Shared Socioeconomic Pathways Research Articles

Increased policy ambition is needed to avoid the effects of climate change and reach carbon removal targets in Portugal

The Paris Agreement’s goal of limiting global warming hinges on forest carbon sequestration as a key in several national strategies. However, Portugal’s rising forest fire occurrences threaten its ability to meet ambitious 2030 and 2050 carbon sequestration targets. Considering fire and forest trends, this study aims to quantify whether Portugal can reach its carbon sequestration ambitions as stated in its 2030 and 2050 targets. We tested three national forest scenario extensions of the global Shared Socioeconomic Pathways (SSPs) and Shared Policy Assumptions (SPAs) based on a dynamic model, simulating forest area and carbon sequestration related to future fire risk and policies of fire management, forest management, restoration of burnt areas, and climate change adaptation. The model projects a rapidly decreasing forest area under existing Portuguese policies (PT-SSP3), a slow decline under moderate policy improvements (PT-SSP2), and an almost stable forest area under long-term sustainable policy developments (PT-SSP1). In PT-SSP3, carbon sequestration will be reduced to 60% by 2050 compared to 2015, while it declines to about 85% and 90% under PT-SSP2 and PT-SSP1, respectively. It is still plausible to reach Portugal’s 2030 sequestration obligations under the EU’s Paris Agreement target under all three scenarios, while the Portuguese GHG neutrality target is not reached in the presented scenarios. Our four introduced policy areas (increasing focus on fire and forest management, forest restoration, and climate change adaptation of forest stands) must be supplemented by other policy strategies, such as reforestation.

Assessing future changes in flood frequencies under CMIP6 climate projections using SWAT modeling: a case study of Bitlis Creek, Turkey

ABSTRACT Climate change is altering flood risk globally, with local variations prompting the necessity for regional assessments to guide the planning and management of water-related infrastructures. This study details an integrated framework for assessing future changes in flood frequencies, using the case of Bitlis Creek (Turkey). The precipitation and temperature simulations of 21 global circulation models (GCMs) from the coupled model intercomparison project phase 6 (CMIP6) are used to drive the developed soil and water assessment tool (SWAT) model in generating daily streamflow projections under the CMIP6 historical experiment and the shared socio-economic pathway (SSP) scenarios of SSP245 and SSP585. Five probability distribution functions are considered to calculate the 5-, 10-, 25-, 50-, 100-, and 500-year flood discharges for the historical period 1955–2010 and the future periods 2025–2074 and 2025–2099. The quantification of climate change impacts on the design discharges is based on the medians of the flood discharges obtained for the climate data of each GCM, using the best-fitted distribution functions. The findings illustrate significant increases in discharge rates, ranging from 21.1 to 31.7% for the 2025–2099 period under the SSP585 scenario, highlighting the necessity of considering changing climate conditions in designing water-related infrastructures.

Assessment of Climate Change-Induced Water Scarcity Risk by Using a Coupled System Dynamics and Bayesian Network Modeling Approaches

AbstractThe water scarcity risk induced by climate change is contributing to a sequence of hydrological and socioeconomic impacts. Certain numbers of related impacts are locked in already and are expected to be much greater in the future. So, there is still a lack of understanding of its dynamics, origin, propagation, and the mutual interaction of its drivers. In recent years, several model-based approaches have been introduced to tackle the complexity, dynamics, and uncertainty of water scarcity specifically. However, the coupled modeling while addressing different aspects of the risk of water scarcity under the climate change scenarios has been rarely done. For bridging this gap, in this research, the combination of complementary System Dynamics modeling and Bayesian Network was applied to Qazvin Plain in Iran with five AOGCM models under two Shared Socioeconomic Pathways (SSP) scenarios (126 and 585). Key findings of this research show: 1) Baseline risk assessment indicates a low probability of water scarcity; however, in the future 30-year time horizon with continuous change in hazard, vulnerability, and exposure for SSP126, the risk fell in the extreme category with an average probability of 41%. Under SSP585, the risk varies between extreme and high categories with an average probability of 47%. 2) Economic development, particularly regional gross domestic product (RGDP) in 2045–2054 in SSP585 can diminish the negative projected consequences of climate change and therefore investments in adaptation policies could offset negative consequences, highlighting the role of economic growth in climate resilience. 3) It is projected that crop yield and income will receive the largest negative effects due to cutting back the agriculture area. 4) Considering the interplay of climate change, economic development, and water extraction policies is essential for the design, operation, and management of water-related activities. The proposed integrated methodology provides a comprehensive framework for understanding climate change-induced water scarcity risks, their drivers, and potential consequences. This approach facilitates adaptive decision-making to address the evolving challenges posed by climate change.

