Regional Adaptation Strategies Research Articles

Evaluation of atmospheric moisture transport to the Tibetan Plateau from 33 CMIP6 models

Atmospheric moisture transport is pivotal in regulating water resources over the Tibetan Plateau (TP). With the growing concerns about climate change, understanding the evolution of atmospheric moisture transport over the TP has become increasingly critical. however, the spatiotemporal distinctions of this transport remain poorly understood in the CMIP6 models. Here, we conducted a comprehensive evaluation of simulated historical atmospheric moisture transport from 33 CMIP6 models, utilizing a novel methodology that assesses the accuracy of model simulations in replicating regional atmospheric moisture transport over the TP. Our results indicate that the CMIP6 models generally succeed in reproducing the broad spatial patterns of atmospheric moisture transport. Nonetheless, substantial errors occur during the monsoon period, primarily attributable to inaccuracies in the location, movement, and intensity of the simulated Indian summer monsoon. The coarser resolution and poor representation of physical processes are potential reasons for errors in atmospheric moisture transport simulation over the TP. The Failure to simulate the terrain blocking on atmospheric moisture transport exacerbates these deficiencies, leading to significant discrepancies. Of the 33 CMIP6 models we investigated, over one-third displayed serious deficiencies in this regard. While coarser resolution and orographic gravity waves are plausible factors, they do not fully account for all the results obtained in this study. Insufficiently detailed or inaccurate topographic data used in the models may also contribute to this deficiency. This study highlights the necessity of using rigorously evaluated models to develop effective regional adaptation strategies over the Tibetan Plateau.

Tackling local environmental challenges with livelihoods strategies: insights from small-scale farmers in the vulnerable region of Ghana

ABSTRACT Climate risks pose significant challenges to farmers' livelihoods, particularly in sub-Saharan Africa, where the complex interplay of factors intensifies the impact on small-scale farmers (SSFs). While there is a broad understanding of climate change's effects on agriculture, there is a need for deeper insights into the key determinants and preferences influencing SSFs' adaptation strategies in vulnerable regions to better inform agricultural policy and planning. Data were collected from 325 SSF randomly selected in Juaben Municipality, Ghana. Quantitative analysis was done using descriptive and inferential statistics, while qualitative data were analyzed through content analysis. The study identified shifting planting dates, altering farm operation timings and mulching as primary adaptation strategies. Significant associations were found between socio-economic factors and the adaptation strategies employed by SSFs, with the Relative Importance Index highlighting affordable tools, land ownership and access to fertile land as crucial for enhancing livelihoods and adaptation. The findings underscore the need for training programmes to equip extension officers with the knowledge to support SSFs in developing skills and efforts related to adaptation and viable livelihood options.

Impact of extreme rainfall on high-speed rail (HSR) delays in major lines of China

Abstract Punctuality monitoring and analysis aims to optimize resource allocation for enhancing rail traffic performance and quality. Adverse weather conditions, particularly heavy precipitation events, are recognized as significant drivers of delays and reduced punctuality of the rail system. This study addresses two key research questions using HSR as an example – what is the impact of rainfall on HSR’s delay, and to what extent are HSR vulnerable to rainstorms. The data for the study were collected from the HSR on the major lines of eastern China in the rainy season of 2015-2017 which lasted from May to October. High-resolution precipitation data is integrated with non-spatial HSR operational data using GIS to create composite grids covering buffer zones around HSR lines. These grids match the spatial scale of historical hourly precipitation data and enable regression analyses to assess how precipitation affects HSR operations. The results indicate that extreme rainfall significantly contributes to delays and reduced punctuality, with varying impacts observed across different HSR lines. Specifically, daily areal precipitation significantly delays services on the Hangzhou-Shenzhen and Nanjing-Hangzhou HSR lines. Rainfall intensity has a more pronounced impact on delay services of the Beijing-Shanghai HSR, while extreme precipitation most frequently affects the Shanghai-Nanjing and Jinhua-Wenzhou HSR lines. The case analysis enhances understanding of HSR vulnerability to heavy rainfall conditions and recommends regional adaptation strategies to manage climate-related uncertainties.

