Abstract. Full-scale Earth System Models (ESMs) are too computationally expensive to keep pace with the growing demand for climate projections across a large range of emissions pathways. Climate emulators, reduced-order models that reproduce the output of full-scale models, are poised to fill this niche. However, the large number of emulation techniques available and lack of a comprehensive theoretical basis to understand their relative strengths and weaknesses compromise fundamental methodological comparisons. Here, we present a theoretical framework that connects disparate emulation techniques and use it to understand potential sources of emulator error focusing on memory effects, hidden variables, system noise, and nonlinearities. This framework includes popular emulation techniques such as pattern scaling and response functions, relating them to less commonly used methods, such as Dynamic Mode Decomposition and the Fluctuation Dissipation Theorem (FDT). To support our theoretical contributions, we provide practical implementation guidance for each technique. Using pedagogical examples including idealized box models and a modified Lorenz 63 model, we illustrate the expected errors from each emulation technique considered. We find that response function-based emulators outperform other techniques, particularly pattern scaling, across all scenarios tested. Potential benefits and trade-offs from incorporating statistical mechanics in climate emulation through the use of the FDT are discussed, along with the importance of designing future scenarios for ESMs with emulation in mind. We argue that large-ensemble experiments utilizing the FDT could benefit climate modeling and impacts communities. We conclude by discussing optimal use cases for each emulator, along with implications for ESMs based on our pedagogical model results.

Abstract. This study explores changes in agricultural drought event characteristics in projections of Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for different future scenarios based on three Shared Socioeconomic Pathways (SSP). To quantify the intensity of agricultural droughts, the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6) with a 65-year reference period is applied to the simulations of 18 ESMs. In a first step, these ESMs are evaluated based on performance metrics and pattern correlations of drought related variables including precipitation and approximated reference evapotranspiration with reanalysis datasets including ERA5 and CRU. With this we extend the model benchmarking performed in the third chapter of the IPCC AR6 by 15 years and additional variables. In a second step we analyze global and regional projected SPEI6 distributions to estimate and characterize the changes in agricultural drought in the future based on multi-model means of change rates, distributions and relative area covered by specific events. We quantify the change of drought index values for 42 IPCC AR6 WG1 reference regions individually with a focus on those with most harvest area and find negative trends in water budget and SPEI for higher emission scenarios in most of them, particularly in the Mediterranean and other arid regions. This agrees with other recent studies. Increasing reference evapotranspiration emerges as the dominant driver for drier conditions in these regions. What is considered as the driest 2.3 % months during 1950–2014 is projected to be the new normal or moderate condition in arid regions by 2100, following a high emission future scenario (SSP5-8.5). For this scenario, 40 % of the harvest regions surface is considered to be under extreme drought conditions during Northern Hemisphere autumn. Under a low emission scenario (SSP1-2.6) with an expected global warming of 1.8 °C it would be less than 10 %. Our results show a significant difference between future scenarios regarding distribution shifts and spatial extent of extreme drought conditions in harvesting regions and can serves as a foundation for further impact and mitigation studies.

Abstract. The Greenland ice sheet is melting at an accelerating rate due to the warming climate. In order to understand the potentially important ice-climate feedback processes, evolving ice sheets need to be included in global climate models. Here, we present results from the first bi-directional coupling of the Earth System model NorESM2 with the ice sheet model CISM2 for the Greenland ice sheet under an extended high emission SSP5-8.5 forcing from 1850 to 2300. In our simulation, the ice-mass loss between 1850 and 2300 is equivalent to 1.4 m of sea-level rise. Comparing simulation results to an otherwise identical simulation with a fixed Greenland ice sheet, we see the same global trends in air, ocean and sea-ice changes. The main signals are a 10 °C global air temperature increase from 2000 to 2300, a reduced maximum AMOC at 26.5° N from average 23 to 9 Sv and an all-year free Arctic by 2200. Similar to other coupled CMIP models, the warming trend dominates the changes of the climate components. At the regional scale, elevation changes become an important part of the Greenland surface mass balance, accounting for 20 % of the SMB change by 2200 and for 49 % in 2300. By the year 2300, the ablation area covers 93 % of the ice area. With a low climate sensitivity and relatively weak polar amplification in NorESM2, these results are on the lower end of the spectrum of expected ice mass-loss under CMIP6 model forcing.

