Warming Scenarios Research Articles

Wind-driven sediment exchange between the Indian marginal seas over the last 18 000 years

The Indian Coastal Current is the only channel for material exchange between the two largest marginal seas in the northern Indian Ocean: the Bay of Bengal and the Arabian Sea. However, its past history is poorly known, limiting accurate predictions of its future changes. Here, we present a new clay mineral record from south of India supported by interpretations of model simulations to trace its variability over the last 18 000 years. Decreased smectite/(illite + chlorite) ratios during the cold intervals suggest that a stronger northeasterly wind led to a mean southward flow of the Indian Coastal Current in the Bay of Bengal. In contrast, increased smectite/(illite + chlorite) ratios during the warm intervals suggest the opposite scenario. Combining the proxy record with model simulations, we infer that atmospheric circulation changes were the main driver of the changes. Moreover, a possible link is observed between a positive Indian Ocean Dipole (IOD) and weakened southward flow of the Indian Coastal Current in the Bay of Bengal during the Holocene. These findings imply that future warming scenarios, if associated with more intense positive IOD events as proposed, may lead to a reduction in fresh water transport from the Bay of Bengal to the Arabian Sea.

Climate, weather, and child health: quantifying health co-benefits

Climate change affects human health negatively in a number of complex ways, and children are particularly vulnerable. Quantifying the negative impacts of climate change on health, and identifying locations where children are at greater risk, can aid evidence-based policy making. We combine high-resolution climatic data with a dataset on infant and child mortality, wasting, and stunting, from more than a hundred countries, to estimate the effects of both gradual and acute climate change, focusing on drought and heatwaves, to plausibly attribute changing child health outcomes to historical climate change. Our results suggest a non-linear relationship between temperature and children’s health, adverse effects of increases in acute events, and a strong regional heterogeneity in these impacts. Our findings also highlight the importance of poverty reduction. Greater wealth is associated with better child health outcomes, and partially mitigates the negative impacts of climate change on child health. Finally, using updated warming scenarios, our projections show that there are substantial health co-benefits from achieving low emissions scenarios.

Climate sensitivity of natural hazards processes in mountain regions: A fuzzy logic approach

Natural hazard processes, as an inherent component of mountain environments, react sensitively to global warming. The main drivers of these changes are alterations in the amount, intensity or type of precipitation, glacier melting, or thawing of permafrost ice. The hazard responses can involve a change in hazard intensity or frequency (increasing or decreasing), a shift in their location or, a shift from one type of hazard to another. As climate change impacts vary in space and time, this variability must be considered when planning measures to protect populations and infrastructure from hazardous processes. To support this, we developed a method for assessing the climate sensitivity of small individual rock releases and larger rockfall processes. The method is based on a fuzzy logic approach and uses highly resolved climate scenario data, allowing application on a regional or even larger scale.The application in a study area of 700 km2 in the central Valais (Switzerland) shows that the impacts of climate change on natural hazard processes can vary quite substantially across small spatial scales. Generally, an increase in rockfall frequency and magnitude is simulated under future warming scenarios, especially at higher altitudes. However, at lower elevations and on south-exposed slopes, a decrease in freeze-thaw cycles leads to a decrease in material availability. This knowledge is essential in discussions of how climate change should be considered in hazard and disaster management.

Leaf litter breakdown phenology in headwater stream networks is modulated by groundwater thermal regimes and litter type

AbstractLeaf litter dominates particulate organic carbon inputs to forest streams. Using data‐informed simulations, we explored how litter type (slow‐ vs. fast‐decomposing species), pulsed autumn litter inputs, groundwater‐mediated temperature regimes, and climate warming affect litter breakdown in a 3rd‐order stream network. We found that the time‐dependent interactions of these variables govern network‐scale litter breakdown phenology, with greater thermal sensitivity of slow‐decomposing litter for both current and future scenarios. Groundwater thermal inputs modified litter breakdown phenology by reducing spring and summer and elevating winter litter breakdown fluxes. Under future warming scenarios, the source depth of contributing groundwater influenced summer detrital resources; shallow groundwater‐fed streams had reduced summer resources compared to deep groundwater‐fed streams. Our results demonstrate that predicting in‐stream carbon cycling requires explicit consideration of the phenology of resource inputs and the seasonal timing of environmental factors, notably stream thermal regimes.

