Concurrent Climate Research Articles

International trade makes European food markets less vulnerable to concurrent and recurrent climate extremes

Abstract Extreme weather events are occurrences of unusually severe weather or climate conditions that can devastate local communities, agriculture and natural ecosystems. Due to climate change, these extreme events are becoming increasingly more likely, lasting longer, and more severe in impact. In this paper, we illustrate the potential effects of concurrent and recurrent extreme weather events on EU agricultural commodity markets and, in particular, on production and trade. A combination of concurrent and recurrent events is expected to have a negative and compounding effect on domestic food supply and trade, making EU agricultural markets less resilient. A set of scenarios based on record low yields show how EU production could be drastically affected in the coming two years compared to a business-as-usual situation. Market disruptions would be potentially larger for commodities in which the EU has a strong net exporter position, such as wheat. In the absence of extremes in non-EU regions, trade reveals as a key element in buffering the adverse impacts of extreme events in the EU.

Mediterranean brown trout catch-and-release recreational fisheries might not be sustainable under concurrent climate warming and hydrological change

Mediterranean brown trout catch-and-release recreational fisheries might not be sustainable under concurrent climate warming and hydrological change

Income and inequality pathways consistent with eradicating poverty

Abstract To investigate concurrent climate action and poverty eradication, we present combined income growth (GDP/capita) and domestic income inequality (measured as Gini coefficients) pathways that pursue (absolute and relative) poverty eradication reflecting the three narratives of Sustainable Development Pathway (SDP). The GDP/capita pathways are modifications of the Shared Socioeconomic Pathway SSP1 scenario, including one post-growth future for high-income countries and higher growth for all currently lower-income countries. Current inequality levels, together with the total national income from the GDP pathways, determine the inequality reductions required to eradicate poverty in individual countries; they are based on a methodology that specifies the relationship between poverty, inequality, and growth. Our pathways show rapid and sustained reductions in within-country inequality (Gini), even with high economic growth. The speed of redistribution is limited to the highest historically observed changes in inequality. We identify which countries face the greatest difficulties in meeting their poverty eradication targets and estimate the level of international transfers needed to fill the gap for those countries. Our findings reconfirm the importance of reducing within-country inequality in eradicating global poverty.

Concurrent extremes in mid-latitude Asia triggered by resonance of multi-scale zonal wind

Abstract Climatic changes worsen concurrent extreme climate events. In July and August of 2022 and 2020, respectively, unexpected concurrent extreme events occurred in mid-latitude Asia. The sudden and severe consequences highlight the importance of a thorough understanding of the drivers of such extreme events, which is crucial for improving predictions and implementing preventive measures to mitigate future risks. By applying multi-scale window transform methodology, a unique mechanism of multi-scale zonal wind resonance is identified, which manifests as a quasi-stationary co-coupling with low-frequency zonal winds. This resonance leads to barotropic instability, triggering abnormal low-frequency Rossby wave behavior in the entrance and exit regions of the quasi-stationary jet stream. Simultaneously, the intensified meridional wind, coupled with adiabatic atmospheric warming, amplifies baroclinic instability, resulting in an enhanced wave pattern and the high concurrence events of 2022. Under long term future global warming levels of 4 °C, the concurrence, strengthened by multi-scale zonal wind resonance, is expected to persist. The mechanism evident in 2022 plays a broader and more significant role in concurrent events compared to the mechanism in 2020. Under the process of warming, resonance phenomena, as observed in 2022, are projected to become more frequent.

