Shared Socioeconomic Pathways Research Articles

Controlling factors of wildfires in Australia and their changes under global warming

Abstract This study investigates a fire weather index (FWI) and its associated components in Australia using the downscaled projects for the Coupled Model Intercomparison Project phase 6 (CMIP6) dataset, aiming to understand how they respond to global warming, particularly associated with different phases of the El Niño-Southern Oscillation (ENSO). In the historical simulation, multimodel mean composite results show positive anomalies of FWI during El Niño and negative anomalies during La Niña over most of Australia relative to the neutral year. At the end of the 21st century under the Shared Socioeconomic Pathways (SSP585 scenario), FWI anomalies increased across Australia; however, ENSO wildfire teleconnections weakened (-4.4%) during El Niño but strengthened (+6.0%) during La Niña, especially in northern Australia. Further examination of the contribution from individual environmental variables that enter the FWI shows that increased temperature and drought conditions with warming in La Niña strengthen positive FWI anomalies, thus making fire more favorable in north and central Australia. The impacts of relative humidity and wind speed anomaly changes also favor fire activity toward the north. These results suggest a more robust modulation of FWI in northern Australia by ENSO in a warmer climate; future efforts to predict wildfire will depend on the model’s ability to predict local climate conditions.

CMIP6-based global estimates of future aridity index and potential evapotranspiration for 2021-2060

The “Future Global Aridity Index and PET Database” provides high-resolution (30 arc-seconds) average annual and monthly global estimates of potential evapotranspiration (PET) and aridity index (AI) for 22 CMIP6 Earth System Models for two future (2021-2041; 2041-2060) and two historical (1960-1990; 1970–2000) time periods, for each of four shared socio-economic pathways (SSP). Three multimodel ensemble averages are also provided (All; Majority Consensus, High Risk) with different level of risks linked to climate model uncertainty. An overview of the methodological approach, geospatial implementation and a technical evaluation of the results is provided. Historical results were compared for technical validation with weather station data (PET: r 2 = 0.72; AI: r 2 = 0.91) and the CRU_TS v 4.04 dataset (PET: r 2 = 0.67; AI: r 2 = 0.80). Within the context of projected significant change in the near- and medium-term, the “Future_Global_AI_PET Database” provides a set of data projections and tools available for a variety of scientific and practical applications, illustrating trends and magnitude of predicted climatic and eco-hydrological impacts on terrestrial ecosystems. The Future_Global_AI_PET Database is archived in the ScienceDB repository and available online at: https://doi.org/10.57760/sciencedb.nbsdc.00086

Intercomparison of deep learning models in predicting streamflow patterns: insight from CMIP6

This research was carried out to predict daily streamflow for the Swat River Basin, Pakistan through four deep learning (DL) models: Feed Forward Artificial Neural Networks (FFANN), Seasonal Artificial Neural Networks (SANN), Time Lag Artificial Neural Networks (TLANN) and Long Short-Term Memory (LSTM) under two Shared Socioeconomic Pathways (SSPs) 585 and 245. Taylor Diagram, Random Forest, and Gradient Boosting techniques were used to select the best combination of General Circulation Models (GCMs) for Multi-Model Ensemble (MME) computation. MME was computed via the Random Forest technique for Maximum Temperature (Tmax), Minimum Temperature (Tmin), and precipitation for the aforementioned three techniques. The best MME for Tmax, Tmin, and precipitation was rendered by Compromise Programming. The DL models were trained and tested using observed precipitation and temperature as independent variables and discharge as dependent variables. The results of deep learning models were evaluated using statistical performance indicators such as root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). The TLANN demonstrated superior performance compared to the other models based on RMSE, MSE, MAE, and R2 during training (65.25 m3/s, 4256.97 m3/s, 46.793 m3/s and 0.7978) and testing (72.06 m3/s, 5192.95 m3/s, 51.363 m3/s and 0.7443) respectively. Subsequently, TLANN was utilized to make predictions based on MME of SSP245 and SSP585 scenarios for future streamflow until the year 2100. These results can be used for planning, management, and policy-making regarding water resources projects in the study area.

