Characterization and attribution in climate studies

With the urgency of halving emissions by 2030, as per the IPCC's recommendation, it is worrying to say the least that corporate responsibility for carbon emissions in 2025 is still marked by a gap between ambitious pledges and actual progress, driven by weak commitments, greenwashing, and inconsistent reporting instead of action. But is that all about to change? A landmark climate case in Germany, in which a Peruvian farmer is suing energy giant RWE for its share of contribution to increased flood risk at his property, is set to be decided later this month. So can climate science attribute economic damage to major polluters? Well possibly yes, thanks to advancements in Attribution Science (altho there are limitations!): The methodology: researchers Justin Mankin (Dartmouth College) and Christopher Callahan (Stanford University) have developed a technique that simulates global average temperatures from 1991 to 2020, with and without emissions from specific fossil fuel companies. They account for both extraction and end-use emissions (e.g., burning fuels by consumers). By mapping global temperature changes to local warming patterns, they focus on the five hottest days annually, which correlate with economic losses from reduced crop yields, increased mortality, and lower labour productivity. Their findings: their analysis attributes $12–49 trillion in global GDP losses over three decades to emissions from major fossil fuel companies, with the top five (Saudi Aramco, Gazprom, Chevron, ExxonMobil, BP) each linked to over $1 trillion in losses. For example, Chevron’s emissions are estimated to have caused $4–61 billion in US GDP losses during a 2012 heatwave. The validation: Experts like Kevin Reed (Stony Brook University) and Friederike Otto (Imperial College London) praise the study as a robust “end-to-end attribution” approach, marking it as a pioneering effort to connect specific emitters to specific damages. Otto suggests that broader adoption by other research groups could refine and strengthen the science. The paper: https://lnkd.in/ezV53Hxa

Researchers have simulated what Valencia's flood would have looked like without climate change. Valencia saw extreme rainfall in October 2024. To identify the contribution of anthropogenic climate change, they applied conditional attribution - a method that replays the exact storm under pre-industrial climate conditions - to isolate climate change's contribution. Using 15 climate models to perturb temperature and moisture fields, then re-running the event at 1-km resolution, the authors compare what happened against what would have happened without human emissions. This approach reveals storm mechanics invisible to statistical methods. Warmer Mediterranean seas loaded the atmosphere with excess moisture, driving stronger convective instability, more vigorous updrafts, and denser ice formation - pushing rainfall intensity well beyond what thermodynamics alone would predict. The next step is connecting these physical insights to adaptation planning for Mediterranean cities. By Carlos Calvo-Sancho, Javier Díaz Fernández, Juan Jesús González Alemán, Amar Halifa-Marín, Mario Marcello Miglietta, and more.

🚨 New publication - guidance for attributing health impacts to climate change This week in Climatic Change, we have published new guidance for conducting studies that attribute health impacts to climate change, led by Kris Ebi, Andy Haines and myself. Supported by the Wellcome Trust, we brought together an eminent group of co-authors primarily from climate and health sciences. The guidelines aim to be method agnostic and recommend that climate change health attribution studies take the following steps: - Work jointly across disciplines to define the research question/intent - Establish a transdisciplinary analytic team - Meaningfully engage communities of practice, partners from affected communities, and representative decision makers - Identify, illustrate, and describe causal linkages in an evidence-based causal pathway linking exposure to weather/climate variables to the health outcome(s) of interest - Define the exposure event (or trend), evaluate the climate model(s) skill, and quantify attributable changes in health-relevant meteorological variables - Quantify attributable short- and long-term health impacts within the context of other determinants of exposure and vulnerability - Report the results, including a description of how the above recommendations were incorporated into the analytical plan We hope that it will prove useful to study authors, reviewers, journal editors and research funders. Much more in the article itself: https://lnkd.in/eiDXuQ53 Christofer Åström Ana M. Vicedo Cabrera Nicholas Brink Colin J. Carlson Shouro Dasgupta, PhD Lucy Temple Felipe J Colón-González Antonio Gasparrini Georgiana Gordon-Strachan Sherilee Harper Luke Harrington Jeremy Hess Elizabeth Kimani-Murage Sari Kovats Rachel Lowe Dann Mitchell Mark New Sarah Perkins-Kirkpatrick Julia Pescarini Nicole Redvers Sadie Ryan Ben Santer Carl-Friedrich Schleussner Jan Semenza Sokhna Thiam Wim Thiery Adrian Tompkins Sabine Undorf Kai Wan Rachel Warren Alistair Woodward Caradee Wright Cyril Caminade Paul Chua Guéladio Cissé Miguel Garrido Zornoza Jimmy Hilly Dr. Vijendra Ingole, PhD Ludmilla Viana Jacobson

