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We analyze data of 27 global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), and examine projected changes in temperature and precipitation over the African continent during the twenty-first century. The temperature and precipitation changes are computed for two future time slices, 2030–2059 (near term) and 2070–2099 (long term), relative to the present climate (1981–2010), for the entire African continent and its eight subregions. The CMIP6 multi-model ensemble projected a continuous and significant increase in the mean annual temperature over all of Africa and its eight subregions during the twenty-first century. The mean annual temperature over Africa for the near (long)-term period is projected to increase by 1.2 °C (1.4 °C), 1.5 °C (2.3 °C), and 1.8 °C (4.4 °C) under the Shared Socioeconomic Pathways (SSPs) for weak, moderate, and strong forcing, referenced as SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The future warming is not uniform over Africa and varies regionally. By the end of the twenty-first century, the largest rise in mean annual temperature (5.6 °C) is projected over the Sahara, while the smallest rise (3.5 °C) is over Central East Africa, under the strong forcing SSP5-8.5 scenario. The projected boreal winter and summer temperature patterns for the twenty-first century show spatial distributions similar to the annual patterns. Uncertainty associated with projected temperature over Africa and its eight subregions increases with time and reaches a maximum by the end of the twenty-first century. On the other hand, the precipitation projections over Africa during the twenty-first century show large spatial variability and seasonal dependency. The northern and southern parts of Africa show a reduction in precipitation, while the central parts of Africa show an increase, in future climates under the three reference scenarios. For the near (long)-term periods, the area-averaged precipitation over Africa is projected to increase by 6.2 (4.8)%, 6.8 (8.5)%, and 9.5 (15.2)% under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The median warming simulated by the CMIP6 model ensemble remains higher than the CMIP5 ensemble over most of Africa, reaching as high as 2.5 °C over some regions, while precipitation shows a mixed spatial pattern.

Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue ‘Air quality, past present and future’.

Wind is an important renewable energy source, and even minor variations in wind speed will significantly impact wind power generation. The objective of this study was to systematically assess the impacts of climate change on wind energy resources in the South China Sea (SCS) under future climate projections. To achieve this, we employed a multi-model ensemble approach based on Coupled Model Intercomparison Project Phase 6 (CMIP6) data under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results demonstrated that, in comparison with scatterometer wind data, the CMIP6 historical results (1995–2014) showed good performance in capturing the spatiotemporal distribution of wind power density (WPD) in the SCS. There were regional discrepancies in the central SCS due to the complex monsoon-driven wind dynamics. Future projections revealed an overall increase in annual mean wind power density (WPD) across the entire SCS by the mid-21st century (2046–2065) and late 21st century (2080–2099). The seasonal analyses indicated significant WPD increases in summer, especially in the northern SCS and the region adjacent to the Kalimantan strait. The increase in summer (>40 × 10−4 m/s/year under SSP5-8.5) is about triple that in winter. In the late 21st century, an increase in WPD exceeding 10% can be generally anticipated under the SSP2-4.5 and SSP5-8.5 scenarios in all seasons. The extreme wind in the northern and central SCS will further increase by 5% under the three scenarios, which will add an extra extreme load to wind turbines and related marine facilities. These assessments are essential for wind farm planning and long-term energy production evaluations in the SCS. Based on the findings in this study, specific areas of concern can be targeted to conduct localized downscaling analyses and risk assessments.

• Globally, spring phenology and abiotic processes are shifting earlier with warming. Differences in the magnitudes of these shifts may decouple the timing of plant resource requirements from resource availability. In riparian forests across the northern hemisphere, warming could decouple seed release from snowmelt peak streamflow, thus reducing moisture and safe sites for dominant tree recruitment. • We combined field observations with climate, hydrology, and phenology models to simulate future change in synchrony of seed release and snowmelt peaks in the South Platte River Basin, Colorado, for three Salicaceae species that dominate western USA riparian forests. • Chilling requirements for overcoming winter endodormancy were strongest in Salix exigua, moderately supported for Populus deltoides, and indiscernible in Salix amygdaloides. Ensemble mean projected warming of 3.5°C shifted snowmelt peaks 10–19 d earlier relative to S. exigua and P. deltoides seed release, because decreased winter chilling combined with increased spring forcing limited change in their phenology. By contrast, warming shifted both snowmelt peaks and S. amygdaloides seed release 21 d earlier, maintaining their synchrony. • Decoupling of snowmelt from seed release for Salicaceae with strong chilling requirements is likely to reduce resources critical for recruitment of these foundational riparian forests, although the magnitude of future decoupling remains uncertain.