Reinventing Sacred Ground Amidst Natural Disaster: The Holy Islamic Tomb in Seventeenth-Century Quanzhou

The Holy Islamic Tomb at Lingshan Mountain in Quanzhou, China, is believed to be the final resting place of two of the Prophet Muhammad’s disciples who were dispatched as missionaries in the early seventh century. While prior scholarship has centred on verifying the tradition’s chronology, this article foregrounds the role of environmental actors in the tomb site’s ascent to prominence. I argue that the holy tomb (shengmu) tradition did not emerge until the late sixteenth and early seventeenth century, so its invention should be analysed alongside concurrent climate hazards that plagued late Ming China (1368–1644). Uncommon episodes of snowfall, flooding, drought, and associated famines drove Quanzhou’s local communities towards popular religious practices. Muslim visitation practices in Quanzhou, which experienced a restrained period following the decline of Mongol rule, re-emerged into universal consciousness and became integral to the city’s spiritual landscape by aligning with Chinese allegorical narratives. Through this reinvented tradition, the Holy Islamic Tomb was characterized as a site blessed by the heavens during times of cosmic disturbances. Instead of passive assimilation, through which religious identities may be diluted, the active participation of Quanzhou Muslims in local practices empowered them to elevate and honour Islamic traditions within a predominantly non-Muslim society.

Severe wildfire increased variability in the response of gross primary production to climate in an Eucalyptus dominated semi-arid woodland in South Australia

Frequency and severity of wildfires have intensified in many regions in the world. High severity fires often initiate vegetation regrowth and succession, and thus alter ecosystem processes and functioning. Understanding how high severity fire-induced variations in gross primary production (GPP) respond to climate variability is critically important. This study aimed to quantify fire-induced changes in the response of GPP to concurrent and antecedent precipitation and air temperature in a semi-arid woodland in South Australia, using MODIS derived near-infrared reflectance of vegetation (NIRv) time series data (2000–2021) and associated climate data. Additionally, the magnitude and time course of climate legacies on GPP of unburnt and severely burnt sites were determined. The results showed that fire severity increased the variability in post-fire vegetation recovery. Prior to fire disturbance, NIRv as a proxy of GPP, was predominately affected by both concurrent and antecedent precipitation. Pre-fire precipitation legacy was about 9 months. Post-fire precipitation legacy duration was shorter in the unburnt patches within fire scar (ca. 9 months) than outside the fire scar (ca. 15 months), suggesting that the unburnt patches remaining within fire scar were more vulnerable to climate change than the adjacent intact woodland. In addition, the temperature legacies varied over time, likely mediated by water availability in this woodland. Post-fire regrowth from lignotubers was not significantly affected by concurrent and antecedent climate variables, but dependent upon endogenous growth which depends on previous growth conditions. This may be due to the smaller root system which reduced the capacity for taking up rain water after the fire event when annual precipitation was relatively low. We suggest that higher temperature together with reduced and more variable precipitation in the future could induce greater uncertainty in recovery of Eucalyptus trees post-fire.

Stable isotope revealed hydroclimate transition and topography growth in the Northern Tibetan Plateau at ∼ 10 Ma

The Middle to Late Miocene uplift of the northern Tibetan Plateau had been revealed in a large amount of studies, however, its effects on hydrological and climatic evolution in Asia remains unclear due to the lack of well dated direct hydrological records in this region. Here, we report a carbonate oxygen isotope record (δ18Oc) from the western Qaidam Basin, and compare it with the δ18Oc records of five different basins in the Northern Tibetan Plateau. These data reconstruct the hydroclimatic evolution in this region and show a divergence of δ18Oc variation pattern in different basins at ∼11.5–8.5 Ma, which is different with a consistent evolution pattern of them before and after this time interval. This divergence is characterized by a significant decrease of δ18Oc in the windward locations while an increase in the leeward locations. This δ18Oc divergence was decoupling with the concurrent stable global climate, but consistent with the contemporaneous uplift of the northern Tibetan plateau. This suggests a possible link between δ18Oc divergence and topographic growth, which is further supported by a ∼ 1000 m paleoelevation increase revealed by our δ18Oc paleoelevation reconstruction. We suggest that the topography growth of the northern Tibetan Plateau especially the surrounding mountains would have facilitated water vapor transport to the windward regions, resulting in isotopic depletion in the water vapor masses. Whilst, a blocking of water vapor masses would induce aridity and increased evaporation in the leeward slopes, thus enriching heavy isotopes in precipitation there. This study corroborates the extensive uplift of the Northern Tibetan Plateau during ∼11.5–8.5 Ma from an isotopic perspective. A comparison of the obtained δ18Oc records with modern ones further suggests an establishment of modern hydroclimatic patterns in northern Tibetan Plateau at ∼8.5 Ma.