Assessing teleconnection influences on the spatial and temporal patterns of meteorological drought in Northwest China

ABSTRACT This study delves into the complex relationship between teleconnection patterns and meteorological drought in Northwest China, highlighting the crucial influence of global circulation indices on regional drought dynamics. By analyzing precipitation and temperature data from 1962 to 2022 using the CN05.1 datasets and incorporating various global circulation indices, the study employs the Standardized Precipitation Evapotranspiration Index (SPEI) to delineate drought conditions. Utilizing the Modified Mann-Kendall test and segmented models for trend and change point detection, along with cross wavelet transforms (XWT) and wavelet coherence (WTC) analysis to examine the impact of 15 global circulation indices, the study uncovers significant spatial and temporal climatic variations. Findings indicate a significant increase in temperature and precipitation, with March-April-May (MAM) season showing pronounced drought severity mainly due to a significant temperature rise with a value of 0.0420 °C/year. Change point analysis reveals pivotal shifts in climate, highlighting the region’s susceptibility to climate change. The study identified strong correlations between drought occurrences and global circulation indices like the Artic Oscillation (AO), Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI), especially within a 4–8 year timeframe, pointing to the significant role of teleconnections in affecting local drought conditions. These insights are vital for formulating effective drought management and climate adaptation strategies in arid and semi-arid regions, offering valuable guidance for policymakers and researchers focused on improving water resource management and enhancing climate resilience in such vulnerable environments.

Influences of climate change on carbon and water fluxes of the ecosystem in the Qinling Mountains of China

Climate change is one of the foremost challenges confronting the contemporary world. Carbon and water cycles and their interconnections of ecosystems are playing a pivotal role in assessing the impacts of climate change on ecosystems. The Qinling Mountains of China represent a focal area for research on global climate change and regional adaptation strategies. Based on historical and CMIP6 (Coupled Model Intercomparison Project Phase 6) future climatic data, the Biome-BGC model, which was sufficiently optimized with the Biome-BGC-PEST package, was used to simulate the historical and future trends of GPP (Gross primary productivity), ET (Evapotranspiration), and WUE (Ecosystem water use efficiency) in the Qinling Mountains, so as to elucidate the dynamics and spatiotemporal variations of carbon and water fluxes amidst climate change. The results showed that the GPP, ET, and WUE of the Qinling Mountains heterogeneously distributed in space, due to the dramatic disparities in carbon and water fluxes among different vegetation types in the Qinling Mountains. Among the various vegetation types, evergreen needle-leaved forest had the highest annual mean value of WUE. In the historical period of 1979-2018, deciduous broad-leaved forest had the highest annual mean value of GPP and ET, while evergreen needle-leaved forest would dominate in the future (2021-2100). For the annual GPP and ET flux variations, different vegetation cover types followed varying peak patterns in the Qinling Mountains. Deciduous broad-leaved forest, evergreen needle-leaved forest, and shrub meadow showed ’single-peak’ pattern annually, whereas the crop area displayed ’double-peak’ pattern due to the different growing seasons of crops. There also were temporal variations for the carbon and water fluxes within the same vegetation type. Future projections suggested a continuous increase in GPP and ET fluxes, underscoring the consistent role of the Qinling Mountains in water resource conservation and carbon sink amid evolving climatic conditions.

