Wanders, N., Singh, R., Hassan, A., Mohammed, K., Javid, H., Haustein, K., Otto, F. E. L., Hirpa, F., Rimi, R. H., Islam, A. K. M. S., Wallom, D. C. H., and van Oldenborgh, G. J.: Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives, Hydrol. Earth Syst. Sci., 23, 1409–1429, https://doi.org/10.5194/hess-23-1409-2019, 2019. a, b, c, d, e
Philip, S. Y., Kew, S. F., Hauser, M., Guillod, B. P., Teuling, A. J., Whan,
K., Uhe, P., and v. Oldenborgh, G. J.: Western US high June 2015
temperatures and their relation to global warming and soil moisture, Clim.
Dynam., 50, 2587–2601, https://doi.org/10.1007/s00382-017-3759-x, 2018a. a
Philip, S. Y., Kew, S. F., van Oldenborgh, G. J., Aalbers, E., Otto, F. E. L.,
Haustein, K., Habets, F., and Singh, R.: Validation of a rapid attribution of
the May/June 2016 flood-inducing precipitation in France to climate
change, J. Hydrometeorol., 19, 1881–1898,
https://doi.org/10.1175/JHM-D-18-0074.1, 2018b. a, b, c, d, e
Philip, S. Y., Kew, S. F., van Oldenborgh, G. J., Otto, F. E. L., O'Keefe, S.,
Haustein, K., King, A. D., Zegeye, A., Eshetu, Z., Hailemariam, K., Singh,
R. K., Jjemba, E., Funk, C., and Cullen, H.: Attribution analysis of the
Ethiopian drought of 2015, J. Climate, 31, 2465–2486,
https://doi.org/10.1175/JCLI-D-17-0274.1, 2018c. a, b, c, d, e, f, g
Puma, M. J. and Cook, B. I.: Effects of irrigation on global climate during the
20th century, J. Geophys. Res.-Atmos., 115, D16120,
https://doi.org/10.1029/2010JD014122, d16120, 2010. a
Risser, M. D. and Wehner, M. F.: Attributable Human-Induced Changes in the
Likelihood and Magnitude of the Observed Extreme Precipitation during
Hurricane Harvey, Geophys. Res. Lett., 44, 12457–12464,
https://doi.org/10.1002/2017GL075888, 2017. a
Schaller, N., Kay, A. L., Lamb, R., Massey, N. R., van Oldenborgh, G. J., Otto,
F. E. L., Sparrow, S. N., Vautard, R., Yiou, P., Bowery, A., Crooks, S. M.,
Huntingford, C., Ingram, W. J., Jones, R. G., Legg, T., Miller, J., Skeggs,
J., Wallom, D., Weisheimer, A., Wilson, S., and Allen, M. R.: The human
influence on climate in the winter 2013/2014 floods in southern England,
Nat. Clim. Change, 6, 627–634, https://doi.org/10.1038/nclimate2927, 2016. a, b, c, d
Shearer, E. and Grieco, E.: Americans Are Wary of the Role Social Media Sites
Play in Delivering the News, Tech. rep., The Pew Charitable Trusts,
available at: https://www.journalism.org/2019/10/02/americans-are-wary-of-the-role-social-media-sites-play-in-delivering-the-news/ (last access: 11 May 2020),
2019. a
Shepherd, T. G.: A Common Framework for Approaches to Extreme Event
Attribution, Current Climate Change Reports, 2, 28–38,
https://doi.org/10.1007/s40641-016-0033-y, 2016. a, b
Sillmann, J., Kharin, V. V., Zhang, X., Zwiers, F. W., and Bronaugh, D.:
Climate extremes indices in the CMIP5 multimodel ensemble: Part 1.
Model evaluation in the present climate, J. Geophys. Res.-Atmos., 118,
1716–1733, https://doi.org/10.1002/jgrd.50203, 2013. a
Sippel, S., Otto, F. E. L., Flach, M., and van Oldenborgh, G. J.: The Role of
Anthropogenic Warming in 2015 Central European Heat Waves, B. Am. Meteorol. Soc., 97, S51–S56, https://doi.org/10.1175/BAMS-D-16-0150.1, 2016. a, b
Siswanto, van Oldenborgh, G. J., van der Schrier, G., Lenderink, G., and
van den Hurk, B. J. J. M.: Trends in high-daily precipitation events in
Jakarta and the flooding of January 2014, B. Am. Meteorol. Soc., 96,
S131–S135, https://doi.org/10.1175/BAMS-D-15-00128.1, 2015. a
Stott, P. A., Christidis, N., Otto, F. E. L., Sun, Y., Vanderlinden, J.-P., van
Oldenborgh, G. J., Vautard, R., von Storch, H., Walton, P., Yiou, P., and
Zwiers, F. W.: Attribution of extreme weather and climate-related events,
WIREs Clim. Change, 7, 23–41, https://doi.org/10.1002/wcc.380, 2016. a
Sun, L., Allured, D., Hoerling, M., Smith, L., Perlwitz, J., Murray, D., and
Eischeid, J.: Drivers of 2016 record Arctic warmth assessed using climate
simulations subjected to Factual and Counterfactual forcing, Weather and
Climate Extremes, 19, 1–9, https://doi.org/10.1016/j.wace.2017.11.001, 2018. a
Tebaldi, C. and Arblaster, J. M.: Pattern scaling: Its strengths and
limitations, and an update on the latest model simulations, Clim. Change,
122, 459–471, https://doi.org/10.1007/s10584-013-1032-9, 2014. a
Tobin, I., Greuell, W., Jerez, S., Ludwig, F., Vautard, R., van Vliet, M.