This study evaluates the impacts of climate change in the Yarmouk River Basin (YRB) using the Statistical Downscaling Model (SDSM) and observed data from six meteorological stations (1989-2017). The second-generation Canadian Earth System Model (CanESM2) was used to project climate scenarios under Representative Concentration Pathways (RCPs) for the period 2018-2100, demonstrating strong performance in modeling the arid climate (R² = 0.87-0.996, RMSE = 0.478-1.829 for calibration; R² = 0.799-0.998, RMSE = 0.55-1.879 for validation). Projected maximum temperature increases across the basin range from 0.19 °C to 1.8 °C, while minimum temperature rises from 0.096 °C to 1.4 °C, depending on emission scenarios. Precipitation is expected to decline by 3% to 49%, with the most severe reductions under RCP8.5. Moreover, current climate observations indicate sharper temperature increases and precipitation declines than even RCP8.5 projections, signaling elevated risks of drought and water scarcity. The analysis of extreme events reveals substantial increases in heatwaves, notable declines in cold spells, and longer dry periods across all scenarios. Under RCP8.5, heatwave days may rise by up to 22, cold spells may drop by more than 24 days, and consecutive dry days could extend by over 65 days, suggesting intensified drought stress. A frequency analysis of the 12-month Standardized Precipitation Index (SPI-12) reveals relatively stable hydro-climatic conditions under RCP2.6, with a balanced distribution of dry and wet months and minimal extremes. Under RCP4.5, a modest shift toward drier conditions emerges, with slightly increased drought frequencies and minor extreme events. In contrast, RCP8.5 projects pronounced drying, with over 40% of months falling below SPI = -0.5 in Irbid and Al-Mafraq, and rising frequencies of both extreme drought and wet months in Samar. These progressive changes highlight the basin’s vulnerability to emission-driven climate impacts and underscore the urgent need for adaptation planning. The findings support the SDSM–CanESM2 framework as a robust tool for assessing climate risks and guiding mitigation strategies in arid and semi-arid regions

Phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate models’ projections of the 2014–2100 Arctic warming under radiative forcing from representative concentration pathway 4.5 (RCP4.5) vary from 0.9° to 6.7°C. Climate models with or without a full indirect aerosol effect are both equally successful in reproducing the observed (1900–2014) Arctic warming and its trends. However, the 2014–2100 Arctic warming and the warming trends projected by models that include a full indirect aerosol effect (denoted here as AA models) are significantly higher (mean projected Arctic warming is about 1.5°C higher) than those projected by models without a full indirect aerosol effect (denoted here as NAA models). The suggestion is that, within models including full indirect aerosol effects, those projecting stronger future changes are not necessarily distinguishable historically because any stronger past warming may have been partially offset by stronger historical aerosol cooling. The CMIP5 models that include a full indirect aerosol effect follow an inverse radiative forcing to equilibrium climate sensitivity relationship, while models without it do not.

Future hydroclimate change is expected to generally follow a wet-get-wetter, dry-get-drier (WWDD) pattern, yet key uncertainties remain regionally and over land. It has been previously hypothesized that lake levels of the Last Glacial Maximum (LGM) could map a reverse analog to future hydroclimate changes due to reduction of CO2 levels at this time. Potential complications to this approach include, however, the confounding effects of factors such as the Laurentide Ice Sheet and lake evaporation changes. Using the ensemble output of six coupled climate models, lake energy and water balance models, an atmospheric moisture budget analysis, and additional CO2 sensitivity experiments, we assess the effectiveness of the LGM as a reverse analog for future hydroclimate changes for a transect from the drylands of North America to southern South America. The model ensemble successfully simulates the general pattern of lower tropical lake levels and higher extratropical lake levels at LGM, matching 82% of the lake proxy records. The greatest model-data mismatch occurs in tropical and extratropical South America, potentially as a result of underestimated changes in temperature and surface evaporation. Thermodynamic processes of the mean circulation best explain the direction of lake changes observed in the proxy record, particularly in the tropics and Pacific coasts of the extratropics, and produce a WWDD pattern. CO2 forcing alone cannot account for LGM lake level changes, however, as the enhanced cooling from the Laurentide ice sheet appears necessary to generate LGM dry anomalies in the tropics and to deepen anomalies in the extratropics. LGM performance as a reverse analog is regionally dependent as anti-correlation between LGM and future P − E is not uniformly observed across the study domain.