Abstract. Simulating the Earth's climate is an important and complex problem, thus climate models are similarly complex, comprised of millions of lines of code. In order to appropriately utilize the latest computational and software infrastructure advancements in Earth system models running on modern hybrid computing architectures to improve their performance, precision, accuracy, or all three; it is important to ensure that model simulations are repeatable and robust. This introduces the need for establishing statistical or non-bit-for-bit reproducibility, since bit-for-bit reproducibility may not always be achievable. Here, we propose a short-simulation ensemble-based test for an atmosphere model to evaluate the null hypothesis that modified model results are statistically equivalent to that of the original model. We implement this test in version 2 of the US Department of Energy's Energy Exascale Earth System Model (E3SM). The test evaluates a standard set of output variables across the two simulation ensembles and uses a false discovery rate correction to account for multiple testing. The false positive rates of the test are examined using re-sampling techniques on large simulation ensembles and are found to be lower than the currently implemented bootstrapping-based testing approach in E3SM. We also evaluate the statistical power of the test using perturbed simulation ensemble suites, each with a progressively larger magnitude of change to a tuning parameter. The new test is generally found to exhibit more statistical power than the current approach, being able to detect smaller changes in parameter values with higher confidence.

Abstract. Effective disaster risk management requires approaches that account for multiple interacting hazards, dynamic vulnerabilities, and institutional complexity. Yet many existing risk assessment methods struggle to reflect how these risks evolve in practice. This paper explores multi-hazard risk dynamics through stakeholder interviews across five European regions (Veneto, Scandinavia, the North Sea, the Danube Region, and the Canary Islands). Stakeholders described how exposure and vulnerability shift over time due to climate change, urban development, and socio-economic dependencies. The interviews highlight governance challenges and the critical role of institutional coordination, as well as synergies and asynergies in DRR measures, where efforts to reduce one risk can unintentionally increase another. By foregrounding real-world experiences across diverse hazard landscapes and sectors, this study offers empirical insights into how multi-hazard risk is perceived and managed. It underscores the need for flexible, context-sensitive strategies that bridge scientific assessment with decision-making on the ground.

Abstract. The North Atlantic subpolar gyre (SPG) plays a fundamental role in the Atlantic ocean circulation by providing an important connection between the subtropical Atlantic and the Arctic. It is driven by both wind and density differences that are, in part, caused by convection in the Labrador Sea. Through this deep convection site, the SPG is also linked to the AMOC. There is considerable evidence that this area of convection may diminish or shift in a changing climate. For this reason, the convection in the SPG is considered a tipping point. Here, we extensively study a conceptual model of the SPG to characterize the stability of convection in the gyre. The bifurcation structure of this model is analyzed in order to identify bistable parameter regions. For a range of gyre salinity and freshwater forcing levels the gyre is found to have both convective and non-convective states. Furthermore, noise-induced transitions between convective and non-convective states are possible for a wide range of parameter values. Convection in the SPG becomes increasingly unstable as the gyre salinity decreases and the freshwater forcing increases. However, convection never fully stops and can always restart after a period of no convection. This indicates that, at least in this conceptual model, a collapse of convection in the SPG does not have to be permanent.

Abstract. The climates of the polar and mid-latitude regions are linked through teleconnections. The regional details of these relationships, and how they may change with global warming, are however still uncertain. Using two large ensembles of coupled climate model simulations (CESM2, ACCESS-ESM1.5) and a composite analysis, we investigate the statistical relationships between sea ice variability and atmospheric circulation patterns, and how they evolve with sea ice retreat for both poles, including sensitivity to sea ice region in the Arctic. We find that relationships between sea ice amount and sea level pressure (SLP), the North Atlantic jet stream, and surface air temperature (SAT), depend on the region where sea ice varies. For instance, the North Atlantic jet resides further south when sea ice is low in the Labrador Sea, but is located further north and/or is weaker for low Okhotsk sea ice and is stronger and displaced northwards for low Chukchi-Bering sea ice. We also investigate the circulation patterns associated with changes in Antarctic sea ice. For the Arctic, circulation patterns tend to persist with global warming, until around 3 or 4 °C, when the ice edge has retreated substantially. In the Antarctic, patterns are sensitive to warming also at lower global warming levels for some seasons and variables, but are otherwise often persistent across warming levels. Lagged analysis suggests that the concurrent relationships mostly reflect the atmospheric conditions contributing to low sea ice, with weaker or altered patterns when sea ice leads. Our results emphasize the importance of regional heterogeneity, and on using large ensembles or other statistically rich datasets, for assessing the interlinkages between polar climate change and mid-latitude weather patterns, today and in a warmer climate. The overall persistence of teleconnection patterns between sea ice change and atmospheric circulation with global warming is encouraging, as it indicates that the main conclusions from current literature will be applicable also in a future, warmer world with less sea ice.