Dual stressors of infection and warming can destabilize host microbiomes.

Climate change is causing extreme heating events and intensifying infectious disease outbreaks. Animals harbour microbial communities, which are vital for their survival and fitness under stressful conditions. Understanding how microbiome structures change in response to infection and warming may be important for forecasting host performance under global change. Here, we evaluated alterations in the microbiomes of several wild Caenorhabditis elegans isolates spanning a range of latitudes, upon warming temperatures and infection by the parasite Leucobacter musarum. Using 16S rRNA sequencing, we found that microbiome diversity decreased, and dispersion increased over time, with the former being more prominent in uninfected adults and the latter aggravated by infection. Infection reduced dominance of specific microbial taxa, and increased microbiome dispersion, indicating destabilizing effects on host microbial communities. Exposing infected hosts to warming did not have an additive destabilizing effect on their microbiomes. Moreover, warming during pre-adult development alleviated the destabilizing effects of infection on host microbiomes. These results revealed an opposing interaction between biotic and abiotic factors on microbiome structure. Lastly, we showed that increased microbiome dispersion might be associated with decreased variability in microbial species interaction strength. Overall, these findings improve our understanding of animal microbiome dynamics amidst concurrent climate change and epidemics. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Interindividual variation among Culex pipiens larvae in terms of thermal response.

This study aims to determine the phenological characteristics of thermal responses in the larvae of a Culex pipiens complex field population at the individual level under the influence of thermal regime of its habitat. The analysis is based on a structured population model quantifying the thermal responses of development time and survival under variable conditions and characterising the variety between the larvae (interindividual variety). During the study performed in Turkish Thrace on a monthly basis between May 2021 and June 2022, a total of 3744 larvae were reared as peer larval cohorts and 2330 larvae as siblings in artificial containers to be fully exposed to the natural thermal condition that was recorded hourly. The development process of larvae was monitored daily from egg to adult. As a result, a total of 4788 adult mosquitoes emerged, with a development period ranging from 8 to 52 days in the females and 7 to 50 days in the males, and the survival rate was found to range from 0% to 100%. Both parameters varied by month and individuals, and the variations manifested itself, particularly in the colder periods. The results indicate that the variation between the individuals in terms of thermal response in the larvae of C. pipiens, along with the thermal acclimation ability, appears to be fate determinant in resisting fluctuating thermal regimes, surviving in concurrent climate change and adapting to new conditions with modifications in the seasonal phenology, such as maintaining reproductive dynamics throughout the winter thanks to global warming.

Recovery and resilience of European temperate forests after large and severe disturbances

AbstractRecent observations of tree regeneration failures following large and severe disturbances, particularly under warm and dry conditions, have raised concerns about the resilience of forest ecosystems and their recovery dynamics in the face of climate change. We investigated the recovery of temperate forests in Europe after large and severe disturbance events (i.e., resulting in more than 70% canopy loss in patches larger than 1 ha), with a range of one to five decades since the disturbance occurred. The study included 143 sites of different forest types and management practices that had experienced 28 disturbance events, including windthrow (132 sites), fire (six sites), and bark beetle outbreaks (five sites). We focused on assessing post‐disturbance tree density, structure, and composition as key indicators of forest resilience. We compared post‐disturbance height‐weighted densities with site‐specific pre‐disturbance densities to qualitatively assess the potential for structural and compositional recovery, overall and for dominant tree species, respectively. Additionally, we analyzed the ecological drivers of post‐windthrow tree density, such as forest management, topography, and post‐disturbance aridity, using a series of generalized additive models. The descriptive results show that European temperate forests have been resilient to past large and severe disturbances and concurrent climate conditions, albeit with lower resilience to high‐severity fire compared with other disturbance agents. Across sites and disturbance agents, the potential for structural recovery was greater than that of compositional recovery, with a large proportion of plots becoming dominated by early‐successional species after disturbance. The models showed that increasing elevation and salvage logging negatively affect post‐windthrow regeneration, particularly for late‐successional species, while pioneer species are negatively affected by increasing summer aridity. These findings provide a key baseline for assessing future recovery and resilience following the recent occurrence of widespread disturbance in the region and in anticipation of future conditions characterized by increasing heat and drought stress.