Biases in global Earth System Models (ESMs) are an important source of errors when used to obtain boundary conditions for regional models. Here we examine historical and future conditions in the California Current System (CCS) using three different methods to force the regional model: (a) interpolation of ESM output to the regional grid with no bias correction; (b) a “seasonally‐varying” delta method that obtains a season‐dependent mean climate change signal from the ESM for a 30‐year future period; and (c) a “time‐varying” delta method that includes the interannual variability of the ESM over the 1980–2100 period. To compare these methods, we use a high‐resolution (0.1°) physical‐biogeochemical regional model to dynamically downscale an ESM projection under the RCP8.5 emission scenario. Using different downscaling methods, the sign of future changes agrees for most of the physical and ecosystem variables, but the spatial patterns and magnitudes of these changes differ, with the seasonal‐ and time‐varying delta simulations showing more similar changes. Not correcting the ESM forcing leads to amplification of biases in some ecosystem variables as well as misrepresentation of the California Undercurrent and CCS source waters. In the non‐bias corrected and time‐varying delta simulations, most of the ecosystem variables inherit trends and decadal variability from the ESM, while in the seasonally‐varying delta simulation the future variability reflects the observed historical variability (1980–2010). Our results demonstrate that bias correcting the forcing prior to downscaling improves historical simulations, and that the bias correction method may impact the spatial and temporal variability of the future projections. Plain Language Summary Global Earth System Models (ESMs) are important tools to understand Earth's processes and project how they will change over time in response to anthropogenic activity and changing climate conditions. However, ESMs have limited capacity to resolve coastal processes at sufficiently high resolution (e.g., <50 km) and often show regional biases when they are compared to observed data. To address the resolution issue, ESMs can be used as input to force high‐resolution models, and their biases with respect to observed data can be reduced by applying bias‐correction methods. This process, called dynamical downscaling, is widely used; but, the implications of different methodological choices during downscaling have not been adequately explored. In this article, we compare three different pre‐processing methods (two with bias correction and one without) prior to dynamical downscaling to simulate present and future conditions in the California Current System. We evaluate the performance of each method by comparing with observed data and assessing how they reproduce future changes and variability. We find that bias correcting the ESM data before forcing the ocean model is key to reducing ESM biases and resolving coastal processes. Results here will help to guide methodological choices when projecting climate change using high‐resolution ocean models to resolve coastal processes. Key Points Bias correcting forcing prior to downscaling is key to reducing historical biases and resolving critical ecosystem‐relevant coastal processes Different bias correction methods produced similar mean and seasonal changes of ecosystem variables in downscaled projections Using forcing without bias correction amplified the historical bias of some variables and produced a misrepresentation of the California Undercurrent

This study explores the direct and semi-direct radiative effect of North African dust in the present and future climate using the regional climate model RegCM4. The simulations cover a historical decade extending from December 1999 to November 2009 and a future decade that spans from December 2089 to November 2099 under the Representative Concentration Pathway 4.5 (RCP4.5), without considering land-cover/land-use changes. For each time-slice a set of two experiments was conducted, namely the “Control”, in which dust is radiatively inactive and the “Feedback”, in which dust interacts with shortwave and longwave radiation. The impact of North African dust on the regional radiative balance is assessed by comparing the “Feedback” and the “Control” experiments during the historical period. The results indicate that the combined effect of dust Direct + Semi-direct Radiative Effect (DSRE) on the shortwave is − 13.8 W m−2 and − 10.7 W m−2 over the Sahel and the Sahara, respectively. The Direct Radiative Effect (DRE) dominates over the Semi-direct Radiative Effect (SRE) in both winter and summer, although during summer over some parts of the desert the SRE in the longwave spectrum accounts for almost 50% of the DSRE. Part of this is due to a noteworthy statistically significant increase of clouds that reaches values up to 3% and stretches across the eastern and western Sahara desert. Dust DSRE intensifies moderately in the future period (− 15.8 W m−2 and − 11.0 W m−2), while its spatial distribution remains the same, suggesting that the effect of climate change in the atmosphere will not alter the radiative effect of dust over North Africa considerably. When taking into account the dust radiative feedback in regional climate simulations the maximum temperature is altered by − 0.2/− 0.2 °C and − 0.3/− 0.6 °C over the Sahel and Sahara regions, respectively, during the summer/winter period, mainly as a result of changes in the shortwave radiative balance. On the contrary, the minimum temperature increases, since it is mostly controlled by the longwave radiation emitted from the Earth’s surface. In the future period the near surface air temperature increases by 1.5–2.5 °C and the fine dust column burden increases by + 4% to + 8% in comparison to the historical period, mainly due to the RCP4.5 forcing. When the dust feedback on climate is active in future simulations it can decrease the summer daily maximum temperature by 0.3 °C over Sahel, and decrease or increase it locally in Sahara by up to 0.2 °C. Prior to the Feedback-Control analysis an extensive evaluation has been conducted for dust optical depth, dust extinction, near surface air temperature and cloud fraction cover using the LIVAS, CRU and CM SAF datasets.

Extreme events such as floods, droughts, and heatwaves profoundly impact all socio-economic sectors in Central Africa. Previous studies often focus on how extreme events respond to global warming without contextualizing these results within socio-economic sectors. In contrast, the present study uses data from 13 global climate models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to explore the impacts of global warming-induced changes in extreme events across various socio-economic sectors. Six indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are employed for the purpose. Analyses are conducted over two time frames, namely 2030–2059 for the near future and 2071–2100 for the far future in comparison to the historical period 1985–2014, under the low SSP126 and high SSP585 emission scenarios. The results indicate enhancements in dry spells and weakening in wet spells in response to global warming. Simultaneously, an increase in annual total precipitation is expected, in association with intensification in heavy precipitation days and daily precipitation intensity. Temperature-based indices exhibit a decreasing trend in the total number of cold days per year and an increasing trend in the number of hot days, with more intense changes under the unmitigated SSP585 scenario. The low-emission, highly mitigated SSP126 scenario demonstrates its effectiveness in limiting the worsening of projected conditions compared to SSP585. Discussing the potential socio-economic risks associated with these changes highlights the urgent need to formulate robust policies to mitigate underlying hazards, as they could lead to challenges such as food insecurity, heat and humidity-related illnesses, population impoverishment, market inflation, and social instability.