📢 𝗧𝘄𝗼-𝘁𝗵𝗶𝗿𝗱𝘀 𝗼𝗳 𝗴𝗹𝗼𝗯𝗮𝗹 𝘄𝗮𝗿𝗺𝗶𝗻𝗴 𝗰𝗮𝘂𝘀𝗲𝗱 𝗯𝘆 𝘄𝗼𝗿𝗹𝗱’𝘀 𝗿𝗶𝗰𝗵𝗲𝘀𝘁 𝟭𝟬% Check out our new attribution study in Nature Climate Change led by Sarah Schöngart and co-authored by Zebedee Nicholls, Setu Pelz, Carl-Friedrich Schleussner, and myself. https://lnkd.in/d2Scxtgy 🔎 We link data on emissions #inequality over the period 1990–2020 to regional warming and resulting climate extremes using an emulator-based framework. We find that: ▪️ 𝗧𝘄𝗼-𝘁𝗵𝗶𝗿𝗱𝘀 (𝗼𝗻𝗲-𝗳𝗶𝗳𝘁𝗵) 𝗼𝗳 𝘄𝗮𝗿𝗺𝗶𝗻𝗴 𝗶𝘀 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗮𝗯𝗹𝗲 𝘁𝗼 𝘁𝗵𝗲 𝘄𝗲𝗮𝗹𝘁𝗵𝗶𝗲𝘀𝘁 𝟭𝟬% (𝟭%) of the global population, meaning that their individual contributions are 6.5 (20) times the average per capita contribution to global warming. ▪️For extreme events, the 𝘁𝗼𝗽 𝟭𝟬% (𝟭%) 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝟳 (𝟮𝟲) 𝘁𝗶𝗺𝗲𝘀 𝘁𝗵𝗲 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝘁𝗼 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝘀 𝗶𝗻 𝗺𝗼𝗻𝘁𝗵𝗹𝘆 𝟭-𝗶𝗻-𝟭𝟬𝟬-𝘆𝗲𝗮𝗿 𝗵𝗲𝗮𝘁 𝗲𝘅𝘁𝗿𝗲𝗺𝗲𝘀 𝗴𝗹𝗼𝗯𝗮𝗹𝗹𝘆 and 6 (17) times more to Amazon droughts. ▪️Our granular impact analysis shows that 𝗹𝗼𝘄-𝗶𝗻𝗰𝗼𝗺𝗲 𝗿𝗲𝗴𝗶𝗼𝗻𝘀 𝗶𝗻𝗰𝘂𝗿 𝘁𝗵𝗲 𝗯𝗿𝘂𝗻𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗵𝗮𝗿𝗺 𝗰𝗮𝘂𝘀𝗲𝗱 𝗯𝘆 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 concentrated among wealthier populations worldwide. While emissions inequality has long been recognized, our study is the first to 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝘆 𝗵𝗼𝘄 𝘁𝗵𝗶𝘀 𝗶𝗻𝗲𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗲𝘀 𝗶𝗻𝘁𝗼 𝗱𝗶𝘀𝗽𝗿𝗼𝗽𝗼𝗿𝘁𝗶𝗼𝗻𝗮𝘁𝗲 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 for global temperature rise and extreme climate events. The findings have significant implications for climate justice, underscoring the stark disparities in responsibility for climate impacts. They provide a strong evidence base for 𝗰𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗼𝗿𝘆 𝗽𝗼𝗹𝗶𝗰𝘆 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗿𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗲𝗳𝗳𝗼𝗿𝘁𝘀 targeting the world’s highest emitters. Nature Magazine, ETH Zürich, International Institute for Applied Systems Analysis (IIASA)