Environmental Aspects and Impacts of Porto Seco: the Case of the Largest Dry Port in Latin America, Located in Foz do Iguaçu (Brazil)

Objective: This work aims to present and describe the process of identifying and classifying environmental aspects in a Brazilian dry port. Theoretical Framework: The Climate Change Adaptation Strategies aim to reduce greenhouse gas (GHG) emissions, increase the share of renewable energy in total energy production and increase the energy efficiency. Unfortunately, road-based dry ports increase heavy truck congestion, energy consumption and, inherently, GHG emissions. Method: The general approach includes a literature review on the importance of managing environmental aspects and impacts in dry ports, followed by the description of the holistic procedure that involves the inventory of port activities linked to environmental aspects, the Leopold matrix and specialized knowledge about the local context (e.g., compliance with law, regional climate change adaptation strategy, stakeholder concerns) to perform the classification. Results and Discussion: The results showed that atmospheric emissions, noise and resource consumption are among the most significant environmental aspects of dry port. The absence of a railway that enables a multimodal transport system and the fact that the port is located in the city center constitute a disadvantage that worsens road congestion and air emissions, since the train would reduce GHG emissions. Research Implications: The work contributes to the planning and management of the activities of Foz do Iguaçu Dry Port considering environmental aspects and impacts, direct and indirect, from a holistic perspective. Originality/Value: The work presents a ranking of the environmental aspects and impacts of dry port to help defining priority actions in light of climate change strategies.

Exploring Historical Patterns of Urban Migration in Pakistan: Origins and Drivers

This study explores the historical patterns and antecedents of urban migration in Pakistan, focusing on the interaction of demographic, economic, and environmental factors. Economic factors like wage disparities, job opportunities, and service access significantly influence migration. Rapid urbanization and inadequate infrastructure make it difficult to house and integrate migrants, exacerbating existing housing, transportation, and healthcare issues. The study advocates for evidence-based policymaking, utilizing descriptive analysis, focusing on sustainable urban development, migrant welfare, and inclusive growth. This study has identified various economic, demographic, and environmental factors that have contributed to rapid urbanization, such as migration for healthcare, education, and services. Still, low economic growth and rapid population growth lead to higher unemployment, low wages, natural disasters, and political instability. It emphasizes prioritizing rural development, improving urban infrastructure, and increasing disaster resilience. Proposals call for regional cooperation and climate change adaptation strategies to address cross-border migration challenges.

Shifts in bioclimatic zones mirror climate change signals in a tropical agriculture‐dominated Bharathapuzha River basin of southern Western Ghats (India)

AbstractAssessing anthropogenic climate change in a regional context is challenging due to the spatial heterogeneity of climatic variables and is more complicated than at the global scale. Especially in the Tropics, such spatial variations are expected to increase, warranting the identification of homogeneous climatic zones for assessing regional climate change. The present study explores the ability of bioclimatic variables in defining regional climatic zones, and the detection of climate change therein. We hypothesize that the identification of homogeneous climatic zones based on bioclimatic variables could be an effective approach rather than the conventional extreme climate‐based indices to identify climate change signals. To demonstrate the hypothesis, bioclimatic variables representing the generalized climatic characteristics of a tropical river basin were derived from observed gridded datasets of rainfall and temperature. Clusters of homogeneous climatic zones were identified, and their temporal variations were analysed to examine the existence of climate change. The results indicate that despite the spatial heterogeneity in extreme climate‐based indices, the bioclimatic variables‐based approach renders a meaningful representation of the regional climatic pattern. Investigation of bioclimatic zones of the study area helped to identify a shift in its climatic zones with a slant towards drier conditions. Further, future changes in climatic zones were identified from 13 different GCMs that participated in the CMIP6, projecting drier conditions over the basin, with varying spatial extend based on future emission scenarios. The study significantly contributes towards the identification of climatologically fragile regions in changing climate, which is an essential component in developing any regional climate change adaptation and mitigation strategy.

