Grazing systems represent the most extensive production systems in the world and are highly sensitive to climate change. However, their global-scale sensitivity and vulnerability to climate impacts remain poorly understood. Here, we apply the safe climatic space framework to assess how changes in core climatic drivers of grazing suitability, including temperature, precipitation, humidity, and wind speed, will reshape global grassland-based grazing systems. Our analysis projects a net decline of 36 to 50% of areas in climate suitability for grazing by 2100, accompanied by inter- and intracontinental shift of grazing suitability. These changes are expected to negatively affect 110 to 140 million pastoralists and 1.4 to 1.6 billion livestock, with particularly severe impacts in Africa. We further show that 51 to 81% of these impacted populations reside in countries with low income, serious hunger, severe gender inequality, and high political fragility. Our study implies that future climate change will threaten grazing suitability across large portions of Earth, endangering the livelihoods of numerous communities and potentially triggering widespread socioeconomic consequences.

The climate niche is a widely used framework for evaluating extinction risk under climate change[1–3] but has yet to be extensively tested in the context of historical extinctions. Here, we propose to use comparative extinction risk modelling[4] to evaluate leading climate impact models in terms of how well they predict historical transitions in IUCN Red List categories for 6,288 amphibian species between 1980 and 2021[5]. Species distribution models and exposure metrics based on the climate niche framework do not predict extinction risk once accounting for species range area, a strong determinant of extinction risk. However, changes in average climate conditions across range areas do provide significant additional predictive power, with higher risk for species that have experienced faster warming or larger changes in the seasonality of precipitation. Moreover, the modeled importance of average climate conditions for extinction risk across amphibians has increased between 1980-2004 and 2004-2021. These results demonstrate that while climate change is playing an increasingly important role in elevating amphibian extinction risk, widely used methods for assessing these risks across species do not appear to accurately reflect this pattern historically.

The increasing relevance of climate change as a threat of species extinction is a pressing concern, as highlighted by the recent IUCN Red List accessment for amphibians (Luedtke et al., 2023). Despite the reported threats of climate change, measuring its influence across species remains complex and lacking the appropiate tools (Cazalis et al., 2022). Changes in "climate niche", referring to the environmental conditions necessary for a species to thrive, have long been discussed and used to predict species distributions and extinctions. Here, we utilize the recently available Red List classifications to test this paradigm within state-of-the-art predictive models of comparative extinction risk. Using historical weather data from the ERA-5 reanalysis, we explore the predictive significance of a wide range of potential definitions of climate niche exceedance. Extinction risk models have consistently identified geographic range size and human population density as important correlates to extinction risk. Also controling for factors such as habitat fragmentation, land use, human preassures, biogeographical realms and biological traits, we use a random forest model to predict the transitions between Red List categories for over 5.000 amphibian species and evaluate results against the official accessments. This approach tests the evidence base of the climate niche paradigm and evaluates its effectiveness as a tool for incorporating climate change into extinction risk models.Luedtke, J.A., Chanson, J., Neam, K. et al. Ongoing declines for the world’s amphibians in the face of emerging threats. Nature 622, 308–314 (2023). https://doi.org/10.1038/s41586-023-06578-4Cazalis, V., Di Marco, M., Butchart, S. H. et al., Bridging the research-implementation gap in iucn red list assessments, Trends in Ecology & Evolution (2022).https://doi.org/10.1016/j.tree.2021.12.002

Terrestrial water storage (TWS) is an essential resource for agriculture, urban development, and energy production, as well as ecosystem health and climate change mitigation. Through satellite gravimetry methods, GRACE and GRACE-FO measurements enable the assessment of TWS anomalies globally, revealing significant alterations over the past two decades due to natural variability, climate change impacts, and direct human influence. Existing studies focus on the impacts of TWS changes on the production of specific crops or agricultural output in specific countries, yet the effects on agro-economic output on a more global scale are not yet well understood. To address this gap in our understanding of the macroeconomic impacts of TWS changes, we combine GRACE measurements with data on economic growth from more than 1600 subnational regions worldwide over the last 60 years. We then empirically assess the impact of TWS anomalies on regional economic growth, employing a long-difference model and fixed-effects panel regression, following recent work on temperature and precipitation impacts. We find that negative groundwater anomalies are associated with reductions in economic growth in a majority of regions. This highlights the critical role of freshwater availability, in particular in low-income regions. Furthermore, we observe that the relationship between TWS and economic growth depends on both meteorological and socioeconomic factors. These heterogeneous relations reflect the complex interplay between water resources and economic development, and indicate potential endogeneity therein. We therefore further discuss instrumental variable approaches for isolating the meteorological drivers of water storage and their causal impact on economic output. These findings contribute valuable insights to the ongoing discourse on sustainable water management and its implications for economic prosperity.