T. H., and Bréon, F.-M.: Vulnerabilities and resilience of European
power generation to 1.5 ∘C, 2 ∘C and 3 ∘C
warming, Environ. Res. Lett., 13, 044024,
https://doi.org/10.1088/1748-9326/aab211, 2018. a
Uhe, P., Otto, F. E. L., Haustein, K., van Oldenborgh, G. J., King, A., Wallom,
D., Allen, M. R., and Cullen, H.: Comparison of Methods: Attributing the 2014
record European temperatures to human influences, Geophys. Res. Lett., 43, 8685–8693,
https://doi.org/10.1002/2016GL069568, 2016. a, b, c
Uhe, P., Philip, S. Y., Kew, S. F., Shah, K., Kimutai, J., Mwangi, E., van
Oldenborgh, G. J., Singh, R. K., Arrighi, J., Jjemba, E., Cullen, H., and
Otto, F. E. L.: Attributing drivers of the 2016 Kenyan drought, Int. J. Climatol., 38, e554–e568, https://doi.org/10.1002/joc.5389, 2018. a, b, c, d
van den Brink, H. W. and Können, G. P.: Estimating 10000-year return
values from short time series, Int. J. Climatol., 31, 115–126,
https://doi.org/10.1002/joc.2047, 2011. a
van der Bles, A., van der Linden, S., Freeman, A., and Spiegelhalter, D.: The
effects of communicating uncertainty about facts and numbers, in:
Evidence-Based Medicine, 23 (Suppl 1), pp. A9–A10, BMJ,
available at: https://ebm.bmj.com/content/23/Suppl_1/A9.2 (last access: 19 December 2019), 2018. a
van der Wiel, K., Kapnick, S. B., van Oldenborgh, G. J., Whan, K., Philip, S., Vecchi, G. A., Singh, R. K., Arrighi, J., and Cullen, H.: Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change, Hydrol. Earth Syst. Sci., 21, 897–921, https://doi.org/10.5194/hess-21-897-2017, 2017. a, b, c, d, e, f, g, h, i, j
van der Wiel, K., Selten, F. M., Bintanja, R., Blackport, R., and Screen,
J. A.: Ensemble climate-impact modelling: extreme impacts from moderate
meteorological conditions, Environ. Res. Lett., 15, 034050,
https://doi.org/10.1088/1748-9326/ab7668, 2020. a
van Engelen, A. and Nellestijn, J. W.: Monthly, seasonal and annual means of
air temperature in tenths of centigrades in De Bilt, Netherlands,
1706–1995, Tech. rep., KNMI report from the Climatological Services Branch, De Bilt, 1996. a
van Oldenborgh, G. J., Drijfhout, S., van Ulden, A., Haarsma, R., Sterl, A., Severijns, C., Hazeleger, W., and Dijkstra, H.: Western Europe is warming much faster than expected, Clim. Past, 5, 1–12, https://doi.org/10.5194/cp-5-1-2009, 2009. a
van Oldenborgh, G. J., Doblas-Reyes, F. J., Wouters, B., and Hazeleger, W.:
Decadal prediction skill in a multi-model ensemble, Clim. Dynam., 38,
1263–1280, https://doi.org/10.1007/s00382-012-1313-4, 2012a. a
van Oldenborgh, G. J., van Urk, A., and Allen, M. R.: The absence of a role of
climate change in the 2011 Thailand floods, B. Am. Meteorol. Soc., 9,
1047–1049, https://doi.org/10.1175/BAMS-D-12-00021.1, 2012b. a
van Oldenborgh, G. J., Doblas Reyes, F. J., Drijfhout, S. S., and Hawkins, E.:
Reliability of regional climate model trends, Environ. Res. Lett., 8,
014055, https://doi.org/10.1088/1748-9326/8/1/014055, 2013. a
van Oldenborgh, G. J., Haarsma, R., De Vries, H., and Allen, M. R.: Cold
Extremes in North America vs. Mild Weather in Europe: The Winter of
2013–14 in the Context of a Warming World, B. Am.