Quantifying future climate extreme indices: implications for sustainable urban development in West Africa, with a focus on the greater Accra region

Climate change leading to Climate extremes in the twenty-first century is more evident in megacities across the world, especially in West Africa. The Greater Accra region is one of the most populated regions in West Africa. As a result, the region has become more susceptible to climate extremes such as floods, heatwaves, and droughts. The study employed the Coupled Model Intercomparison Project 6 models in simulating climate extreme indices under the Shared Socioeconomic Pathway scenarios (SSPs) over West Africa between 1979 and 2059 as exemplified by the Greater Accra region. The study observed a generally weak drought in the historical period and expected to intensify especially under SSP585 in Greater Accra. For instance, continuous dry days (CDD) reveal an increasing trend under the SSPs. Similarly, the overall projected trend of CDD over West Africa reveals an increase signifying a more frequent and longer drought in the future. The flood indices revealed a surge in the intensity and duration of extreme precipitation events under the SSPs in the region. For instance, R99pTOT and Rx5days are expected to significantly increase under the SSPs with intensification under the SSP245, SSP370, and SSP585. A similar trend has been projected across West Africa, especially along the Guinean coast. The study foresees a gradual and intensifying rise in heatwave indices over the Greater Accra region. The warming and cooling indices reveal an increasing and decreasing trend respectively in the historical period as well as under the SSPs particularly within urban centers like Accra and Tema. Most West African countries are projected to observe more frequent warm days and nights with cold nights and days becoming less frequent. Expected effects of future climate extreme indices pose potential threats to the water, food, and energy systems as well as trigger recurrent floods and droughts over Greater Accra. The findings of the study are expected to inform climate policies and the nationally determined contribution of the Paris Agreement as well as address the sustainable development goal 11 (Sustainable cities) and 13 (Climate action) in West Africa.

Projected Increase in Heatwaves under 1.5 and 2.0 °C Warming Levels Will Increase the Socio-Economic Exposure across China by the Late 21st Century

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes.

Projected navigability of Arctic shipping routes based on climate model FIO-ESM v2.1

As Arctic sea ice has rapidly declined, the navigational potential of the Arctic routes has greatly increased. Based on sea ice output from the First Institute Of Oceanography-Earth System Model version 2.1 (FIO-ESM v2.1) and the Arctic Transport Accessibility Model, this study investigates the future navigability of the Arctic routes for open-water ships (OW) without icebreaking capabilities and ships with different icebreaking capabilities, namely Polar Class 7 (PC7), Polar Class 6 (PC6), and Polar Class 3 (PC3). The results show that the simulations of FIO-ESM v2.1 adequately reproduce the changes in the navigability of the four types of ships in Arctic shipping routes over the past 40 years. The navigable area for the four ship types is projected to continue to expand in the future. Under the high emission scenario (Shared Socioeconomic Pathways 5–8.5, SSP585), the four ship types are projected to achieve full Arctic navigability in summer (September) by the end of the 21st century, and PC6 and PC3 ships are projected to achieve full Arctic navigability in winter (March). Under the high emission scenario, year-round navigability in the Northwest Passage is projected for PC3 and PC6 ships, and in the Northeast Passage is projected for all four types of ships. The impact of emission scenario on the navigability of the Arctic shipping routes varies with different ship types: the largest impact is for OW ships, followed by PC6 and PC7 ships, and the smallest impact is for PC3 ships. The impact of scenario is also larger in winter than in summer.

Projecting Climate Change Impact on Precipitation Patterns during Different Growth Stages of Rainfed Wheat Crop in the Pothwar Plateau, Pakistan

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation.

Anthropogenic effects on tropical cyclones near Western Europe

There is less consensus on whether human activities have significantly altered tropical cyclone (TC) statistics, given the relatively short duration of reliable observed records. Understanding and projecting TC frequency change is more challenging in certain coastal regions with lower TC activity yet high exposure, such as Western Europe. Here, we show, with large-ensemble simulations, that the observed increase in TC frequency near Western Europe from 1966 to 2020 is likely linked to the anthropogenic aerosol effect. Under a future scenario featuring regionally controlled aerosol emissions and substantially increased greenhouse gas concentrations (Shared Socioeconomic Pathway 5-85), our simulations show a potential decrease in TC frequency near Western Europe by the end of the 21st century. These contrasting trends in historical and future TC frequencies are primarily due to the rise for 1966–2020 and potentially subsequent fall for 2030–2100 in TC genesis frequency in the North Atlantic. The response of large-scale environmental conditions to anthropogenic forcing is found to be crucial in explaining the historical and future changes in TC frequency near Western Europe.