Assessments of the effects of climate change on terrestrial biodiversity typically rely on species distribution models [1] which neither exploit data on historical abundance changes nor consider the potentially important role of climate extremes. Here, we combine global data on the abundance of vertebrate species populations [2] with metrics of exposure to local climate conditions to demonstrate that historical warming and increased exposure to heat, heavy precipitation extremes and drought have had significant impacts on abundance, even after controlling for changing human pressures. Fixed-effects models reveal plausibly causal impacts which vary by species class and habitat system, as well as by latitude and the extent of human pressure. Results indicate that warming and intensified heat extremes have negative impacts at low latitudes for freshwater fish and terrestrial birds. By contrast, warming can bring benefits to freshwater birds and terrestrial mammals. Heavy precipitation extremes and drought appear to have had mainly negative impacts on abundance across species’ and habitats. We then combine these empirical results with estimates of the changes in climate conditions and extremes which are attributable to anthropogenic influence, using an established impact-attribution framework [3]. This approach reveals that anthropogenic climate change has caused considerable alterations to the abundance of terrestrial life, for example by reducing the abundance of terrestrial birds and freshwater fish by up to 40% at low latitudes. [1] Thomas, Chris D., et al. "Extinction risk from climate change." Nature 427.6970 (2004): 145-148. [2] Loh, Jonathan, et al. "The Living Planet Index: using species population time series to track trends in biodiversity." Philosophical Transactions of the Royal Society B: Biological Sciences 360.1454 (2005): 289-295. [3] Mengel, Matthias, et al. "ATTRICI v1. 1–counterfactual climate for impact attribution." Geoscientific Model Development 14.8 (2021): 5269-5284.

Climate change is having widespread impacts on ecosystems worldwide, but the extent to which it may have already altered the abundance of major taxa remains unknown. Here, we show that the historical intensification of climate extremes has substantially reduced the abundance of terrestrial bird populations over the past five decades. Combining over 86,000 time-series observations of population abundance with exposure to locally defined climate extremes, we find strong and robust evidence that hot extremes reduce abundance growth, dominating the role of average temperature conditions or changes in precipitation. These impacts are largest in lower-latitude tropical regions and are robust when controlling for changing human pressure and the geographic and taxonomic bias of observed populations. Quantifying the portion of extreme intensification which is attributable to climate change implies substantial historical reductions in bird-abundance of up to 50% at low latitudes. These results provide new evidence that human-driven intensification of heat extremes is degrading the abundance of a major terrestrial vertebrate class, of particular relevance given hitherto unexplained declines of tropical birds in undisturbed habitats.

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model dis-crepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global tempera-ture change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation ex-tremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution.

Historically, economic growth has been closely coupled to carbon emissions responsible for climate change, but to stabilize global mean temperature, net-zero carbon emissions are necessary. Some economies have begun to reduce emissions while continuing to grow, but this decoupling is not fast enough to achieve global climate targets. Subnational climate actions seem to be crucial for the achievement of these targets. Here, we uncover the effectiveness of subnational efforts by estimating decoupling rates and CO2 emission intensities over the last three decades for over 1,500 subnational regions, encompassing 85% of global emissions, using global data on reported economic output and gridded production-based emissions. Thirty percent of regions with available data have fully decoupled, with higher-income and historically carbon-intensive regions exhibiting higher rates of decoupling and declining emission intensity. Countries of the Organization for Economic Co-operation and Development with greater spending on subnational climate actions show higher decoupling rates, as do subnational regions in EU countries where climate policies have been implemented, highlighting the effectiveness of subnational policies. Moreover, subnational analysis reveals greater variance of decoupling rates within national boundaries than between them and that countries with weaker governance typically show higher variance of decoupling within their borders. If recent rates of production-based carbon decoupling continue, less than half of subnational regions would reach net-zero before 2050, even when accounting for observed acceleration via socioeconomic development and assuming no interregional carbon leakage.