G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies

Abstract. The Geoengineering Model Intercomparison Project (GeoMIP) has proposed multiple model experiments during phases 5 and 6 of the Climate Model Intercomparison Project (CMIP), with the latest set of model experiments proposed in 2015. With phase 7 of CMIP in preparation and with multiple efforts ongoing to better explore the potential space of outcomes for different solar radiation modifications (SRMs) both in terms of deployment strategies and scenarios and in terms of potential impacts, the GeoMIP community has identified the need to propose and conduct a new experiment that could serve as a bridge between past iterations and future CMIP7 experiments. Here we report the details of such a proposed experiment, named G6-1.5K-SAI, to be conducted with the current generation of scenarios and models from CMIP6 and clarify the reasoning behind many of the new choices introduced. Namely, compared to the CMIP6 GeoMIP scenario G6sulfur, we decided on (1) an intermediate emission scenario as a baseline (the Shared Socioeconomic Pathway 2-4.5), (2) a start date set in the future that includes both considerations for the likelihood of exceeding 1.5 °C above preindustrial levels and some considerations for a likely start date for an SRM implementation, and (3) a deployment strategy for stratospheric aerosol injection that does not inject in the tropical pipe in order to obtain a more latitudinally uniform aerosol distribution. We also offer more details regarding the preferred experiment length and number of ensemble members and include potential options for second-tier experiments that some modeling groups might want to run. The specifics of the proposed experiment will further allow for a more direct comparison between results obtained from CMIP6 models and those obtained from future scenarios for CMIP7.

A Spatiotemporal Assessment of the Precipitation Variability and Pattern and an Evaluation of the Predictive Reliability of Global Climate Models over Bihar

Climate change is significantly altering precipitation patterns, leading to spatiotemporal changes throughout the world. In particular, the increased frequency and intensity of extreme weather events, leading to heavy rainfall, floods, and droughts, have been a cause of concern. A comprehensive understanding of these changes in precipitation patterns on a regional scale is essential to enhance resilience against the adverse effects of climate change. The present study, focused on the state of Bihar in India, uses a long-term (1901–2020) gridded precipitation dataset to analyze the effect of climate change. Change point detection tests divide the time series into two epochs: 1901–1960 and 1961–2020, with 1960 as the change point year. Modified Mann–Kendall (MMK) and Sen’s slope estimator tests are used to identify trends in seasonal and annual time scales, while Centroidal Day (CD) analysis is performed to determine changes in temporal patterns of rainfall. The results show significant variability in seasonal rainfall, with the nature of pre-monsoon and post-monsoon observed to have flipped in second epoch. The daily rainfall intensity during the monsoon season has increased considerably, particularly in north Bihar, while the extreme rainfall has increased by 60.6 mm/day in the second epoch. The surface runoff increased by approximately 13.43% from 2001 to 2020. Further, 13 Global Climate Models (GCMs) evaluate future scenarios based on Shared Socioeconomic Pathways (SSP) 370 and SSP585. The suitability analysis of these GCMs, based on probability density function (PDF), monthly mean absolute error (MAE), root mean square error (RMSE) and percentage bias (P-Bias), suggests that EC-Earth3-Veg-LR, MIROC6, and MPI-ESM1-2-LR are the three best GCMs representative of rainfall in Bihar. A Bayesian model-averaged (BMA) multi-model ensemble reflects the variability expected in the future with the least uncertainty. The present study’s findings clarify the current state of variability, patterns and trends in precipitation, while suggesting the most appropriate GCMs for better decision-making and preparedness.