Distance to a River Modifies Climate Legacy on Vegetation Growth in a Boreal Riparian Forest

Inter-annual variability in growing season temperature and precipitation, together with snow coverage duration, determine vegetation growth in boreal ecosystems. However, little is known about the impact of concurrent and antecedent climate, particularly snow cover duration, on vegetation growth in a boreal riparian forest. Additionally, significant uncertainty exists regarding whether the distance to a river (as a proxy of groundwater availability) further modifies these climatic legacy effects on vegetation growth. To fill this knowledge gap, we quantified the responses of different vegetation types (shrub, deciduous coniferous and broadleaf forests) to concurrent and antecedent climate variables in a boreal riparian forest, and further determined the magnitude and duration of climate legacies in relation to distance to a river, using MODIS-derived NDVI time series with gridded climate data from 2001 to 2020. Results showed that higher temperature and precipitation and longer snow cover duration increased vegetation growth. For deciduous coniferous forests and broadleaf forests, the duration of temperature legacy was about one year, precipitation legacy about two years and snow cover duration legacy was 3 to 4 years. Further, distance to a river modified the concurrent and antecedent temperature and snow cover duration legacy effects on vegetation growth, but not that of precipitation. Specifically, temperature and snow cover duration legacies were shorter at the sites near a river compared to sites at greater distance to a river. Our research highlights the importance of snow cover duration on vegetation growth and that closeness to a river can buffer adverse climate impacts by shortening the strength and duration of climate legacies in a boreal riparian forest.

Effects of land use types and environmental factors on woody species diversity in agricultural landscapes of Jimma Ganati District, Western Oromia, Ethiopia

Nowadays agricultural expansion and the concurrent climate variability jointly jeopardized global biodiversity in general and plant species diversity in particular. Assessing current diversity status of different land uses is a proxy for anticipating their individualistic resilience against future climatic variability. Here we explored woody species composition, diversity, distribution, and indicator species across five agricultural land uses. For this we employed a systematic sampling design to collect phytosociological attributes of woody plant species from 103 plots in four landscapes at a regular distance following transect lines. For comparative diversity analysis, we used linear mixed effects model using the lmer function and subsequently, post hoc pairwise comparisons with the emmeans function of R software. To visualize species composition dissimilarities between the land uses, we applied NMDS ordination based on Bray-Curtis dissimilarity index and subsequently, adonis2 () function (R software) was used for testing its significance and pair-wise PERMANOVA analysis. Linear regression model and multiple regression model by Envfit function was used to test the effect of environmental topographic variables on the species distribution. The result indicated that, 104 woody plant species belonging to 52 families were collected, in which significant differences in species richness and composition among the five land use types were showed. The result reveal that, forest is with the most diversified species assemblage followed by home gardens. However, grazing land is the least in species diversity. Among topographic variables, elevation gradient shows significant influence on diversity and species compositional dissimilarity among the five agricultural land uses in which 38 species were significantly contributed to the dissimilarity of species composition. Species richness and woody stem abundance declines with increasing elevation. However, slope and aspect does not show significant effect on these attributes analysis. Indicator species assessment (IndVal.) showed that, 20 species were significantly (P ≤ 0.001) associated with at least one of the five land use classes in agricultural landscape. In sum, this study highlights that, changes in woody species diversity, composition and spatial patterns are the responses to types of land uses of varying disturbance intensities and topographic elevation as a proxy to different environmental factors.

Adapting crop production to climate change and air pollution at different scales.