The social cost of carbon (SCC) is a central tool for climate policy-making. Estimates of the SCC depend crucially on their representation of climate damages. Recent developments in climate econometrics have increased the level of spatial detail, constrained the persistence, and widened the scope of climatic drivers of impacts on macroeconomic growth, but their implications for the SCC remain unexplored. Here we integrate a reduced form representation of such empirical damages in the state-of-the-art Integrated Assessment Model GIVE. At a near-term discount rate of 2%, damages imply a SCC of $2520 with a likely range of $1330-4250 based on uncertainty in the econometric, climate and integrated assessment models, an order of magnitude greater than recent sector-specific calibrations. Accounting for the variability of temperature and the variability and extremes of precipitation increases estimates of the SCC by over 80% compared to damages from average temperature alone. Constraining the persistence of impacts on growth alters the SCC by orders of magnitude, increasing over forty-fold compared to empirical specifications which assume no persistence and decreasing four-fold compared to those which assume infinite persistence. Exploring the potential of adaptation to reduce damages, we find that halving economic vulnerability to impacts within the next 23 years would be necessary to bring the SCC below 1000$.

Climate impacts on economic productivity indicate that climate change may threaten price stability. Here we apply fixed-effects regressions to over 27,000 observations of monthly consumer price indices worldwide to quantify the impacts of climate conditions on inflation. Higher temperatures increase food and headline inflation persistently over 12 months in both higher- and lower-income countries. Effects vary across seasons and regions depending on climatic norms, with further impacts from daily temperature variability and extreme precipitation. Evaluating these results under temperature increases projected for 2035 implies upwards pressures on food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per-year respectively on average globally (uncertainty range across emission scenarios, climate models and empirical specifications). Pressures are largest at low latitudes and show strong seasonality at high latitudes, peaking in summer. Finally, the 2022 extreme summer heat increased food inflation in Europe by 0.43-0.93 percentage-points which warming projected for 2035 would amplify by 30-50%.

Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long-time horizons. Here, we utilize recent empirical findings from more than 1600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation including daily variability and extremes. Using an empirical approach which provides a robust lower-bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years due to historical carbon emissions and socioeconomic inertia (relative to a baseline without climate impacts, likely range of 11-29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to two degrees by sixfold over this near-term timeframe, and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately fifty percent and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, where reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

Climate change is aggravating water scarcity worldwide. In rural households lacking access to running water, women often bear the responsibility for its collection, with adverse effects on their well being through long daily time commitments, physical strain and mental distress. Here we show that rising temperatures will exacerbate this water collection burden globally. Using fixed-effects regression, we analyse the effect of climate conditions on self-reported water collection times for 347 subnational regions across four continents from 1990 to 2019. Historically, a 1 degrees C temperature rise increased daily water collection times by 4 minutes. Reduced precipitation historically increased water collection time, most strongly where precipitation levels were low or fewer women employed. Accordingly, due to warming by 2050, daily water collection times for women without household access could increase by 30% globally and up to 100% regionally, under a high-emissions scenario. This underscores a gendered dimension of climate impacts, which undermines womens' welfare. Water scarcity is becoming increasingly severe under climate change, and women often bear most of the burden of collecting water. This research finds that both temperature rises and reduced precipitation increase women's daily water collection time, thereby undermining their welfare globally.

Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.

This repository contains secondary data and code necessary to reproduce the results of the manuscript: Global warming and heat extremes to exacerbate inflationary pressures. M. Kotz, F. Kuik, E. Liz, C. Nickel. Nature Communications Earth & Environment (2023). For further information please contact: maxkotz@pik-potsdam.de This document contains: 1. An outline of the data included in the repository. 2. An outline of the code included in the repository. See the README for further details. Credit and thanks go to Miles Parker, Chiara Osbat and Emanuele Franceschi for compiling the inflation data which is used in this study. Inflation data provided here has been anonymised (countries shuffled and names replaced by random letter combinations) to enable reproduction of our results, while limiting further use. Moreover, inflation in terms of the change in the logarithm of prices is included, whereas the level of price indices are excluded. For full inflation data please see the forthcoming publication by Miles Parker, Chiara Osbat,and Emanuele Franceschi (contact Miles.Parker@ecb.europa.eu for further enquiries into the raw inflation data).