Quantifying the environmental impact of structural timber across multiple future lifecycles

The pressing challenge of reducing human-induced environmental and climate impacts requires a massive transformation in the construction sector, a major contributor to energy consumption and CO2 emissions. The potential for implementing circular strategies in construction is increasingly supported by current standards and reports. Emerging technologies, like cross-laminated reclaimed timber, render cascading options potentially comparable to direct reuse. Simultaneously, wood possesses a high heating value, meaning that incineration remains a competitive alternative to recycling seen from a contemporary market perspective. This study seeks to identify the most environmentally beneficial end-of-life strategy for structural timber elements under diverse future scenarios, taking into account systemic changes occurring over time. It introduces novelty by combining elements that are relevant to this context: (1) the circular economy of timber; (2) structural calculations accounting for material quality and losses; (3) dynamic prospective life-cycle assessments (LCAs); and (4) matching different circular-economy strategies with compatible future scenarios suggested by the Shared Socioeconomic Pathways (SSPs) mentioned in the IPCC’s sixth assessment report. The results indicate that the reuse of timber is beneficial only when there is no need for additional steel brackets, underscoring the importance of a meticulous definition of the unit with all adjoining structures to ensure accurate and appropriate results. Furthermore, the cascading options are valuable primarily in preserving the high performance of the element during its subsequent use.

Improving the statistical downscaling performance of climatic parameters with convolutional neural networks

Abstract This study examines two downscaling techniques, convolutional neural networks (CNNs) and feedforward neural networks for predicting precipitation and temperature, alongside statistical downscaling as a benchmark model. The daily climate predictors were extracted from the European Center for Medium-range Weather Forecast (ECMWF) ERA5 dataset spanning from 1979 to 2010 for Tabriz city, located in the northwest of Iran. The biases in precipitation data of ERA5 predictors were corrected through the empirical quantile mapping method. Also, two nonlinear predictor screening methods, random forest and mutual information, were employed, alongside linear correlation coefficient. While these methods facilitate identification of dominant regional climate change drivers, it is essential to consider their limitations, such as sensitivity to parameter settings, assumptions about data relationships, potential biases in handling redundancy and correlation, challenges in generalizability across datasets, and computational complexity. Evaluation results indicated that CNN, when applied without predictor screening, achieves coefficient of determination of 0.98 for temperature and 0.71 for precipitation. Ultimately, future projections were employed under two shared socioeconomic pathways (SSPs), SSP2-4.5 and SSP5-8.5, and concluded that the most increase in temperature by 2.9 °C and decrease in precipitation by 3.5 mm may occur under SSP5-8.5.

Projected changes in rainfall and temperature using CMIP6 models over the Okavango River basin, southern Africa

AbstractThe Okavango River Basin (ORB) which includes a renowned World Heritage site Okavango Delta, contains highly biodiverse ecosystems. Most of its rural population relies on rain-fed subsistence farming. Limited research has been done on future changes in rainfall and temperature in this region. Here, such changes are analysed for the periods 2030–2059 (near term) and 2070–2099 (long term), relative to the historical period 1985–2014. The analysis is based on the Coupled Model Intercomparison Project Phase 6 (CMIP6), under the shared socioeconomic pathways (SSPs) SSP245 and SSP585. The projected changes vary over the ORB. For rainfall, the models project some significant decreasing trends over Ngamiland in the central/southern ORB, but none are significant over the northern ORB. The significant trends during the near term period include those projected by the model average (-30.60 mm/decade) in March–April (MA) under the SSP585 scenario. Some significant decreasing rainfall trends have also been found in December-February (DJF), but none are significant in October–November (ON). DJF is the main growing season whereas ON (MA) is the onset (end) of the rainy season. For temperature, significant warming trends have been found over both Ngamiland and the northern ORB, with the strongest warming in ON particularly during the near term period. For this ON season over the northern ORB, under the SSP585 (SSP245) scenario, the model average projects a warming trend of 0.56 °C/decade (0.67 °C/decade). These findings may help with the management of agricultural activities, water resources and the highly biodiverse ecosystems in the ORB.