No slowdown of growing season extension with warming in a permafrost‐affected meadow on the Tibetan Plateau

Abstract The Tibetan Plateau holds the world's largest alpine permafrost and is undergoing an acceleration of warming. Phenological shifts over alpine permafrost in a warmer world have been little studied and are greatly underrepresented in current syntheses. Here, we conducted seasonal and gradient temperature‐controlled experiments in a permafrost‐affected meadow to evaluate how warming drives shifts in spring and autumn phenology, and associated growing‐season length at both community and species levels. We found that there is no sign of slowdown in spring advance with warming under a higher year‐around warming treatment, aligning with a future medium warming scenario. Although spring advance led to an advance in autumn senescence according to spring‐only warming experiments, the advance could not offset the delay due to concurrent warming. As a result, year‐around warming significantly delayed autumn senescence, although there was a deceleration in delay with warming under high temperature treatment than under the low one. This finding can be attributed to the possibility that winter warming is insufficient to reduce chilling accumulation, which would not delay spring phenology and then lead to a non‐slowdown in spring phenological advancement. Taken together, there is no slowdown in an extension of growing season length with warming under a higher year‐around warming treatment, with an increase of length by 9 and 21 days at the end of this century under a CO2 stabilization and medium warming scenarios, respectively. Synthesis. Our results suggest that a continued growing season extension at least under the medium warming scenario would help permafrost‐affected meadow ecosystems to mitigate permafrost carbon release on the Tibetan Plateau.

Emerging Risk to Dengue in Asian Metropolitan Areas Under Global Warming

AbstractAedes sp. mosquitoes are changing their geographic range in response to climate change. This is of concern because these mosquitoes can carry dengue fever and other viral diseases. Changing weather patterns can also increase the numbers of Aedes mosquitoes, leading to greater human exposure and enhancing population health risks. We project the geographic distribution of Aedes and associated changes in populations exposed to dengue in Asian metropolitan areas under warming scenarios from 1.5°C to 5.0°C above pre‐industrial temperatures, using multi‐model ensembles. With global warming, the southern part of the Arabian Peninsula, the coast of the Arabian Sea in southern Iran, southern Pakistan in West Asia, the Korean Peninsula, most of the Japanese islands, and parts of North China in East Asia are projected to become suitable for dengue transmission. The numbers of metropolitan areas exposed to dengue is projected to change from 142 (48%) in the reference period (1995–2014) to 211 (71%) at 5.0°C warming. With the combined impact of socioeconomic and climate change, population exposure to dengue in Asian metropolitan areas is projected to increase from 263 (multi‐model range 252–268) million in 1995–2014 to 411 (394–432) million, 446 (420–490) million, 509 (475–601), 558 (493–685) and 587 (529–773) million, respectively, at 1.5°C, 2.0°C, 3.0°C, 4.0°C and 5°C warming, with an average of 2.9 million new people exposed to dengue fever in metropolitan areas each year.

Regression Forest Approaches to Gravity Wave Parameterization for Climate Projection

AbstractWe train random and boosted forests, two machine learning architectures based on regression trees, to emulate a physics‐based parameterization of atmospheric gravity wave momentum transport. We compare the forests to a neural network benchmark, evaluating both offline errors and online performance when coupled to an atmospheric model under the present day climate and in 800 and 1,200 ppm CO2 global warming scenarios. Offline, the boosted forest exhibits similar skill to the neural network, while the random forest scores significantly lower. Both forest models couple stably to the atmospheric model, and control climate integrations with the boosted forest exhibit lower biases than those with the neural network. Integrations with all three data‐driven emulators successfully capture the Quasi‐Biennial Oscillation (QBO) and sudden stratospheric warmings, key modes of stratospheric variability, with the boosted forest more accurate than the random forest in replicating their statistics across our range of carbon dioxide perturbations. The boosted forest and neural network capture the sign of the QBO period response to increased CO2, though both struggle with the magnitude of this response under the more extreme 1,200 ppm scenario. To investigate the connection between performance in the control climate and the ability to generalize, we use techniques from interpretable machine learning to understand how the data‐driven methods use physical information. We leverage this understanding to develop a retraining procedure that improves the coupled performance of the boosted forest in the control climate and under the 800 ppm CO2 scenario.

Identifying Climate Patterns Using Clustering Autoencoder Techniques

Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k-means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k-means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.