I’m really happy to share our recently published paper on detection and attribution of climate change impacts in natural-human systems across the Andes in South America, in Nature Communications Earth & Environment: https://lnkd.in/eJPrNYT8   Our study attributes observed changes in climatic variables, cryosphere, water, hazards, ecosystems, food security, human health, migration, tourism and culture to anthropogenic climate change – to different extents, accounting for multiple drivers of change. It thus provides evidence of observed (mainly negative) substantial impacts of anthropogenic climate change across a ca 8000 km long North-South transect of the Andes region. Particularly noteworthy, and unique for the Andes, is the assessment of cascading impacts from climate to cryosphere to ecosystems and eventually affecting human systems, and their attribution to anthropogenic climate change. My favorite is Figure 4 – have a look at it! We also included local and indigenous knowledge in the analysis. The study contributes to improved evidence of climate change impacts in the region which is essential to take urgently needed action on climate change adaptation and mitigation.   The paper is led by Ana Ochoa Sánchez and a product of the Mentoring and Training Programme in IPCC processes for Early Career Mountain Researchers, supported by the University of Zurich, Mountain Research Initiative (MRI), Helvetas, and ICIMOD, funded by the Swiss Agency for Development and Cooperation (SDC), where we trained a number of great early career researchers from developing countries during the past 6th Assessment Cycle of the IPCC. This was a great experience, and our colleagues are now ready to make a great contribution to the 7th Assessment Cycle of IPCC, by assessing the state of science and building highly needed bridges between science and policy. Ana Elizabeth Ochoa Sánchez, Dáithí Stone, Fabian Drenkhan, Daniel Mendoza, Ronald Gualán Geographisches Institut UZH, University of Zurich, NIWA, Universidad del Azuay

The World Weather Attribution (link below) report examines the extraordinary March 2025 heatwave in Central Asia, highlighting its causes, impacts, and the role of #climatechange in intensifying extreme temperatures. This is combined with lowest levels of artic sea ice seen in March as the polar regions continue to be impacted more severely than other other regions by changes in our climate. Key Findings Economic & Agricultural Impact: Agriculture contributes up to 24% of GDP in affected countries, with 50% of the workforce reliant on it. Over 230 million labour hours were lost in Uzbekistan in 2023 due to extreme heat. The heat coincided with the flowering of key export fruit crops and spring wheat sowing in Kazakhstan, potentially impacting yields. Water Supply Vulnerabilities: Central Asia relies heavily on glacier-fed irrigation systems. The altered timing of snowmelt reduces water availability during peak growing seasons, further stressing agricultural output. Unprecedented Temperatures: While March temperatures can be variable, this year's record-breaking heat had never been observed before in many areas. The climate has warmed by 1.3°C globally, making extreme March temperatures now likely once every three years—whereas in a cooler climate, they would have been up to 10°C lower. Climate Change Influence: Human-induced climate change made this extreme heat about 4°C hotter and three times more likely. However, climate models underestimate the increase in heat observed. Future Projections: At a 2.6°C global warming level, such heatwaves will double in likelihood and intensify by another 2°C. Adaptation Measures: Strategies such as adjusting planting calendars, using heat-tolerant crops, and improving irrigation systems are in place but vary by country. Kazakhstan and Tajikistan have integrated adaptation policies into national frameworks, while Kyrgyzstan and Tajikistan have developed Early Action Protocols for heat. Comprehensive Heat Adaptation Needed: Experts stress the need for self-protective behaviour, heat education, urban planning with nature-based solutions, Heat Action Plans, and strengthening healthcare systems to tackle rising temperatures. Central Asia is increasingly vulnerable to early-season extreme heat due to human-induced climate change, glacier retreat, and desertification. The region must continue to urgently scale up adaptation efforts, ensuring protection for agriculture, water supply, and urban infrastructure to mitigate future heatwave impacts.

What do wildfire burn scars, extreme heat, and air pollution have in common? They’re all part of a fast-changing climate story. And a new book I contributed to "The Conversation on Extreme Weather" helped me see the connections more clearly. Four themes especially stood out: Climate change attribution Chapter 1, Is climate change to blame for extreme weather events?, explains how scientists can now determine how much more likely climate change has made certain extremes. Xubin Zeng breaks down how attribution works and where it’s most effective. Cascading events Chapter 5, The risk of ‘cascading’ natural disasters is on the rise, and Chapter 8, Atmospheric rivers over California’s wildfire burn scars raise fears of deadly mudslides, show how one disaster can trigger others. Farshid Vahedifard and Amir AghaKouchak explain how compound risks are increasing and why our planning needs to account for chains of events. Double-whammies Chapter 18, Extreme heat and air pollution can be deadly, shows how these risks interact. Erika Garcia, Md Mostafijur Rahman, and Rob McConnell explain that when heat waves coincide with pollution spikes, the health impacts are much more severe. In my own Chapter 4, The fastest population growth in the West’s wildland-urban interface is in areas most vulnerable to wildfires, I found that new development is expanding fastest in regions with the most drought-sensitive vegetation. These landscapes dry out more quickly and burn more severely under the same climate conditions. Growth and hazard are rising together. Climate havens are a misnomer Chapter 37, Looking for a US ‘climate haven’ away from disaster risks?, challenges the idea that some regions will escape the worst impacts. Julie Arbit, Brad Bottoms, and Earl Lewis show that even cities often cited as refuges like Buffalo, Duluth, or Madison face increasing risks from extreme heat, intense rain, snowmelt flooding, and aging infrastructure. No state is immune, and even the “safe” places are seeing disasters more often. It’s a powerful read for anyone trying to understand what we’re up against. The book should be available in your local library or amazon: https://lnkd.in/g5AW2JHW