Predicting Current and Future Habitat Suitability of an Endemic Species Using Data-Fusion Approach: Responses to Climate Change

Fritillaria imperialis L., an indicator plant species in Iran, is facing threats and its population has declined in recent years. To provide insights into the drivers affecting its loss, this research aims to identify the effects of three groups of factors, including climate, soil, and physiographic variables, on the current and future spatial distributions of F. imperialis. For this purpose, we used five machine learning algorithms as well as an ensemble forecasting of species distribution approach to explain the geographical distributions of the species as a function of these factors. In addition, we used two shared socio-economic pathways scenarios – SSP 1-2.6 and SSP 5-8.5 – to project the future distributions of F. imperialis in 2030, 2050, 2070, and 2090. Based on evaluation indices, area under the ROC curve (AUC) and true skill statistic (TSS), the Random Forest (RF) model generated the strongest prediction of the distribution of F. imperialis (TSS>0.9 and AUC>0.9). No significant difference observed among the three datasets (climate-only variables, climate + physiography variables, and climate + physiography + soil variables) in terms of AUC values. In models using climate + physiography + soil datasets, soil electrical conductivity, clay, and pH emerged as the most important variables affecting the growth and development of F. imperialis while climate factors played a lesser role in its distribution. Future projections revealed different patterns when using the optimistic (SSP 1-2.6) and pessimistic (SSP 5-8.5) socio-economic pathway scenarios and either the climate only or climate + physiography models. The climate + physiography + soil model produced similar prediction patterns for the scenarios. The climate-only models predicted larger areas suitable for crown imperial in the future than did the climate + physiography + soil model. These results emphasize the consideration of factors beyond climate scenarios when modeling biological responses to global warming and regional climate change.

Climate change exacerbates the compounding of heat stress and flooding in the mid‐latitudes

AbstractHeat stress and flood impacts have been extensively studied separately because of their significant societal and economic impacts, albeit apart from each other. Here we show that heat stress can trigger floods across large areas of North and South America, southern Africa, Asia and eastern Australia. We also show that the compounding of heat stress and floods is projected to worsen under climate change. This effect is magnified as we move from the Shared Socioeconomic Pathways (SSPs) 1–2.6 to 5–8.5. Moreover, in the future, the compounding between heat stress and floods is projected to extend to Europe and Russia, two areas where it has not been identified as relevant in the past. Moreover, by intersecting our results with future projections of the population of urban agglomerations, we find that heat stress/flood compound can pose a serious risk to a large portion of the world population. These results highlight the need towards improved preparation and mitigation measures that account for the compound nature of heat stress and flooding, and how the compounding is expected to be exacerbated because of climate change.

Alterations in Hydrological Responses under Changing Climate and Land Use/Land Cover across Contrasting Agroecological Environments: A Case Study on the Chemoga Watershed in the Upper Blue Nile Basin, Ethiopia