Assessing the Potential Impacts of Climate Change on Drought in Uzbekistan: Findings from RCP and SSP Scenarios

Future climate change and its impact on drought is critical for Uzbekistan, located in Central Asia, the world’s largest arid zone. This study examines the evolving intensity of climate change and drought events using multi-model ensembles (MMEs) derived from the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5 and CMIP6) simulated under the Representative Concentration Pathway and Shared Socioeconomic Pathway (RCP and SSP) scenarios. The projections show different rates of increase in temperature and precipitation under the RCPs and SSPs. Projected temperature increases are expected to reach up to 2–2.5 °C under SSP1-2.6, SSP2-4.5, and SSP3-7.0, by mid-century. By 2080–2099, an increase is projected of 2–3 °C in monthly mean temperatures throughout the year (SSP1-2.6), and a more pronounced increase in summer up to 3–4 °C (SSP2-4.5) and 4–6 °C (SSP3-7.0), with a marked contrast in conditions between the mountainous and desert regions of Uzbekistan. Regional changes in precipitation over the study periods show relatively little variability, except for FD, where notable trends are found. Under SSP1-2.6 and SSP2-4.5, the increase in precipitation is relatively modest, whereas the changes in SSP3-7.0 are more substantial, with some regions experiencing variations of up to 10–20 mm per period. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated based on the projected temperature and precipitation, provides an estimate of future drought trends. Our results show increasing aridity under all scenarios by mid-century, with longer-term projections indicating stabilization around different SPEI values by 2100: RCP2.6 and SSP1-1.9 stabilize around −1.0; RCP4.5, RCP6.0, SSP2-4.5, and SSP3-7.0 stabilize around −1.5; while RCP8.5 and SSP5-8.5 scenarios project values of −2 or less by 2100. Notable differences in the SPEI index are found between lowland and foothill regions. In view of Uzbekistan’s heavy reliance on agriculture and irrigation, which are the sectors that are expected to be mostly affected by climate change, our study provides a scientific basis for informed policy decision-making. This includes various aspects such as planning and management water resources, as well as the broader socioeconomic development of the country.

Estimating terrestrial ecosystem carbon storage change in the YREB caused by land-use change under SSP-RCPs scenarios

Terrestrial ecosystems, as an essential carbon sink of atmospheric CO2, play an important role in balancing the global carbon cycle. Land-use and land-cover changes (LUCCs) are the major factors in terrestrial ecosystem carbon storage (TECS) change. However, they are not yet sure how future LUCCs would affect the TECS in the Yangtze River Economic Belt (YREB) to meet China's carbon-neutral goal. We simulated eight land-use change scenarios and used these to estimate the YREB's TECS and its 2020–2060 variation by coupling the spatially explicit projections of LUCCs under the latest IPCC, combining shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) with datasets on terrestrial ecosystem carbon density dataset. Results show that: 1) the total TECS of the YREB in 2020 is ∼28.07 Gt. Spatially, TECS in the YREB focused on Sichuan and Yunnan (∼13.35 Gt), which plays a crucial role in balancing the regional carbon cycle; its losses are in Jiangsu, Zhejiang, and Hunan provinces; Yunnan is the potential region with future carbon sink enhancement in the YREB. 2) Compared to the TECS change under eight land-use scenarios, the low-carbon and sustainable development pathways are the priority chosen by humans. 3) The replacement of vast forest land with cropland and urban expansion are the key factor of TECS change in the YREB. 4) Land management policies (i.e., Cultivated land requisition-compensation balance) should balance the conflicts between food self-sufficiency and the carbon sink rather than only the dynamic balance in quantity. Our study aims to provide data support for the government in planning future development pathways and refining carbon emission reduction strategies to assist in carbon trading and compensation and achieve the YREB's dual-carbon goal.

Forecasting Future Vegetation Dynamics under SSP/RCP Pathways under Spatially Changing Climate and Human Activities Conditions

Vegetation dynamics result from the interaction between human activities and climate change. Numerous studies have investigated the contributions of human activities and climate change to vegetation cover dynamics using statistical methods. However, these studies have not focused much on the spatially non-stationary effects of human activities on vegetation cover changes and future trends. Taking the Three Gorges Reservoir (TGR) area as the case study area, it was divided into 32 combinations by considering the spatially varying effects of five factors related to human activity and climate change, including gross domestic product (GDP), population, land use change, precipitation, and temperature. Regression in terms of pixels was then performed for each combination at the pixel scale. The result showed that from 2001 to 2020, the annual average normalized digital vegetation index (NDVI) in the TGR area exhibited an upward trend (slope = 0.0051, p < 0.01), with the mean NDVI increasing from 0.53 to 0.64. Compared with the regression with climate variables, the proposed model improved the R2 value from 0.2567 to 0.6484, with the p-value in the t-test reduced from 0.2579 to 0.0056. It indicated that changes in vegetation were dominated by human activities and climate change in 48.77% and 3.19% of the TGR area, respectively, and 43.70% of the vegetation coverage was dominated by both human activities and climate change. This study also predicted the future NDVI according to the shared socioeconomic pathways (SSPs) and representative concentration pathway (RCP) scenarios provided by the Intergovernmental Panel on Climate Change. It suggests that, assuming future regional policies are the same as the historical policies in the TGR, the SSP5–8.5 scenario would have the highest and fastest growth in average NDVI, with the average NDVI increasing from 0.68 to 0.89, because of the large increase in the GDP, lower population in this scenario, and adequate hydrothermal conditions.