Intensification and Poleward Shift of Compound Wind and Precipitation Extremes in a Warmer Climate

AbstractCompound wind and precipitation extremes (CWPEs) can severely impact natural and socioeconomic systems. However, our understanding of CWPE future changes, drivers, and uncertainties under a warmer climate is limited. Here, by analyzing the event both on oceans and landmasses via state‐of‐the‐art climate model simulations, we reveal a poleward shift of CWPE occurrences by the late 21st century, with notable increases at latitudes exceeding 50° in both hemispheres and decreases in the subtropics around 25°. CWPE intensification occurs across approximately 90% of global landmasses, and is most pronounced under a high‐emission scenario. Most changes in CWPE frequency and intensity (about 70% and 80%, respectively) stem from changes in precipitation extremes. We further identify large uncertainties in CWPE changes, which can be understood at the regional level by considering climate model differences in trends of CWPE drivers. These results provide insights into understanding CWPE changes under a warmer climate, aiding robust regional adaptation strategy development.

Storylines for Global Hydrologic Drought Within CMIP6

AbstractFuture global increases in the duration and severity of hydrologic drought present an emerging challenge for water resource management. However, projected changes to drought within global climate models are often complex, including potentially co‐occurring changes to the timing, duration, and severity of drought. Here, we apply a storyline approach for interpreting projections of future hydrologic drought to identify coherent narratives that include runoff trends, shifts in the seasonal drought timing, increases in multi‐year drought frequency, and increased drought severity within the Coupled Model Intercomparison Project Phase 6. We develop a framework to classify future drought storylines (2015–2100) and quantify model consensus to determine the most‐likely “dominant” storyline under four emission scenarios Shared Socioeconomic Pathways (SSPs) 1–2.6, 2–4.5, 3–7.0, and 5–8.5. Under a low‐emission scenario (SSPs 1–2.6) approximately one third of the land‐area is projected to be impacted by a dominant storyline of minimally detectable runoff trend paired with increased frequency of multi‐year drought. However, under the highest‐emission scenarios (SSPs 5–8.5), the most likely storyline shifts to an increase in multi‐year drought frequency, increased severity of drought, and negative long‐term runoff trends for 62% of the area in those same regions. Shifts in the seasonal timing of drought are a component of dominant storylines for the northern latitudes across all emission scenarios. These results provide an alternative mode of interpretation of co‐occurring changes to the features of future drought, framed in a way to support regional adaptation strategies to mitigate future drought impacts.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (− 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (− 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Future extreme and compound events in Angola: CORDEX-Africa regional climate modelling projections

Angola is exceptionally vulnerable to climate change, and sectors such as health, agricultural, water resources and ecosystems may endure severe impacts. Here, an extensive analysis of the signal of climate change on temperature, precipitation, extremes and compound events, for the end of the 21st century, is presented. The analysis is based on a CORDEX-Africa multi-model ensemble at 0.44° resolution built with 19 individual simulations, which allows a robust study of climate change future projections and depict model's uncertainty. For the RCP8.5, the end of the century future warming can reach maxima values ∼ 7 °C for maximum temperature in south-eastern Angola, and 6 °C for minimum temperature. The extreme temperatures (90th percentile) is projected to rise more than 7 °C in southern areas. In general, projections display a rainfall reduction in the drier seasons and a rise in the wet seasons, leading to sharper annual cycles; it is also projected a growth on extreme precipitation (95th percentile), as much as plus ∼ 50 % in some coastal regions. Angola is projected to endure in the future more frequent and longer heatwaves and droughts. In agreement with the RCP8.5, up to 10 heatwaves and more 4 moderate droughts will occur, respectively in coastal and interior areas. Finally, the number of days when a compound of heatwave and moderate drought occurs is projected to growth immensely, around +30 % for many regions, which corresponds to multiply by 10 these events in the future. For the RCP4.5, changes are projected to be smaller but significant in what regards especially extremes and compound events. The magnitude of the projected changes for vulnerable countries as Angola constitute an urgent call for global mitigation and national to regional adaptation strategies, and ultimately to a constant effort of updating and deepen the quality of climate information produced.

