Real data in climate cost modeling

The US has already lost 12% of its current income due to climate change. Most studies project future losses, but new research from the University of Arizona has calculated the costs to date. "If we can't figure out what climate change is already costing us with the data we have, projecting the future becomes almost hopeless," said Prof Derek Lemoine, lead author of the study. The study does not look at extreme short term weather events such as hurricanes, wildfires and floods, which have a smaller impact than temperature change in general. When he accounted for climate change's year-after-year persistence and nationwide reach as well as connections between regional economies, the income loss jumped to about 12%—comparable to a major national policy shift. "A lot of the real cost comes from how temperature changes across the whole country ripple through prices and trade," he added. "It's not just about the weather where we live. When every region is affected at the same time, the economic consequences add up quickly.” To measure climate change as an ongoing economic force, Lemoine worked with climate models simulating the world with and without human emissions to figure out how different each county's weather would have been if there was no climate change. He then combined county-level data on daily temperature with county-level personal income per capita from the Bureau of Economic Analysis covering 1969-2019. By doing this, he was able to measure how income historically changed with the number of hotter and colder days both locally and around the country, giving him a more detailed picture of the economic effects of shifting temperature patterns. "The reason the effects get so much larger is that climate change operates through the whole economy," Lemoine said. "Places are linked through trade, so temperatures in California or Iowa can influence income in Arizona. Those cross-state connections turn local weather changes into nationwide economic impacts.” With this as the baseline, it’s clear that future losses will be significant, and not in decades or more, every year from now on. Story: https://lnkd.in/gN9z2bif #climatechange #economy #income #impacts #supplychains 

New evidence is sharpening our understanding of coastal climate risk in the Asia–Pacific region. A recent study in Scientific Reports quantifies how coastal flooding already causes USD 26.8 billion in annual losses across 29 Asia–Pacific countries. Under current policies, this figure could rise to USD 518 billion per year by 2100. Even under a 1.5 °C pathway, losses still reach USD 338 billion annually. The science is unequivocal: Small island states experience the highest relative impacts. Six million people are already affected annually, with China and Bangladesh showing the largest populations at risk, and island nations the highest exposure percentages. What is particularly notable from a scientific perspective is the study’s use of: ✅ Multi-model sea-level projections from the IPCC AR6, ✅ High-resolution ocean and tide modelling, ✅ Coupled exposure–vulnerability assessments across multiple economic sectors. The authors highlight that their estimates are conservative, as indirect losses (infrastructure disruption, supply-chain impacts, migration) are not included. This suggests that total economic and social impacts are likely to be significantly higher. From the vantage point of World Meteorological Organization, these findings reinforce a central scientific message: physical climate risks are scaling faster than societal adaptation capacity in many regions. Sea-level rise, thermal expansion, storm surge intensification, and compound flooding require integrated observation systems, advanced forecasting, and climate services that can support anticipatory planning and resilient infrastructure design. The study also provides evidence for the cost-effectiveness of adaptation. Under a 1.5 °C scenario, investing USD 9 billion in coastal defence infrastructure could avert roughly USD 157 billion in projected damages—a clear signal that climate-informed planning yields high returns. As research continues to refine projections and quantify sector-specific losses, strengthening global climate observing networks, early warning systems, and climate intelligence services becomes essential. This is exactly where #WMO’s scientific coordination and operational frameworks can support countries in translating climate data into risk-informed decisions. Scientific insights such as these are critical for guiding adaptation finance, development planning, and long-term resilience strategies—especially for the countries facing the steepest climate-related inequalities. Read the article here 👇 https://lnkd.in/ecvWz_Gz

Climate Change estimates a 12% GDP Hit: Why the Real Cost of Carbon Is 6x Higher Than previous research. New research by Adrien Bilal and Diego Känzig shows that the macroeconomic damage of climate change is six times larger than previously estimated. Global temperature rises—not local ones—are an economic threat, with a 1°C increase slashing global GDP by 12%. Their model sets the Social Cost of Carbon at $1,367/ton— above current policy benchmarks. Abstract: We estimate the macroeconomic damage function of climate change by combining a structural macroeconomic model with a new panel dataset for 174 countries over 1960–2019. Our approach overcomes the attenuation bias from local temperature shocks and separates the effects of persistent global warming from transitory local weather shocks. We find that a 1°C increase in global temperature leads to a 12% decline in world GDP. Damages are heterogeneous, with poorer and hotter countries suffering the most. These effects are driven by persistent productivity losses and are amplified by capital accumulation. Our estimated damage function implies a Social Cost of Carbon (SCC) of $1,385 per ton of carbon dioxide—more than six times the US government’s current estimate. Our results highlight the importance of accounting for macroeconomic persistence and heterogeneity when evaluating climate damages.” And link to paper in comments and below.

Nature Climate Change has highlighted our recent publication in the journal’s Research Briefing: https://lnkd.in/e9GTby5W . It is a great honor for me and the entire European Research Council (ERC) SCALAR team. In the #climate #change domain, particularly with respect to the private sector, a lack of granular #economic #data obstructs understanding and facilitation of effective climate action. Our recent article https://lnkd.in/eifdvNsG published by Nature Portfolio Climate Change and the corresponding Research Briefing present a newly developed dataset on #private #sector #investments in #climate #adaptation. Here, we present insights into five #coastal regions in the Netherlands, China, Indonesia, and the USA. Besides curious descriptive statistics, we also present a theoretical framework that connects economic and behavioral empirical research on #firms’ climate adaptation decisions. To address a debate in the literature, we test the hypothesis of whether private adaptation investments affect economic development. Our statistical analysis indicates that when the private sector invests in climate adaptation, there is an empirical signal that regional economic revenues grow, albeit inelastically, already in the short run of our data span. The paper outlines future directions, in particular for quantifying the #economic #effectiveness of #climate #adaptation. Importantly, in addition to the traditional #corporate #disclosures data or #firm-level #surveys - both valuable but relying on self-reported statements - we can also now tap into the real market data to reveal what firms actually do already today to ensure climate resilience of their enterprises. Many thanks to the team, especially Alessandro Taberna and Ignasi Cortés Arbués, for your persistent efforts on getting the right data cross-section, Sarah and Steve Howard at kMatrix https://lnkd.in/eZyE-TyB for your consistent support and flexibility, and Theodoros Chatzivasileiadis for the inspiring insights that data analysis methods can offer. TU Delft Climate Action Programme European Association of Environmental and Resource Economists (EAERE) NL AAA–Climate Resilient