Amplification of temperature extremes in Arabian Peninsula under warmer worlds

The Paris Agreement and the Special Report on Global Warming of 1.5 °C from the Intergovernmental Panel on Climate Change (IPCC) highlighted the potential risks of climate change across different global warming levels (GWLs). The increasing occurrence of extreme high-temperature events is linked to a warmer climate that is particularly prevalent in the Arabian Peninsula (AP). This study investigates future changes in temperatures and related extremes over AP, under four GWLs, such as 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C, with three different Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The study uses high-resolution datasets of 27 models from the NASA Earth Exchange Global Daily Downscaled Projections of the Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6). The results showed that the NEX-GDDP-CMIP6 individual models and their multi-model means reasonably captured the extreme temperature events. The summer maximum and winter minimum temperatures are projected to increase by 0.11–0.67 °C and 0.09–0.70 °C per decade under the selected SSPs. Likewise, the projected temperature extremes exhibit significant warming with varying degrees across the GWLs under the selected SSPs. The warm temperature extremes are projected to increase, while the cold extremes are projected to decrease under all GWLs and the selected SSPs. Overall, the findings provide a comprehensive assessment of temperature changes over AP in response to global warming, which can be helpful in the development of climate adaptation and mitigation strategies.

Assessing spatial thermal comfort and adaptation measures for the Antalya basin under climate change scenarios

The concrete damages of climate change are intensifying, and adaptation efforts of actors around the world are increasing, especially in coastal regions. Recommending adaptation measures for specific regions and sectors and determining long-term strategies for mitigating global climate change is essential for reducing vulnerability to climate change. This research aims to estimate the changes in climatic parameters and thermal comfort zones to determine concrete targets and offer suggestions for sectors affected by possible changes. The changes that will occur until 2100 in the Antalya basin, which is located in the southernmost part of Türkiye and is a significant hub for agricultural production and tourism, were monitored spatially using Discomfort Index (DI) and Effective Temperature taking wind velocity (ETv). The Shared Socioeconomic Pathways (SSP): SSP 245 and SSP 585 predict that the quite cool areas prevailing in the area, according to ETv, will shrink by 24% and 46%, respectively, and the prevailing cold areas, according to DI, will shrink by 45% and 56%, respectively. By 2100, 5% of the area, according to SSP 245, and 25%, according to SSP 585, will turn into hot areas and move away from the comfort level. The fact that critical regions are areas with high vitality in terms of coastal tourism shows the need to prioritize adaptation policies. These discoveries are discussed in the context of critical issues such as water scarcity and food security, contributing to policy-making for effective management by suggesting specific adaptation measures.

Net evaporation-induced mangrove area loss across low-lying Caribbean islands

Abstract Although mangroves provide many beneficial ecosystem services, such as blue carbon storage and coastal protection, they are currently under threat due to changes in climate conditions, such as prolonged drought exposure. Under drought conditions, evaporation exceeds precipitation increasing porewater salinity causing mangroves stunted growth and die-back. To quantify this interplay, we developed a database for low-lying and uninhabited mangrove islands in the Caribbean under various evaporation and precipitation regimes. We extracted physical and biological information from each island using remote sensing techniques and coupled it with a process-based model. We used this database to develop a model that explains both the spatial variability in vegetated area across the Caribbean – as a function of rates of evaporation and precipitation – and porewater salinity concentration and dispersion from island edge towards the interior of mangrove islands. We then used this validated model to predict mangrove area loss associated with increases in evaporation to precipitation rates by 2100 for different Shared Socioeconomic Pathways (SSP). Less wealthy Caribbean regions such as Belize, Puerto Rico, and Venezuela are disproportionally affected, with mangrove area losses ranging from 3-7% for SSP 2.6 and 13-21% for SSP 7.0. Furthermore, foregone carbon sequestration in lost biomass under SSP 4.5 and 7.0 scenarios could compromise the ability of low-lying Caribbean mangrove islands to vertically adjust to sea level rise.