📣 How do exposure to extreme weather events and the subjective attribution of these events to climate change relate to climate policy support across the world? 🔥🌎  👉 Find out more in our open-access article published in Nature Climate Change: https://lnkd.in/dyreWD3V 🔧 𝗪𝗵𝗮𝘁 𝗱𝗶𝗱 𝘄𝗲 𝗱𝗼?  With an interdisciplinary author team, we developed a measure of exposed population to several different types of extreme weather event (e.g., heatwaves, wildfires, floods) over the last decades across 68 countries. We then triangulated this data with survey responses collected with the TISP Many Labs study. Specifically, we asked participants to what extent they believed that climate change had impacted several types of extreme weather event over the last decades in their country. We also asked participants to what extent they supported several climate policies. Linking these datasets allowed us to study whether population-level exposure to events and subjective attribution of these events to climate change relate to climate policy support. 💡 𝗪𝗵𝗮𝘁 𝗱𝗶𝗱 𝘄𝗲 𝗳𝗶𝗻𝗱? 1️⃣ Subjective attribution of extreme weather events to climate change was well above the scale midpoint in all countries. 2️⃣ A majority of the public supports climate policies, though support varies across policies and countries. 3️⃣ We find global evidence that subjective attribution predicts climate policy support. 4️⃣ We find that population-level exposure to most events is unrelated to climate policy support. Interestingly, and in line with previous studies, only population-level exposure to wildfires was positively related to climate policy support. ✊ 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 🗣️ Making the link between climate change and extreme weather events more salient could increase climate policy support (though experimental studies are needed). The occurrence of extreme weather events (such as the current heatwaves in many countries), provides a window of opportunity for climate change communicators to increase subjective attribution. ☝️ 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗳𝘂𝘁𝘂𝗿𝗲 𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻𝘀  Importantly, our data does not allow us to make conclusions about individual-level exposure. In other words, we do not know whether respondents in our sample were directly affected by these events. We can only draw conclusions about population-level exposure. (Note: a recent global study looking at individual-level exposure found a positive relationship with climate risk perception across event types https://lnkd.in/dWxJ4wDs). The literature on the relationship between extreme weather events and climate change beliefs, attitudes, and behaviors is still mixed. We hope that this study will spark more research in this area. Big thanks to my amazing co-authors, it's been such a pleasure to work with this interdisciplinary team Simona Meiler Chahan Kropf Samuel Lüthi Niels G. Mede David N. Bresch Oscar Lecuona and many others! 🙏

Did anyone have doubts about the role of climate change in the megarainfall event that occurred 10 days ago in Central Europe? Our World Weather Attribution study shows that the probability of such rainfall level, over 4 consecutive days, has about doubled due to global warming. It is, again, a record shattering event. 👉 https://lnkd.in/e8N2shC3 🌨 What happened in the weather? A cold polair air invades Western Europe, hits the Alps, deviates southward and rotates, triggering a lee-side cyclogenesis over Northern Italy. A classical situation. The air then travels over the hot Mediterranean Sea and the Black Sea (see the SST anomaly of a few degrees over both Seas), collecting a lot of humidity from there, and then returns to Central Europe in the rotating system, unleashing heavy rainfalls. The weather system was very slowly moving, allowing persistence of rain. 🌡 How did global warming worsen things? Likely by inducing so high temperatures and anomalies over the Mediterranean and Black Seas areas, allowing more humidity in the air (7% more per °C, that is thermodynamics!). But maybe not only, we will see in further studies. 🌫 Such megarainfalls and floods are not isolated those days: remember East Africa megarainfalls in late 2023, which left many homeless, for instance, but there are many more examples. This event which will induce billions of losses and damages, will become more and more frequent, until greenhouse gases emissions are stopped, in particular those from burning fossil fuels which accumulate in the atmosphere and increase warming. The WWA study was led by Dr. Joyce Kimutai, thanks Joyce! And thanks Christophe Cassou 🐿 for the great weather analysis! Schematic drawing of the air flow superimposed with the SST anomaly as shown from the Copernicus C3S Pulse tool. 👉 https://lnkd.in/e47kFAMG Maja Vahlberg Clair Barnes Izidine Pinto