Understanding the behavioral response dynamics to risks is important for informed policy-making at times of crises. Here we elucidate two response channels to Covid-19 risk and show that they weakened over time, prior to the availability of vaccines. We employ fixed-effects panel regression models to empirically assess the relationship between actual Covid-19 risk (daily case numbers), the perceived risk (attention paid to the pandemic via related Google search requests) and the resulting behavioral response (personal mobility choices) over two pandemic phases for 113 cities in eight countries, while accounting for government interventions. Prolonged exposure to Covid-19 reduces risk perception which in turn leads to a weakened behavioral response. Attention responses and mobility reductions across all three mobility types are weaker in the second phase, given the same levels of actual and perceived risk, respectively. Our results provide evidence that the risk response attenuates over time with implications for other crises evolving over long timescales.

Understanding of the macroeconomic effects of climate change is developing rapidly, but the implications for past and future inflation remain less well understood. Here we exploit a global dataset of monthly consumer price indices to identify the causal impacts of changes in climate on inflation, and to assess their implications under future warming. Flexibly accounting for heterogenous impacts across seasons and baseline climatic and socio-economic conditions, we find that increased average temperatures cause non-linear upwards inflationary pressures which persist over 12 months in both higher- and lower-income countries. Projections from state-of-the-art climate models show that in the absence of historically un-precedented adaptation, future warming will cause global increases in annual food and headline inflation of 0.92-3.23 and 0.32-1.18 percentage-points per year respectively, under 2035 projected climate (uncertainty range across emission scenarios, climate models and empirical specifications), as well as altering the seasonal dynamics of inflation. Moreover, we estimate that the 2022 summer heat extreme increased food inflation in Europe by 0.67 (0.43-0.93) percentage-points and that future warming projected for 2035 would amplify the impacts of such extremes by 50%. These results suggest that climate change poses risks to price stability by having an upward impact on inflation, altering its seasonality and amplifying the impacts caused by extremes.

Projections of precipitation from global climate models are crucial for risk assessment and adaptation strategies under different emission scenarios, yet model uncertainty limits their application. Here, we assess inter-model differences by separating the response of precipitation to anthropogenic forcing within 21 individual, bias-adjusted CMIP6 models using a pattern filtering technique. The forced response of mean precipitation, the number of wet days and the intensity and frequency of daily extremes are identified using low-frequency component analysis. Inter-model agreement in the sign of local change is moderate across land areas, with better agreement for extreme metrics (90\% of models agree on 51, 41, 61, 61\% of land area, for each metric respectively). Differences in the average magnitude of local changes are also large but can be explained well by the magnitude of global surface warming, despite model differences in the sign of local change (R^2 of 0.81, 0.79, 0.69, 0.79). Moreover, we show that these temperature-precipitation scaling relationships can be identified robustly within individual climate models from inter-temporal changes in the detected forced response (median R^2 of 0.82, 0.82, 0.76, 0.87). Inter-model spread in these relationships is considerable (coefficient of variation of 22, 33, 26, 17%), thus diagnosing a source of the uncertainty in the magnitude of projected precipitation change. These results suggest that despite uncertainty in the sign of regional change, the magnitude of future precipitation changes is well constrained by temperature-scaling relationships both across and within models. They may offer a new avenue to constrain the magnitude of future projections.

Macro-economic assessments of climate impacts lack an analysis of the distribution of daily rainfall, which can resolve both complex societal impact channels and anthropogenically forced changes 1 – 6 . Here, using a global panel of subnational economic output for 1,554 regions worldwide over the past 40 years, we show that economic growth rates are reduced by increases in the number of wet days and in extreme daily rainfall, in addition to responding nonlinearly to the total annual and to the standardized monthly deviations of rainfall. Furthermore, high-income nations and the services and manufacturing sectors are most strongly hindered by both measures of daily rainfall, complementing previous work that emphasized the beneficial effects of additional total annual rainfall in low-income, agriculturally dependent economies 4 , 7 . By assessing the distribution of rainfall at multiple timescales and the effects on different sectors, we uncover channels through which climatic conditions can affect the economy. These results suggest that anthropogenic intensification of daily rainfall extremes 8 – 10 will have negative global economic consequences that require further assessment by those who wish to evaluate the costs of anthropogenic climate change.