We analyzed hydrological responses to changing climate and land use/land cover (LULC) for the past (1985–2020) and future (2021–2080) in the Chemoga watershed of the Upper Blue Nile Basin. The watershed comprises four agroecological environments: Moist Kolla, Moist Weyna Dega, Moist Dega, and Wet Wurch. Past and projected LULC changes under business-as-usual (BAU) and land conservation (LC) scenarios were utilized. Climate projections from 2021 to 2080, under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5), were downscaled from Global Climate Models. Utilizing the Soil and Water Analysis Tool, we assessed impacts on mean annual surface runoff (SR) and evapotranspiration (ET). Maximum and minimum temperatures increased significantly in the past and future climate scenarios, with a significant rainfall increase observed under SSP5-8.5. Historical trends revealed a 16.6% increase in SR and 7% in ET from 1983–2002 to 2003–2020. Under BAU LULC with the SSP2-4.5 (SSP5-8.5) climate scenario, SR increased by 24% (26.1%) and ET by 3.1% (4.4%) from 2003–2020 to 2021–2050, followed by a subsequent SR rise of 13.7% (14.0%) and ET increase of 6.0% (5.7%) from 2021–2050 to 2051–2080. Conversely, the LC LULC with SSP2-4.5 (SSP5-8.5) resulted in a 5.3% (4.2%) SR decrease and ET increase of 9.7% (11.3%) from 2003–2020 to 2021–2050 and a further SR decrease of 1% (0.7%) and 6.1% (6.9%) ET increase from 2021–2050 to 2051–2080. The Moist Kolla agroecology experienced the highest SR increase due to vegetation clearances for commercial farming. Meanwhile, the LC scenario indicated substantial decreases in SR and marginal increases in ET in the Moist Weyna Dega agroecology due to forest restoration on steep slopes. Overall, SR showed greater sensitivity to LULC changes, while ET was more responsive to climate changes. The results emphasize considering diverse agroecological contexts for effective water resource management under changing climate and LULC scenarios.

Acceleration of daily land temperature extremes and correlations with surface energy fluxes

Assessment of climate reanalysis data for land (ECMWF Re-Analysis v5; ERA5-Land) covering the last seven decades reveals regions where extreme daily mean temperatures are rising faster than the average rate of temperature rise of the 6 months of highest background warmth. However, such extreme temperature acceleration is very heterogeneous, occurring only in some places including regions of Europe, the western part of North America, parts of southeast Asia and much of South America. An ensemble average of Earth System Models (ESMs) over the same period also shows acceleration across land areas, but this enhancement is much more spatially uniform in the models than it is for ERA5-Land. Examination of projections from now to the end of the 21st Century, with ESMs driven by the highest emissions Shared Socio-economic Pathway scenario (SSP585) of future changes to atmospheric greenhouse gases, also reveals larger warming during extreme days for most land areas. The increase in high-temperature extremes is driven by different processes depending on location. In northern mid-latitudes, a key driver is often a decrease in the evaporative fraction of the available energy, consistent with soil drying. By contrast, the acceleration of high-temperature extremes in tropical Africa is primarily due to increased available energy. These two drivers combine via the surface energy balance to equal the sensible heat flux, which we find is often strongly correlated with the areas where the acceleration of high-temperature extremes is largest.

Projecting Global Mercury Emissions and Deposition Under the Shared Socioeconomic Pathways

AbstractMercury (Hg) is a naturally occurring element that has been greatly enriched in the environment by human activities like mining and fossil fuel combustion. Despite commonalities in some carbon dioxide (CO2) and Hg emission sources, the implications of long‐range climate scenarios for anthropogenic Hg emissions have yet to be explored. Here, we present comprehensive projections of anthropogenic Hg emissions extending to the year 2300 and evaluate impacts on global atmospheric Hg deposition. Projections are based on four Shared Socioeconomic Pathways (SSPs) ranging from sustainable reductions in resource and energy intensity to rapid economic growth driven by abundant fossil fuel exploitation. There is a greater than two‐fold difference in cumulative anthropogenic Hg emissions between the lower‐bound (110 Gg) and upper‐bound (235 Gg) scenarios. Hg releases to land and water are approximately six times those of direct emissions to air (600–1,470 Gg). At their peak, anthropogenic Hg emissions reach 2,200–2,600 Mg a−1 sometime between 2010 (baseline) and 2030, depending on the SSP scenario. Coal combustion is the largest determinant of differences in Hg emissions among scenarios. Decoupling of Hg and CO2 emission sources occurs under low‐to mid‐range scenarios, though contributions from artisanal and small‐scale gold mining remain uncertain. Future Hg emissions may have lower gaseous elemental Hg (Hg0) and higher divalent Hg (HgII), resulting in a higher fraction of locally sourced Hg deposition. Projected reemissions of previously deposited anthropogenic Hg follow a similar temporal trajectory to primary emissions, amplifying the benefits of primary Hg emission reductions under the most stringent mitigation scenarios.