A Multi-Approach and Collaborative Pathway towards Designing Climate Strategies: The Case of Trentino, a Mountainous Region in Italy

Mountainous and rural territories are considered among the most vulnerable to the effects of the Climate Crisis. Their geographical and topographical conditions, together with the complexity of the system of relations between human and natural elements, amplify the impacts and risks associated with extreme climatic events. Therefore, the consequences on the socio-economic fabric are systemic and require an immediate response from all the actors in a region. Public administration and politics can play a pivotal role within the planning framework in contrasting the impacts of the climate crisis. This paper demonstrates the multi-level and multi-stakeholder approach applied during the development process of a regional adaptation strategy. The Autonomous Province of Trento has initiated an innovative approach to understanding and managing the effects of the climate crisis on its landscape and resources and has aligned the process of definition of its long-term strategy with the guidance provided by the EU Commission and the Italian Government. The methodology used is based on the tools provided by the Climate-ADAPT platform (in particular, the Regional Adaptation Support Tool—RAST), and the “impact chains” method is specifically implemented for climate risk assessment. The RAST is applied according to a multi-stakeholder and multi-level approach to capitalise on previously established and ongoing initiatives and working groups. The research suggests that the Climate Strategy model presented in this paper needs to be at the core of the broader framework adopted by the Autonomous Province of Trento and that it can represent an important example for other regions aiming to actively involve local stakeholders in acting for climate neutrality and resilience.

Evaluating the temperature–mortality relationship over 16 years in Cyprus

ABSTRACT In many regions of the world, the relationship between ambient temperature and mortality is well-documented, but little is known about Cyprus, a Mediterranean island country where climate change is progressing faster than the global average. We Examined the association between daily ambient temperature and all-cause mortality risk in Cyprus. We conducted a time-series analysis with quasipoisson distribution and distributed lag non-linear models to investigate the association between temperature and all-cause mortality from 1 January 2004 to 31 December 2019 in five districts in Cyprus. We then performed a meta-analysis to estimate the overall temperature-mortality dose-response relationship in Cyprus. Excess mortality was computed to determine the public health burden caused by extreme temperatures. We did not find evidence of heterogeneity between the five districts (p = 0.47). The pooled results show that for cold effects, comparing the 1st, 2.5th, and 5th percentiles to the optimal temperature (temperature associated with least mortality, 25 ℃), the overall relative risks of mortality were 1.55 (95% CI: 1.32, 1.82), 1.41 (95% CI: 1.21, 1.64), and 1.32 (95% CI: 1.15, 1.52), respectively. For heat effects, the overall relative risks of mortality at the 95th, 97.5th and 99th percentiles were 1.10 (95% CI: 1.04, 1.16), 1.17 (95% CI: 1.07, 1.29), and 1.29 (95% CI: 1.11, 1.5), respectively. The excess mortality attributable to cold days accounted for 8.0 deaths (95% empirical CI: 4.5–10.8) for every 100 deaths, while the excess mortality attributable to heat days accounted for 1.3 deaths (95% empirical CI: 0.7–1.7) for every 100 deaths. The results prompt additional research into environmental risk prevention in this under-studied hot and dry region that could experience disproportionate climate change related exposures. Implications: The quantification of excess mortality attributable to temperature extremes shows an urgent need for targeted public health interventions and climate adaptation strategies in Cyprus and similar regions facing rapid climate change. Future steps should look into subpopulation sensitivity, coping strategies, and adaptive interventions to reduce potential future risks.

Mapping the race between crop phenology and climate risks for wheat in France under climate change.

Climate change threatens food security by affecting the productivity of major cereal crops. To date, agroclimatic risk projections through indicators have focused on expected hazards exposure during the crop's current vulnerable seasons, without considering the non-stationarity of their phenology under evolving climatic conditions. We propose a new method for spatially classifying agroclimatic risks for wheat, combining high-resolution climatic data with a wheat's phenological model. The method is implemented for French wheat involving three GCM-RCM model pairs and two emission scenarios. We found that the precocity of phenological stages allows wheat to avoid periods of water deficit in the near future. Nevertheless, in the coming decades the emergence of heat stress and increasing water deficit will deteriorate wheat cultivation over the French territory. Projections show the appearance of combined risks of heat and water deficit up to 4years per decade under the RCP 8.5 scenario. The proposed method provides a deep level of information that enables regional adaptation strategies: the nature of the risk, its temporal and spatial occurrence, and its potential combination with other risks. It's a first step towards identifying potential sites for breeding crop varieties to increase the resilience of agricultural systems.