Simulation and Prediction of Land Use Change and Carbon Emission under Multiple Development Scenarios at the City Level: A Case Study of Xi’an, China

Studying urban land use and its impact on carbon emissions is crucial for achieving China’s dual carbon goals. This research utilized the Shared Socio-economic Pathways (SSPs) scenarios 126, 245, and 585 from the Sixth International Coupled Model Intercomparison Project (CMIP6), along with a coupled System Dynamics (SD) and Patch-generating Land Use Simulation (PLUS) model and a carbon emission coefficient method to simulate and predict Xi’an’s land use carbon emissions from 2020 to 2040. The results indicate the following: (1) Cultivated and forest lands are the predominant land use types in Xi’an, with cultivated and grassland areas projected to decline under all three SSP scenarios by 2040. The most significant expansion of construction land, primarily at the expense of farmland, is projected under the SSP585 scenario, with an increase of 515.92 km2 by 2040. (2) Land use carbon emissions increased from 414.15 × 104 t in 2000 to 2376.10 × 104 t in 2020, with construction land being the primary source of emissions and forest land serving as the main carbon sink. However, the carbon sink capacity remained low at only 21.38 × 104 t in 2020. (3) Carbon emissions are expected to continue increasing under all scenarios through 2030 and 2040, though at a decreasing rate. The SSP126 scenario predicts the lowest emissions, reaching 9186.00 × 104 t by 2040, while SSP585 predicts the highest at 14,935.00 × 104 t. The findings of this study provide theoretical support for future low-carbon and high-quality urban development strategies.

The fire weather in Europe: large-scale trends towards higher danger

Abstract The climate over Europe has been recorded to be hotter, drier, and more fire-prone over the last decade than ever before, leading to concerns about how climate change will alter fire weather in the future. A typical measure to estimate fire weather severity based on climate is the Canadian fire weather index (FWI). In this study, we used high-resolution, bias-corrected climate model output (∼9 km) from six CMIP6 climate models and four shared socio-economic pathway projections (SSPs) to calculate consistent and comparable daily FWI datasets for Europe from 1950 to 2080. Our study aims to identify regional and large-scale shifts in fire weather severity and its predictability over time to support adaptive planning. We show that irrespective of the future SSP, fire weather will become more severe, but the increase is much stronger under high greenhouse gas emissions. This leads to new areas being exposed to severe fire weather, such as central Europe and rapidly warming mountainous areas. Already fire-prone regions in southern Europe will experience more extreme conditions. We conclude that only the low-emission SSP1-2.6 pathway can prevent strong increases in fire weather beyond the 2050s. Fire surveillance and management will become more important, even in areas and in seasons where they have not been in the focus so far.

Predicting Land Use Changes under Shared Socioeconomic Pathway–Representative Concentration Pathway Scenarios to Support Sustainable Planning in High-Density Urban Areas: A Case Study of Hangzhou, Southeastern China

Amidst the challenges posed by global climate change and accelerated urbanization, the structure and distribution of land use are shifting dramatically, exacerbating ecological and land-use conflicts, particularly in China. Effective land resource management requires accurate forecasts of land use and cover change (LUCC). However, the future trajectory of LUCC, influenced by climate change and urbanization, remains uncertain. This study developed an integrated multi-scenario framework by combining system dynamics and patch-generating land use simulation models to predict future LUCC in high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration Pathway (RCP) scenarios. The results showed the following: (1) From 2020 to 2050, cultivated land, unused land, and water are projected to decrease, while construction land is expected to increase. (2) Future land use patterns exhibit significant spatial heterogeneity across three scenarios. Construction land will expand in all districts of Hangzhou, particularly in the main urban areas. Under the SSP585 scenario, the expansion of construction land is most significant, while it is the least under the SSP126 scenario. (3) Distinct factors drive the expansion of different land use types. The digital elevation model is the predominant factor for the expansion of forest and grassland, contributing 19.25% and 30.76%, respectively. Night light contributes the most to cultivated land and construction land, at 13.94% and 20.35%, respectively. (4) The average land use intensity (LUI) in central urban districts markedly surpasses that in the surrounding suburban areas, with Xiacheng having the highest LUI and Chun’an the lowest. Under the SSP126 scenario, the area with increased LUI is significantly smaller than under the SSP245 and SSP585 scenarios. These findings offer valuable guidance for sustainable planning and built environment management in Hangzhou and similarly situated urban centers worldwide.