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.

Projections of Aedes and Culex mosquitoes across North and South America in response to climate change

IntroductionClimate and land use change may cause the geographical range of mosquitoes to expand, shift, or contract, ultimately changing what communities are at risk for contracting mosquito-borne diseases. Across North and South America, mosquitoes from the Aedes and Culex genera are vectors for numerous diseases, including chikungunya, dengue, various equine encephalitis viruses, Saint Louis encephalitis virus, West Nile virus, yellow fever virus, and Zika virus. The goal of our study was to project the geographical distributions of important mosquito vectors across North and South America in response to climate change, which is important to inform public health planning. MethodsWe used an ecological niche model and future projections of climate and land use to project the geographical ranges of two Aedes species (Ae. aegypti, Ae. albopictus) and seven Culex species (Cx. erraticus, Cx. nigripalpus, Cx. pipiens, Cx. quinquefasciatus, Cx. restuans, Cx. salinarius, Cx. tarsalis) over North and South America in response to both a high (Shared Socioeconomic Pathway [SSP] 5, Representative Concentration Pathway [RCP] 8.5) and moderate (SSP2 RCP4.5) climate warming scenario through years 2050 and 2090. ResultsFor SSP5 RCP8.5, six species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus, Cx. restuans) are projected to expand in geographical range, two species (Cx. pipiens, Cx. tarsalis) are projected to shift in geographical range, and one species (Cx. salinarius) is projected to nearly remain the same. Five species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus) show the largest increase in high habitat suitability (>0.5 on a 0–1 scale) for SSP5 RCP8.5, three species (Cx. pipiens, Cx. restuans, Cx. tarsalis) show the largest increase for SSP2 RCP4.5, and one species (Cx. salinarius) shows a relatively small decrease in response to both scenarios. ConclusionsWe found that all nine species responded resiliently to climate change under both the high and moderate climate warming scenario, suggesting mosquito-borne disease is likely to be a continued threat in response to climate change. The projected geographical ranges can be used to inform disease risk analyses and mitigation strategies in response to climate change.

Adaptation measures to global change in the Serpis River Basin (Spain): An evaluation considering agricultural benefits, environmental flows, and invasive fishes

Damming and flow regulation ensure water availability during dearth periods, but they cause impacts on inhabiting biota and facilitate the establishment of Invasive Alien Species (IAS). Setting environmental flows (e-flows) has proven fundamental to ensure good ecological status of rivers, battle IAS, and sustain ecosystem services. However, ongoing climate change is further straining water resources availability and the fulfilment of e-flows in Spain, which has compelled River Basin Management Plans (RBMPs) to include specific adaptation measures. In this study, we assessed adaptation strategies addressing land use and climate change in the Serpis River (Eastern Spain), based on increasing irrigation efficiency (i.e. moving from gravity to drip irrigation). The evaluation considered two CMIP6 climate change scenarios (Shared Socioeconomic Pathways SSP1-2.6 and SSP5-8.5) for two time horizons (short term 2015–2040 and mid-term 2041–2070), together with three land use change scenarios (changes in irrigated areas and technologies). Future estimations included reservoir flow releases, e-flows fulfilment, agricultural benefits, and changes in the suitable habitat and potential competition for two native (Eastern Iberian chub Squalius valentinus and European eel Anguilla anguilla) and two invasive (common bleak Alburnus alburnus and pumpkinseed Lepomis gibbosus) fish species. Predictions indicated a decrease in the suitable habitat for eel and Eastern Iberian chub, but the established e-flows will be ensured. Although the maximum benefits will rarely be achieved, on average the modernisation expected in the RBMP would sustain agricultural incomes in the optimistic scenario (SSP1-2.6) and for the short term of the pessimistic scenario (SSP5-8.5), showing similar effects than the ongoing redistribution of agricultural plots. Habitat and competition with invasive species will experience little changes due to the strong flow regulation, although the invasive bleak would prevail in the mid-term of the most pessimistic scenario. These results highlight the necessity of proactive adaptation measures beyond those described in the RBMPs (e.g. forest management or crop substitution) to increase water availability and sustain agricultural benefits, in particular for the most pessimistic scenario. They also underscore the difficulties to counteract invasive species through streamflow management under water scarcity scenarios.