Conservation of Water Resources in a Botanic Garden

Water-resource challenges, encompassing both quality and quantity, pose significant threats to Florida’s ecosystems, especially in the face of climate change, rising sea levels, and rapid urbanization. This paper explores the innovative stormwater-management system implemented at Naples Botanical Garden as a model for addressing these challenges. The Garden’s approach, treating stormwater as a valuable resource, involves dry and wet retention areas, created lakes, and a unique River of Grass, mimicking natural ecosystems. This system not only mitigates flooding, but also effectively removes pollutants, recharges the aquifer, and provides a habitat for diverse wildlife. The paper emphasizes the economic, environmental, and social impacts of traditional stormwater-management practices in Florida. Naples Botanical Garden’s case serves as a guide for botanical gardens and zoos globally, showcasing the pivotal role these institutions can play in sustainable water-resource management. The collaborative design process involving landscape architects, engineers, and horticulturists ensures a holistic and aesthetically pleasing approach to stormwater management. The paper underscores the role of botanical gardens in promoting nature-based solutions, educating the public, and offering tangible steps for implementing similar systems worldwide. It can help guide regional adaptation strategies to manage stormwater as a resource.

Assessing Regional-Scale Heterogeneity in Blue–Green Water Availability under the 1.5°C Global Warming Scenario

Abstract The 2015 Paris Agreement outlined limiting global warming to 1.5°C relative to the preindustrial levels, necessitating the development of regional climate adaptation strategies. This requires a comprehensive understanding of how the 1.5°C rise in global temperature would translate across different regions. However, its implications on critical agricultural components, particularly blue and green water, remains understudied. This study investigates these changes using a rice-growing semiarid region in central India. The aim of this study is to initiate a discussion on the regional response of blue–green water at specific warming levels. Using different global climate models (GCMs) and shared socioeconomic pathways (SSPs), the study estimated the time frame for reaching the 1.5°C warming level and subsequently investigated changes in regional precipitation, temperature, surface runoff, and blue–green water. The results reveal projected reductions in precipitation and surface runoff by approximately 5%–15% and 10%–35%, respectively, along with decrease in green and blue water by approximately 12%–1% and 40%–10%, respectively, across different GCMs and SSPs. These findings highlight 1) the susceptibility of blue–green water to the 1.5°C global warming level, 2) the narrow time frame available for the region to develop the adaptive strategies, 3) the influence of warm semiarid climate on the blue–green water dynamics, and 4) the uncertainty associated with regional assessment of a specific warming level. This study provides new insights for shaping food security strategies over highly vulnerable semiarid regions and is expected to serve as a reference for other regional blue/green water assessment studies. Significance Statement This study helps to drive home the message that a global agreement to limit the warming level to 1.5°C does not mean local-scale temperature (and associated hydrological) impacts would be limited to those levels. The regional changes can be more exaggerated and uncertain, and they also depend on the choice of the climate model and region. Therefore, local-scale vulnerability assessments must focus on the multidimensional assessment of a 1.5°C warmer world involving different climate models, climate-sensitive components, and regions. This information is relevant for managing vulnerable agricultural systems. This study is among the first to investigate the critical agricultural components such as the blue–green water over a semiarid Indian region, and the findings and methodology are expected to be transferable for performing regional-scale assessments elsewhere.