Air pollution and climate change are tightly interconnected and jointly affect field crop production and agroecosystem health. Although our understanding of the individual and combined impacts of air pollution and climate change factors is improving, the adaptation of crop production to concurrent air pollution and climate change remains challenging to resolve. Here we evaluate recent advances in the adaptation of crop production to climate change and air pollution at the plant, field and ecosystem scales. The main approaches at the plant level include the integration of genetic variation, molecular breeding and phenotyping. Field-level techniques include optimizing cultivation practices, promoting mixed cropping and diversification, and applying technologies such as antiozonants, nanotechnology and robot-assisted farming. Plant- and field-level techniques would be further facilitated by enhancing soil resilience, incorporating precision agriculture and modifying the hydrology and microclimate of agricultural landscapes at the ecosystem level. Strategies and opportunities for crop production under climate change and air pollution are discussed.

Hybrid Prediction-Driven High-Throughput Sustainability Screening for Advancing Waste-to-Dimethyl Ether Valorization.

Assessing the prospective climate preservation potential of novel, innovative, but immature chemical production techniques is limited by the high number of process synthesis options and the lack of reliable, high-throughput quantitative sustainability pre-screening methods. This study presents the sequential use of data-driven hybrid prediction (ANN-RSM-DOM) to streamline waste-to-dimethyl ether (DME) upcycling using a set of sustainability criteria. Artificial neural networks (ANNs) are developed to generate in silico waste valorization experimental results and ex-ante model the operating space of biorefineries applying the organic fraction of municipal solid waste (OFMSW) and sewage sludge (SS). Aspen Plus process flowsheeting and ANN simulations are postprocessed using the response surface methodology (RSM) and desirability optimization method (DOM) to improve the in-depth mechanistic understanding of environmental systems and identify the most benign configurations. The hybrid prediction highlights the importance of targeted waste selection based on elemental composition and the need to design waste-specific DME synthesis to improve techno-economic and environmental performances. The developed framework reveals plant configurations with concurrent climate benefits (-1.241 and -2.128 kg CO2-eq (kg DME)-1) and low DME production costs (0.382 and 0.492 € (kg DME)-1) using OFMSW and SS feedstocks. Overall, the multi-scale explorative hybrid prediction facilitates early stage process synthesis, assists in the design of block units with nonlinear characteristics, resolves the simultaneous analysis of qualitative and quantitative variables, and enables the high-throughput sustainability screening of low technological readiness level processes.

Hybrid Targeted/Untargeted Screening Method for the Determination of Wildfire and Water-Soluble Organic Tracers in Ice Cores and Snow.

Wildfires can influence the earth's radiative forcing through the emission of biomass-burning aerosols. To better constrain the impacts of wildfires on climate and understand their evolution under future climate scenarios, reconstructing their chemical nature, assessing their past variability, and evaluating their influence on the atmospheric composition are essential. Ice cores are unique to perform such reconstructions representing archives not only of past biomass-burning events but also of concurrent climate and environmental changes. Here, we present a novel methodology for the quantification of five biomass-burning proxies (syringic acid, vanillic acid, vanillin, syringaldehyde, and p-hydroxybenzoic acid) and one biogenic emission proxy (pinic acid) using solid phase extraction (SPE) and ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry. This method was also optimized for untargeted screening analysis to gain a broader knowledge about the chemical composition of organic aerosols in ice and snow samples. The method provides low detection limits (0.003-0.012 ng g-1), high recoveries (74 ± 10%), and excellent reproducibility, allowing the quantification of the six proxies and the identification of 313 different molecules, mainly constituted by carbon, hydrogen, and oxygen. The effectiveness of two different sample storage strategies, i.e., re-freezing of previously molten ice samples and freezing of previously loaded SPE cartridges, was also assessed, showing that the latter approach provides more reproducible results.