Simulated Abrupt Shifts in Aerobic Habitats of Marine Species in the Past, Present, and Future

AbstractThe physiological tolerances of marine species toward ambient temperature and oxygen can jointly be evaluated in a single metric: the metabolic index. Changes therein characterize a changing aerobic habitat tailored to species‐specific thermal and hypoxia sensitivity traits. If the geographical limits of marine species as indicated by critical thresholds of the metabolic index shift abruptly in response to ocean warming and deoxygenation, aerobic habitat could potentially be lost abruptly. Here, we assess the spatio‐temporal detectability of abrupt shifts in potential habitats for selected marine species within the Shared Socioeconomic Pathway 5–8.5 (SSP5‐8.5) scenario run with the fully coupled Norwegian Earth System Model version 2 (NorESM2‐LM). We use an environmental time series changepoint detection routine and analyze the number and timing of these abrupt changes over the past, present and future. We construct nine ecophysiotypes with low, medium, and high resting vulnerability to hypoxia and sensitivity of hypoxia vulnerability to temperature, respectively, with six different thresholds for minimal oxygen demand. For all ecophysiotypes with positive temperature sensitivity to hypoxia, the volume of non‐viable habitat in the upper ocean expands between 1850 and 2100. Changepoints in the metabolic index are detected in 49.0 ± 9.2% of the volume that eventually becomes non‐viable for all ecophysiotypes over the course of the 21st century. More than 75% of these abrupt shifts occur in response to warming close to the surface, while at depth, the abrupt shifts driven by changes in oxygen partial pressure become more important, with potentially severe consequences for marine species, populations, and ecosystems.

Climate change projection using statistical downscaling model over southern coastal Iran