Fluctuations in extreme temperatures in northern Morocco and the impact of climate change: Contribution of the Regional Climate Model (RegCM)

In this study, we use the RegCM4.6 regional climate model to simulate extreme air temperatures in northern Morocco, with a focus on the Tangier-Tetouan-Al Hoceima (TTA) region. In pursuit of this, we evaluate its performance by comparing its simulations with CRU observational data and HadGEM2-ES historical simulations over 35 years for the purpose of predicting future temperature evolution by the end of the century in the region using the validated RegCM4.6 model. The results show a slight underestimation of temperatures compared to observations, with a preference for the RegCM4.6 model over HadGEM2-ES. Projections indicate a mean temperature increase of 2°C (RCP4.5) to 4.62°C (RCP8.5) by 2099, highlighting the need for regional adaptation strategies.

Projection of land susceptibility to subsidence hazard in China using an interpretable CNN deep learning model

Land subsidence is a worldwide geo-environmental hazard. Clarifying the influencing factors of land subsidence hazards susceptibility (LSHS) and their spatial distribution are critical to the prevention and control of subsidence disasters. In this study, we selected natural and anthropogenic features or variables on LSHS and used the interpretable convolutional neural network (CNN) method to successfully construct a LSHS model in China. The model performed well, with AUC and F1-score testing set accuracies reaching 0.9939 and 0.9566, respectively. The interpretable method of SHapley Additive exPlanations (SHAP) was use to elucidate the individual contribution of input features to the predictions of CNN model. The importance ranking of model variables showed that population, gross domestic product (GDP) and groundwater storage (GWS) change are the three major factors that affect China's land subsidence. During year 2004–2016, an area of 237.6 thousand km2 was classified as high and very high LSHS, mainly concentrated in the North China Plain, central Shanxi, southern Shaanxi, Shanghai and the junction of Jiangsu and Zhejiang. There will be 333.82–343.12 thousand km2 of areas located in the high and very high LSHS in the mid-21st century (2030–2059) and 361.9–385.92 thousand km2 of areas in the late-21st century (2070–2099). Future population exposure to high and very high LSHS will be 252.12–270.19 million people (mid-21st century) and 196.14–274.50 million people (late-21st century), respectively, compared with the historical exposure of 210.99 million people. The proportion of future railway and road exposure will reach 14.63 %–14.89 % and 11.51 %–11.82 % in the mid-21st century, and 15.46 %–17.12 % and 12.35 %–13.11 % in the late-21st century, respectively. Our findings provide an important information for creating regional adaptation policies and strategies to mitigate damage induced by subsidence.

Historical evaluation and future projections of compound heatwave and drought extremes over the conterminous United States in CMIP6 * *Notice: This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). Accordingly, the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide

Independently, both droughts and heatwaves can induce severe impacts on human and natural systems. However, when these two climate extremes occur concurrently in a given region, their compound impacts are often more pronounced. With the improvement in both the spatiotemporal resolution and representation of complex climate processes in the global climate models (GCMs), they are increasingly used to study future changes in these extremes and associated regional impacts. However, GCM selection for such impact assessments is generally based on historical performance and/or future mean changes, without considering individual or compound extremes. In contrast, this study evaluates historical performance and projected changes in heatwaves, droughts, and compound heatwave-droughts using an ensemble of GCMs from the latest Phase 6 of Coupled Models Intercomparison Project at a regional scale across the conterminous United States. Additionally, we explore the inter-model differences in the projected changes that are associated with various characteristics of extremes and the choice of drought indices. Our analysis reveals considerable variation among the GCMs, as well as substantial differences in the projected changes based on the choice of drought indices and region of interest. For example, the projected increases in both the frequency and intensity of drought and associated compound extreme days, based on the standardized precipitation evapotranspiration index far exceed those derived from the standard precipitation index. Further, the largest changes in the frequency of compound extremes are projected over the Southwest, South Central, and parts of the Southeast while the smallest changes are projected over the Northeast. Overall, this study provides important insights for the interpretation and selection of GCMs for future assessment studies that are crucial for the development of regional adaptation strategies in the face of climate change.