Meteorol. Soc., 96, 707–714, https://doi.org/10.1175/BAMS-D-14-00036.1, 2015. a, b
van Oldenborgh, G. J., Macias-Fauria, M., King, A., Uhe, P., Philip, S. Y., Kew, S. F., Karoly, D., Otto, F. E. L., Allen, M., and Cullen, H.: Unusually high temperatures at the North Pole, winter
2016, Tech. rep., World Weather Attribution,
available at: https://www.worldweatherattribution.org/north-pole-nov-dec-2016/ (last access: 31 October 2018),
2016a. a, b, c
van Oldenborgh, G. J., Otto, F. E. L., Haustein, K., and Achuta Rao, K.: The
heavy precipitation event of December 2015 in Chennai, India, B. Am. Meteorol. Soc., 97, S87–S91, https://doi.org/10.1175/BAMS-D-16-0129.1,
2016b. a, b
van Oldenborgh, G. J., van der Wiel, K., Sebastian, A., Singh, R. K., Arrighi,
J., Otto, F. E. L., Haustein, K., Li, S., Vecchi, G. A., and Cullen, H.:
Attribution of extreme rainfall from Hurricane Harvey, August 2017,
Environ. Res. Lett., 12, 124009, https://doi.org/10.1088/1748-9326/aa9ef2, 2017. a, b, c, d, e, f
Vautard, R., Cattiaux, J., Yiou, P., Thepaut, J.-N., and Ciais, P.: Northern
Hemisphere atmospheric stilling partly attributed to an increase in surface
roughness, Nat. Geosci., 3, 756–761, https://doi.org/10.1038/ngeo979, 2010. a
Vautard, R., van Oldenborgh, G. J., Thao, S., Dubuisson, B., Lenderink, G.,
Ribes, A., Soubeyroux, J. M., Yiou, P., and Planton, S.: Extreme fall 2014
precipitations in the Cévennes mountain range, B. Am. Meteorol. Soc.,
96, S56–S60, https://doi.org/10.1175/BAMS-D-15-00088.1, 2015. a, b, c
Vautard, R., Yiou, P., Otto, F. E. L., Stott, P. A., Christidis, N., van
Oldenborgh, G. J., and Schaller, N.: Attribution of human-induced dynamical
and thermodynamical contributions in extreme weather events, Environ. Res. Lett., 11, 114009, https://doi.org/10.1088/1748-9326/11/11/114009, 2016. a
Vautard, R., Christidis, N., Ciavarella, A., Alvarex-Castro, C., Bellprat, O.,
Christensen, O. B., Colfescu, I., Cowan, T., Doblas Reyes, F. J., Eden,
J. M., Hauser, M., Hegerl, G. C., Hempelmann, N., Klehmet, K., Lott, F. C.,
Nangini, C., Orth, R., Radanovics, S., Seneviratne, S. I., van Oldenborgh,
G. J., Stott, P. A., Tett, S., Wilcox, L., and Yiou, P.: Evaluation of the
HadGEM3-A simulations in view of climate and weather event human influence
attribution in Europe, Clim. Dynam., 52, 1187–1210,
https://doi.org/10.1007/s00382-018-4183-6, 2018. a
Vautard, R., van Oldenborgh, G. J., Otto, F. E. L., Yiou, P., de Vries, H., van Meijgaard, E., Stepek, A., Soubeyroux, J.-M., Philip, S., Kew, S. F., Costella, C., Singh, R., and Tebaldi, C.: Human influence on European winter wind storms such as those of January 2018, Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, 2019.
a, b, c, d, e, f
Wild, M.: Global dimming and brightening: a review, J. Geophys. Res., 114,
D00D16, https://doi.org/10.1029/2008JD011470, 2009. a
Ye, Y., Xu, P., and Zhang, M.: Social media, public discourse and civic
engagement in modern China, Telemat. Inform., 34, 705–714,
https://doi.org/10.1016/j.tele.2016.05.021, 2017. a
Yokohata, T., Annan, J., Collins, M., Jackson, C., Tobis, M., Webb, M., and
Hargreaves, J.: Reliability of multi-model and structurally different
single-model ensembles, Clim. Dynam., 39, 599–616,
https://doi.org/10.1007/s00382-011-1203-1, 2012. a
Short summary
Event attribution studies can now be performed at short notice. We document a protocol developed by the World Weather Attribution group. It includes choices of which events to analyse, the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis, and communication procedures. The protocol will be useful for future event attribution studies and as a basis for an operational attribution service.
Event attribution studies can now be performed at short notice. We document a protocol developed...