Analyzing the Contribution of Moisture Sources to Precipitation Changes Under 1.5/2.0°C Stabilized Warming Scenarios: A Study Over Northwest China

AbstractChanges in precipitation and its causes under future warming scenarios in Northwest China are of great concern. Based on the dynamical downscaling results of the Weather Research and Forecasting model (WRF), this study quantitatively identified the contribution of local evaporation and external moisture transport to future precipitation changes in western and eastern Northwest China (WNWC and ENWC) by calculating the precipitation recycling ratio (PRR). The results showed that the WRF could reasonably reproduce the observed spatial and temporal distribution of precipitation and evaporation during the historical reference period of 1985–2014. Under the 1.5 and 2.0°C stabilized warming scenarios from 2071 to 2100, there is a stronger precipitation growth in WNWC than in ENWC, and the PRR generally increases in WNWC and decreases in ENWC. Further analysis indicates that external moisture transport is the dominant contributor to the increased precipitation in all cases with its contribution exceeding 70%, while the difference of precipitation growth in two sub‐regions arises from the summer moisture transport at the southern boundary as the inflow in WNWC and outflow in ENWC. Compared to the negligible contribution of evaporation in ENWC (less than 7%), evaporation contributes more than 23% to the precipitation increase in WNWC under future warming scenarios, which may be related to the strong land‐atmosphere coupling there. Furthermore, an additional warming of 0.5°C leads to an increase in precipitation for both sub‐regions, which is mainly due to the contribution of external moisture transport.

Response of the Southern Hemisphere extratropical cyclone climatology to climate intervention with stratospheric aerosol injection

Little is known about how climate intervention through stratospheric aerosol injection (SAI) may affect the climatology of the Southern Hemisphere extratropical cyclones under warming scenarios. To address this knowledge gap, we tracked extratropical cyclones from 2015 to 2099 in a set of projections of three international projects: the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with Stratospheric Aerosol Injection (ARISE), the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS), and the Geoengineering Model Intercomparison Project (GeoMIP/G6sulfur). Comparisons were performed between no-SAI and SAI scenarios as well as between different timeslices and their reference period (2015–2024). Among the findings, both no-SAI and SAI project a decrease in cyclone frequency towards the end of the century although weaker under SAI scenarios. On the other hand, cyclones tend to be stronger under no-SAI scenarios while keeping their intensity more similar to the reference period under SAI scenarios. This means that under SAI scenarios the climatology of cyclones is less affected by global warming than under no-SAI. Other features of these systems, such as travelling distance, lifetime, and mean velocity show small differences between no-SAI and SAI scenarios and between reference and future periods.

Competing climate feedbacks of ice sheet freshwater discharge in a warming world

Freshwater discharge from ice sheets induces surface atmospheric cooling and subsurface ocean warming, which are associated with negative and positive feedbacks respectively. However, uncertainties persist regarding these feedbacks’ relative strength and combined effect. Here we assess associated feedbacks in a coupled ice sheet-climate model, and show that for the Antarctic Ice Sheet the positive feedback dominates in moderate future warming scenarios and in the early stage of ice sheet retreat, but is overwhelmed by the negative feedback in intensive warming scenarios when the West Antarctic Ice Sheet undergoes catastrophic collapse. The Atlantic Meridional Overturning Circulation is affected by freshwater discharge from both the Greenland and the Antarctic ice sheets and, as an interhemispheric teleconnection bridge, exacerbates the opposing ice sheet’s retreat via the Bipolar Seesaw. These results highlight the crucial role of ice sheet-climate interactions via freshwater flux in future ice sheet retreat and associated sea-level rise.

Climate and vegetation change impacts on future conterminous United States water yield

Future water availability is influenced by both climate and associated vegetation dynamics. This study coupled vegetation projections from a dynamic global vegetation model (MC2) with an ecohydrological model, Water Supply Stress Index (WaSSI), to predict water yield at the 8-digit Hydrologic Unit Code (HUC8) watershed level for the conterminous United States (CONUS) for the 21st century. We considered two contrasting warming scenarios (Representative Concentration Pathways 8.5 and 4.5) and accounted for simulation uncertainty by using a large ensemble of climate model outputs. The coupled model projects a decrease in water yield across much of CONUS, especially towards end-century (2080–2099) under RCP 8.5 (warmer scenario), reaching up to −30% at the regional level, relative to the 2008–2027 baseline period. Overall, the projected water yield reduction under RCP 8.5 is roughly twice as high as under RCP 4.5. Substantial changes in water yield for watersheds in the central and southeastern United States are expected by mid-century (2040–2059), reaching up to −40% (RCP 4.5) and −75% (RCP 8.5) at at the century’s end (2080–2099), relative to 2008–2027, respectively. Climate change, rather than vegetation change, strongly dominates the projected future changes in water yield, with contributions typically one order of magnitude higher. For a small number of watersheds, the effects of vegetation change can mitigate or exacerbate the effects of climate change on water yield. Our simulation results suggest a widespread increase in aridity and evaporative indices and a decrease in soil moisture, especially under RCP 8.5. Our integrated modeling results can inform policy makers and resource development planners quantitative information of future water availability.