Abstract. Hot-dry compound extremes have recently gained increasing attention due to their potential impacts on environments and societies. For these reasons, assessing climate predictions is essential to providing reliable information on such extremes. However, despite several studies focusing on compound extremes in the past and climate projections, little is known on a multi-annual timescale. In this regard, decadal climate predictions have been produced to provide useful information for this specific timescale. Thus, we evaluate the ability of the CMIP6 multi-model decadal climate hindcast to predict hot-dry climate extremes, as well as their hot and dry univariate counterparts, for the forecast years 2–5. The multi-model skillfully predicts hot-dry compound extremes and hot extremes over most land regions, while the skill is more limited for dry extremes. However, we find only minor and spatially limited improvements from the initialisation of the hindcasts, especially for the hot-dry compound extremes, with most of the skill coming from external forcings, especially long-term trends. Finally, we find that the decadal hindcast is able to reproduce the connections between the compound extremes and their hot and dry univariate components. Evaluations of decadal hindcasts, such as this, are an essential tool for establishing the potential and limitations of these products. In turn, they represent a necessary step in providing reliable and valuable information regarding such impactful extremes.

Abstract. Irrigation, a key activity for food security, uses local water resources to increase evapotranspiration, creating feedback loops with the atmosphere and water resources. With climate change, it is unclear how irrigation will evolve in the future and how it may influence the evolution of water resources and the water cycle. It is also unclear whether irrigation may be constrained by climate change or water resource shortages. Here, we compare two surface-atmosphere simulations performed with the IPSL-CM6 model from 1950–2100: one with irrigation and one without irrigation. In both simulations, the evolutions of atmospheric radiative forcing, land use, and irrigated areas are taken from CMIP6, which uses a historical dataset for the data before 2014 and the SSP5-RCP8.5 dataset for data after 2014. The two simulations reveal strong global warming and precipitation increases between 1950–2000 and 2050–2100 average values (+5.6 °C and +8.1 %, on average, over land with irrigation). Over the same period, our results indicate an increase in irrigation (+76 % increase in irrigation in the 2050–2100 compared to the 1950–2000 period), which is in line with an important expansion of irrigated areas. The influence of irrigation on evapotranspiration in irrigated areas is greater in 2050–2100 than in 1950–2000 (+12 % vs. +8 %, respectively). Evapotranspiration has also been found to increase in non-irrigated areas near irrigated zones owing to an increase in precipitation under historical and future climate conditions. Water depletion due to irrigation is more intense in the future than in the historical period, although climate change increases water storages and river discharge due to more precipitation in the future. We also identified areas where future environmental conditions can limit irrigation or where irrigation can increase tensions over water use (approximately one-third of irrigated areas, including the Mediterranean basin, California, and Southeast Asia). Our results highlight the importance of considering irrigation in climate projections and future water resources assessments.

Abstract. The Dansgaard-Oeschger (DO) events of past glacial episodes provide an archetypical example of abrupt climate shifts and are discernible, for example, in oxygen isotope ratios from Greenland ice core records. The causes and mechanisms underlying these events are still subjects of ongoing debate. It has previously been hypothesised that DO events may be triggered by bifurcations of mechanisms operating at decadal time scales, as indicated by a significant number of early warning signals (EWS) in the high-frequency variability of records from the North Greenland Ice Core Project (NGRIP). Here, we re-evaluate the presence of EWS by employing indicators based on critical slowing down (CSD) and wavelet analysis and conduct a systematic methodological robustness test. Our findings reveal fewer significant EWS than previous studies, yet their numbers are significant for some of the indicators estimating changes in variability. Additionally, a comparison of different Greenland ice core records also shows consistency for these same EWS estimators preceding a small selection of events in records with high temporal resolution. While those indicators might represent changes in a common climate background, we cannot rule out that signals specific to the different ice core locations are captured. Nevertheless, the numbers of detected EWS are not significant for most ice core records as well as for estimators of correlation times when considered on their own, which were found to be less consistent. Based on these inconclusive results it is not possible to constrain mechanisms underlying the DO events. Instead, our results highlight the complexities and limitations of applying early warning signals to paleoclimate proxy data.