Concurrent drought threatens wheat and maize production and will widen crop yield gaps in the future

CONTEXTDrought poses a significant threat to global crop production. As the global community grapples with the escalating challenges of climate change, understanding the multifaceted impacts of concurrent drought on food security becomes imperative. OBJECTIVEThis study delved into the response of wheat and maize, key staples in the global food system, to different types of drought, with a particular focus on the yield gaps resulting from concurrent meteorological and agricultural drought. METHODSThe DSSAT-CERES model was adopted to simulate phenophase, rain-fed, and potential yields of maize and wheat in China from 1962 to 2100. Meteorological (Non-stationary Standard Precipitation Evapotranspiration Index, NSPEI) and agricultural (Standard Soil Moisture Index, SSMI) drought indices were calculated from crop seeding to maturity stages. We employed bivariate and multiple cross-wavelet as well as vine Copula to qualitatively and quantitatively analyze the response of yield gaps to different drought types. Finally, we determined the relative dependence weights of maize and wheat on NSPEI and SSMI by least squares regression. RESULTS AND CONCLUSIONSSpanning from 2022 to 2100, a trend of shortened growth periods for these crops were detected, accompanied by increasingly drier conditions. These situations exacerbated the crops' vulnerability to concurrent drought, leading to considerable yield reductions. Our projections indicated that future yield gaps due to concurrent drought could be, on average, 2–30% higher than those caused by single-type drought. Concurrent drought affected wheat (5–50%) more severely than maize (0–35%). Western regions would be more affected than the Eastern regions. Under the SSP (Shared socioeconomic pathway) 5-8.5 scenario in 2022–2100, all four crops would have higher dependence weights on SSMI (51–99%) than NSPEI (26–59%), emphasizing the critical role of soil moisture in agricultural drought monitoring and yield loss alleviation. SIGNIFICANCEOur findings highlight the urgent need for integrated drought management strategies that address the compounded risks of concurrent drought, thereby contributing to the resilience of agricultural systems and global food security in a changing climate. Our research proposes to consider the relative weights of meteorological and agricultural drought in the future development of composite drought monitoring indicators for addressing food drought risk under climate change.

Hydro-climatic extremes shift the hydrologic sensitivity regime in a cold basin

Escalating climate extreme events disrupt hydrological processes by affecting both water availability and sediment dynamics. However, the interconnection between hydrological variability and climatic extremes remains underexplored, particularly in cold regions under a changing climate. Here, we develop a yield-based dichotomy framework to examine the impact of shifted climatic extreme patterns on hydrological regimes in the Ishikari River Basin (IRB), Hokkaido, Japan, which is a crucial area for local agriculture and urban development. Utilizing a modified Soil and Water Assessment Tool (SWAT) integrated with downscaled CMIP6-GCM climate projections under Shared Socioeconomic Pathways (SSPs) scenarios, we identified significant annual variability in water and sediment yields associated with extreme climate events. Hot-dry conditions correlate with lower water and sediment yields, whereas increased cold extremes may result in higher sediment yields across the IRB. Our findings also indicate that hotter and drier patterns interact with hydrological processes, potentially establishing new hydrologic regimes and shifting climatic extremes-induced thresholds for yield classification within the IRB. Notably, under SSP585, both water availability and sediment transport are projected to intensify, increasing flood risks and exacerbating sedimentation challenges. Our study highlights the urgent need for adaptive water management strategies to address these anticipated changes in hydrological regimes in response to global climate change.

Increases of Offshore Wind Potential in a Warming World

AbstractOffshore wind farms, a rapidly expanding sector within wind energy, are playing a significant role in achieving global carbon neutrality, and this trend is to continue. Here, we utilize ERA5 reanalysis to correct offshore wind speed trends predicted by CMIP6 models. This approach led to enhanced projections for changes in offshore Wind Power Density (WPD) under four Shared Socioeconomic Pathways (SSPs) scenarios. Throughout the 21st century, global offshore WPD is projected to follow an upward trend across all SSP scenarios. Notably, Europe stands out with the most substantial increase in offshore WPD among regions with higher current installations, projected to reach up to 26% under 4°C global warming. Our study uncovers a notable increase of global offshore WPD in a warmer climate, which offers valuable insights for the strategic planning of future global wind energy.