Can upwelling regions be potential thermal refugia for marine fishes during climate warming?

Species are expected to migrate to higher latitudes as warming intensifies due to anthropogenic climate change since physiological mechanisms have been adapted to maximize fitness under specific temperatures. However, literature suggests that upwellings could act as thermal refugia under climate warming protecting marine ecosystem diversity. This research aimed to predict the effects of climate warming on commercial and non-commercial fish species reported in official Mexican documents (>200 species) based on their thermal niche to observe if upwellings can act as potential thermal refugia. Present (2000–2014) and Representative Concentration Pathway (6.0 and 8.5) scenarios (2040–2050 and 2090–2100) have been considered for this work. Current and future suitability patterns, species distribution, richness, and turnover were calculated using the minimum volume ellipsoids as algorithm. The results in this study highlight that beyond migration to higher latitudes, upwelling regions could protect marine fishes, although the mechanism differed between the innate characteristics of upwellings. Most modeled species (primarily tropical fishes) found refuge in the tropical upwelling in Northern Yucatan. However, the highest warming scenario overwhelmed this region. In contrast, the Baja California region lies within the Eastern Boundary Upwelling Systems. While the area experiences an increase in suitability, the northern regions have a higher upwelling intensity acting as environmental barriers for many tropical species. Conversely, in the southern regions where upwelling is weaker, species tend to congregate and persist even during elevated warming, according to the turnover analysis. These findings suggest that tropicalization in higher latitudes may not be as straightforward as previously assumed. Nevertheless, climate change affects numerous ecosystem features, such as trophic relationships, phenology, and other environmental variables not considered here. In addition, uncertainty still exists about the assumption of increasing intensity of upwelling systems.

Global agricultural N2O emission reduction strategies deliver climate benefits with minimal impact on stratospheric O3 recovery

Agricultural nitrous oxide (N2O) emission reduction strategies are required given the potency of N2O as a greenhouse gas. However, the growing influence of N2O on stratospheric ozone (O3) with declining stratospheric chlorine means the wider atmospheric impact of N2O reductions requires investigation. We calculate a N2O emission reduction of 1.35 TgN2O yr-1 (~5% of 2020 emissions) using spatially separate deployment of nitrification inhibitors ($70–113 tCO2e−1) and crushed basalt (no-cost co-benefit) which also sequesters CO2. In Earth System model simulations for 2025–2075 under high (SSP3-7.0) and low (SSP1-2.6) surface warming scenarios, this N2O mitigation reduces NOx-driven O3 destruction, driving regional stratospheric O3 increases but with minimal impact on total O3 column recovery. By 2075, the radiative forcing of the combined N2O and CO2 reductions equates to a beneficial 9–11 ppm CO2 removal. Our results support targeted agricultural N2O emission reductions for helping nations reach net-zero without hindering O3 recovery.

Combined stress of an insecticide and heatwaves or elevated temperature induce community and food web effects in a Mediterranean freshwater ecosystem