Iran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply to address the challenges posed by future climate change. Over the next two to three decades, the effects of climate change, such as precipitation and temperature, are expected to worsen, posing greater risks to water resources, agriculture, and infrastructure stability. Therefore, this study aims to evaluate the alterations in mean daily temperature (Tmean) and total daily rainfall (rrr24) utilizing climate change scenarios from both phases 5 and 6 of the Coupled Model Inter-comparison Project (CMIP5 and CMIP6, respectively) in the southern coastal regions of Iran (Hormozgan province), specifically north of the Strait of Hormuz. The predictions were generated using the Statistical Downscaling Model (SDSM) and National Centre for Environmental Prediction (NCEP) predictors, incorporating climate change scenarios from CMIP5 with Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 and CMIP6 with Shared Socioeconomic Pathways (SSPs) 1, 2, and 5. The analysis was conducted for three distinct time periods: the early 21st century (2021–2045), middle 21st century (2046–2071), and late 21st century (2071–2095). The results indicated that the CMIP5 model outperformed the CMIP6 model in simulating and predicting Tmean and rrr24. In addition, a significant increase in Tmean was observed across all the scenarios and time periods, with the most pronounced trend occurring in the middle and late 21st century future periods. This increase was already evident during the base period of 2021–2045 across all scenarios. Moreover, the fluctuations in precipitation throughout the region and across all scenarios were significant in the three examined future periods. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of Tmean (+1.22 °C) in Bandar Lengeh station in 2071–2095 period. The lowest change magnitude of Tmean among CMIP5 scenarios was found in RCP4.5 (−1.94 °C) in Ch station in 2046–2070 period. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of rrr24 (+150.2 mm) in Chabahar station in 2071–2095 period. The lowest change magnitude of rrr24 among CMIP5 scenarios was found in RCP8.5 (−25.8 mm) in Bandar Abbas station in 2046–2070 period. In conclusion, the study reveals that the coastal area of Hormozgan province will experience rising temperatures and changing rainfall patterns in the future. These changes may lead to challenges such as increased water and energy consumption, heightened risks of droughts or floods, and potential damage to agriculture and infrastructure. These findings offer valuable insights for implementing local mitigation policies and strategies and adapting to emerging climate changes in Hormozgan's coastal areas. For example, utilizing water harvesting technologies, implementing watershed management practices, and adopting new irrigation systems can address challenges like water consumption, agricultural impacts, and infrastructure vulnerability. Future research should accurately assess the effect of these changes in precipitation and temperature on water resources, forest ecosystems, agriculture, and other infrastructures in the study area to implement effective management measures.

Significant Reduction of Unequal Population Exposure to Climate Extremes by Achieving the Carbon Neutrality

AbstractClimate extremes, such as hot temperature and heavy precipitation events, have devastating effects on human societies. As the planet gets warmer, they have become more intense and more frequent. To avoid irreversible damages from climate extremes, many countries have committed to achieving net‐zero anthropogenic carbon emissions, or carbon neutrality, by the 2050s. Here, we quantify the impact of carbon neutrality on population exposure to climate extremes using multi‐model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP)1‐1.9 and SSP3‐7.0 scenarios. It is found that the increasing population exposure to hot‐temperature and heavy‐precipitation extremes under SSP3‐7.0 scenario can be substantially reduced by 87%–98% in the late 21st century by achieving the carbon neutrality based on SSP1‐1.9 scenario. The benefits of carbon neutrality are particularly pronounced in Africa and Asia. The potential benefits of carbon neutrality are also significant in North America, Europe, and Oceania, where a reduction in climate extremes is more than twice as important as population decline in reducing population exposure to climate extremes. These results provide important scientific support for ongoing efforts to achieve net‐zero carbon emissions by the 2050s to reduce potential climate risk and its inequity across continents.

Projected climatic drought events in drought-prone cities: Insights from high-resolution downscaled CMIP6 data

This study investigated the drought trends, frequency, and duration in three drought-prone cities in Northwest China under various Shared Socioeconomic Pathways (SSPs) climate scenarios from 2015 to 2099. Utilizing a two-step downscaling method, we generated high-resolution (1 km) temperature and precipitation projections for the cities using multiple global climate model (GCM) data. The Standardized Precipitation Evapotranspiration Index (SPEI) was then calculated to assess drought conditions. Our results revealed that under the influence of global climate change, the 12-month SPEI exhibited a significant increasing trend for all three cities, indicating a shift towards a more humid climate. The influence of climate change on drought trends was more pronounced at higher latitudes. Additionally, the occurrence and duration of severe droughts (3-month SPEI < -1.5) were higher in the near future (2015–2056) compared to the far future (2057–2099), suggesting time-lagged and cumulative effects of global climate change on drought. Spatial variations within each city were also observed, with the western mountainous regions of Xi'an showing a more pronounced decrease in drought frequency under higher emission scenarios. Under the influence of different projected scenarios, the variations in drought characteristics across cities exhibited significant spatial heterogeneity. This study highlights the importance of understanding local and inter-regional drought characteristics in the context of climate change, and the need for targeted management policies to effectively cope with climate anomalies and associated disasters in different regions.