Ongoing global climate change will shift nature towards Anthropocene's unprecedented conditions by increasing average temperatures and the frequency and severity of extreme events, such as heatwaves. While such climatic changes pose an increased threat for freshwater ecosystems, other stressors like pesticides may interact with warming and lead to unpredictable effects. Studies that examine the underpinned mechanisms of multiple stressor effects are scarce and often lack environmental realism. Here, we conducted a multiple stressors experiment using outdoor freshwater mesocosms with natural assemblages of macroinvertebrates, zooplankton, phytoplankton, macrophytes, and microbes. The effects of the neonicotinoid insecticide imidacloprid (1 µg/L) were investigated in combination with three temperature scenarios representing ambient, elevated temperatures (+4 °C), and heatwaves (+0 to 8 °C), the latter two having similar energy input. We found similar imidacloprid dissipation patterns for all temperature treatments with lowest average dissipation half-lives under both warming scenarios (DT50: 3 days) and highest under ambient temperatures (DT50: 4 days) throughout the experiment. Amongst all communities, only the zooplankton community was significantly affected by the combined treatments. This community demonstrated low chemical sensitivity with lagged and significant negative imidacloprid effects only for cyclopoids. Heatwaves caused early and long-lasting significant effects on the zooplankton community as compared to elevated temperatures, with Polyarthra, Daphnia longispina, Lecanidae, and cyclopoids being the most negatively affected taxa, whereas Ceriodaphnia and nauplii showed positive responses to temperature. Community recovery from imidacloprid stress was slower under heatwaves, suggesting temperature-enhanced toxicity. Finally, microbial and macrofauna litter degradation were significantly enhanced by temperature, whereas the latter was also negatively affected by imidacloprid. A structural equation model depicted cascading food web effects of both stressors with stronger relationships and significant negative stressor effects at higher than at lower trophic levels. Our study highlights the threat of a series of heatwaves compared to elevated temperatures for imidacloprid-stressed freshwaters.

Climate refugia along Lake Superior’s shores: disjunct arctic–alpine plants rely on cool shoreline temperatures but are restricted to highly exposed habitat under climate warming

Abstract Climate refugia can serve as a remnant habitat or stepping stones for species dispersal under climate warming. The largest freshwater lake by surface area, Lake Superior, USA and Canada, serves as a model system for understanding cooling-mediated local refugia, as its cool water temperatures and wave action have maintained shoreline habitats suitable for southern disjunct populations of arctic–alpine plants since deglaciation. Here, we seek to explain spatial patterns and environmental drivers of arctic–alpine plant refugia along Lake Superior’s shores, and assess future risk to refugia under moderate (+3.5 °C) and warmest (+5.7 °C) climate warming scenarios. First, we examined how the interactive effects of summer surface water temperatures and wind affected onshore temperatures, resulting in areas of cooler refugia. Second, we developed an ecological niche model for the presence of disjunct arctic–alpine refugia (pooling 1253 occurrences from 58 species) along the lake’s shoreline. Third, we fit species distribution models for 20 of the most common arctic–alpine disjunct species and predicted presence to identify refugia hotspots. Finally, we used the two climate warming scenarios to predict changes in the presence of refugia and disjunct hotspots. Bedrock type, elevation above water, inland distance, July land surface temperature from MODIS/Terra satellite and near-shore depth of water were the best predictors of disjunct occurrences. Overall, we predicted 2236 km of the shoreline (51%) as disjunct refugia habitat for at least one species under current conditions, but this was reduced to 20% and 7% with moderate (894 km) and warmest (313 km) climate change projections.

Climate Impact on Dissolved Organic Carbon Composition in a North‐Temperate Peatland and Recipient Surface Water

AbstractClimate may regulate dissolved organic carbon (DOC) composition across the peat‐water interface, but experimental evidence is scarce. We manipulated the climate in peatland and recipient surface water mesocosms to reflect four different climate warming scenarios. In half of the mesocosms, the water level was managed to avoid drought, after which responses were recorded during two annual cycles. It was hypothesized that warming and drought increase the aromaticity and humic‐like fluorescence character of DOC, and that this change propagate to recipient waters. Pore water DOC concentrations increased with temperature and peaked in hydrologically unmanaged mesocosms. Aromaticity increased as expected after drought in the warmest scenario (+3.2°C), but the overall evidence for hypothesized changes in DOC aromaticity and fluorescence composition (%) was limited. In managed warming scenarios, one aromatic humic component expectedly increased together with microbially derived humic fluorescence, whereas two other humic‐like components decreased. In the unmanaged mesocosms which were exposed to drought, water level exerted an overriding control of humic DOC; for example, as the microbially derived humic fluorescence diminished after drought in all climate scenarios. In the surface water recipients, warming had nearly no impact on humic‐like fluorescence, but there were decreases in protein‐like fluorescence. Overall, this experiment revealed no conclusive support for the hypothesized aromatization and humification of peatland‐derived DOC in response to drought or warming. Nonetheless, both factors increase the quantity of DOC in peatland pore waters and affect composition in complex ways, calling for further investigation of chemical and functional traits of peatland DOC in a changing environment.

Climate change impacts on Central Asia: Trends, extremes and future projections

AbstractCentral Asia (CA) is among the world's most vulnerable regions to climate change. Increasing anthropogenic greenhouse gas concentrations (GHGs) are the primary forcing of the current and future climate system for the time scale of a century. By analysing observation datasets, we show that a warming of 1.2°C led to a decrease of 20% in snow‐depth CA during the last 70 years, especially over the mountains. In recent decades, longer summer times and fewer icing days (more than 20 days·year−1) have exposed unprecedented shock to CA's climate system's components. Furthermore, we analyse 442 model simulations from Coupled Model Inter‐comparison Project Phase 5 and 6 (CMIP5, CMIP6) and show that CMIP6 simulations are generally warmer and wetter than the CMIP5 ones in CA. For instance, under the highest emission scenarios (RCP8.5 and SSP5‐8.5), CMIP6 projects a 6.1°C increase, while CMIP5 projects a 5.3°C increase, suggesting CMIP6 anticipates greater warming with high emissions. In contrast to CMIP6, the CMIP5 precipitation trends suggest a potential nonlinear relationship between increased greenhouse gas emissions and changes in precipitation, though the impact is much less pronounced than the temperature changes. Our analysis shows that CMIP6 models are more sensitive to temperature rise than CMIP5 ones. Both simulation sets' ensemble means capture well the observed warming trend. The imposed snow‐melting leads to an increase in the run‐off in the vicinity of glaciers. Such climatic shifts lead to more flooding events in CA. Given the projected warming range of 2–6°C in CA at the end of the century in various scenarios and models, such warming trends might be catastrophic in this region. The seasonal cycle of the temperature change indicates an extension of the glacier's melting period under future scenarios with fossil‐fueled development. The models' uncertainty increases for the far‐future time‐slice, and warming larger than 4°C in CA is very likely among all the models and during all the seasons if no sustainable action is taken. This study also incorporates a detailed Köppen climate classification analysis, revealing significant shifts towards warmer climate categories in Central Asia, which may have profound implications for regional hydrological cycles and water resource management, particularly in the Amu Darya and Syr Darya river basins under warmer scenario by the end of the century. The Tundra and ice cap climate categories will lose more than 60% of their coverage at the end of the century compared to the historical period in the Amu Darya and Syr Darya river basins.

Projected impacts of global warming scenarios on marine ecosystems: Insights from the CMIP6 model

Rising oceanic temperatures and increased heat content have triggered a decline in marine biodiversity and the degradation of ecosystem services. This study employs the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze variables within the Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) framework. Focusing on two contrasting Shared Socioeconomic Pathways (SSPs) - SSP1-2.6 (low-warming scenario) and SSP5-8.5 (high-warming scenario) - we assess future impacts of climate-related factors on marine ecosystems across major oceanic regions. Under the high-warming SSP5-8.5 scenario, global ocean temperature rise, coupled with declining surface pH levels, nitrate concentrations, and plankton biomass/productivity, is evident. Regional reductions in plankton biomass/productivity, especially pronounced at higher latitudes, are observed in both SSP scenarios. Nutrient cycling emerges as a pivotal factor influencing plankton communities, particularly ammonium regulation in the Southern Ocean. This research emphasizes the urgent need to curb greenhouse gas emissions to mitigate global warmings profound effects on marine ecosystems.

Quantitative Analysis of the Vertical Interactions between Dust, Zonal Wind, and Migrating Diurnal Tide on Mars and the Role of Gravity Waves

In the atmospheric system of Mars, vertical interactions are crucial, yet quantitative studies addressing this issue remain scarce. Based on simulations using the Mars PCM-LMDZ, we present the first frequency-domain quantitative analysis of the vertical interactions among Martian atmospheric dust, zonal circulation, and the migrating diurnal tide (DW1), employing Partial Directed Coherence (PDC) techniques to quantify the strength of associations between different variables. Our findings reveal a chain of influence where sub-seasonal-scale dust signals in the troposphere, through the Doppler effect of middle atmospheric zonal winds, transmit modulated energy to the DW1 in the upper mesosphere, thereby facilitating interlayer atmospheric interactions. The radiative heating from dust activities enhances the residual mean meridional circulation, which, under the influence of the Coriolis force, further accelerates the westerlies. Although gravity wave activity also contributes to the acceleration of the westerlies, its forcing generally remains below 5 m/s, which is relatively weak compared to the impact of intense dust activities in the warm scenario experiments (approximately 20 m/s). Overall, this study quantifies the interactions among atmospheric layers by means of PDC technology and analytically demonstrates how dust energy is transferred to mesospheric tides by shaping the zonal winds in between.