El Niño and other climatic drivers of epidemic malaria in Ethiopia: new tools for national health adaptation plans

BackgroundEthiopia has a history of climate related malaria epidemics. An improved understanding of malaria–climate interactions is needed to inform malaria control and national adaptation plans.MethodsMalaria–climate associations in Ethiopia were assessed using (a) monthly climate data (1981–2016) from the Ethiopian National Meteorological Agency (NMA), (b) sea surface temperatures (SSTs) from the eastern Pacific, Indian Ocean and Tropical Atlantic and (c) historical malaria epidemic information obtained from the literature. Data analysed spanned 1950–2016. Individual analyses were undertaken over relevant time periods. The impact of the El Niño Southern Oscillation (ENSO) on seasonal and spatial patterns of rainfall and minimum temperature (Tmin) and maximum temperature (Tmax) was explored using NMA online Maprooms. The relationship of historic malaria epidemics (local or widespread) and concurrent ENSO phases (El Niño, Neutral, La Niña) and climate conditions (including drought) was explored in various ways. The relationships between SSTs (ENSO, Indian Ocean Dipole and Tropical Atlantic), rainfall, Tmin, Tmax and malaria epidemics in Amhara region were also explored.ResultsEl Niño events are strongly related to higher Tmax across the country, drought in north-west Ethiopia during the July–August–September (JAS) rainy season and unusually heavy rain in the semi-arid south-east during the October–November–December (OND) season. La Niña conditions approximate the reverse. At the national level malaria epidemics mostly occur following the JAS rainy season and widespread epidemics are commonly associated with El Niño events when Tmax is high, and drought is common. In the Amhara region, malaria epidemics were not associated with ENSO, but with warm Tropical Atlantic SSTs and higher rainfall.ConclusionMalaria–climate relationships in Ethiopia are complex, unravelling them requires good climate and malaria data (as well as data on potential confounders) and an understanding of the regional and local climate system. The development of climate informed early warning systems must, therefore, target a specific region and season when predictability is high and where the climate drivers of malaria are sufficiently well understood. An El Niño event is likely in the coming years. Warming temperatures, political instability in some regions, and declining investments from international donors, implies an increasing risk of climate-related malaria epidemics.

Protected areas under pressure: An online survey of protected area managers regarding social and environmental conservation target attainment and stakeholder conflicts

The Sustainable Development Goals (SDGs) recognize the interconnectivity between a diverse set of agendas. Identifying policies and practices that can reconcile incompatibilities across goals remains a challenge. With concurrent biodiversity and climate crises, the world faces increased pressure to find effective options for building resilience in remaining intact landscapes and ecosystems, which is critical for making progress toward several SDGs. While pressures on biodiversity and ecosystems have intensified dramatically, recent studies have shown a high geographic coincidence between important ecosystems and social conflict. Considering this, it is critical to understand how to manage Protected Areas (PAs) to effectively deliver environmental and social dividends while also minimizing or effectively managing stakeholder conflict. In this study, we present the results of an online survey of PA managers administered in 2021 to explore these themes. We conduct correlational analysis to identify patterns in survey data provided by PA managers from a variety of geographies. Building upon previous studies on the interlinkages between PA governance and social conflict, our results highlight the real challenge conflict presents for conservation efforts. Our findings also indicate that broader and more inclusive involvement of a wide range stakeholders in PA management is critical for enabling better environmental and social outcomes, but many PA managers lack the resources and support needed to effectively involve a wide array of stakeholders. Future studies should undertake case studies and qualitative work to uncover the dynamics between stakeholder conflicts, exogenous shocks, and conservation in specific contexts.

How Extreme Events in China Would Be Affected by Global Warming—Insights From a Bias‐Corrected CMIP6 Ensemble

AbstractIn recent years, concurrent climate extreme conditions (i.e., hot‐dry, cold‐dry, hot‐wet, and cold‐wet) have led to various unprecedented natural disasters (e.g., floods, landslide, wildfire, droughts, etc.), causing significant damages to human societies and ecosystems. This is especially true for China where many unprecedented natural disasters have been reported due to the recent warming in local climate. In this paper, we focus on the issue of ultra‐extreme events (1‰ threshold) and address how future global warming would affect the climate extreme conditions in China. Specifically, to reduce the uncertainties from models, we use a downscaled and bias‐corrected CMIP6 ensemble under two continuously‐warming scenarios to evaluate the impact of global warming on ultra‐extreme events over China. The results show that, under both SSP245 and SSP585 scenarios, extreme hot conditions would become dominant in most regions of China and some regions are likely to experience over 50 extreme hot days at future warming levels. The frequency of extreme cold events is projected to be small. More frequent extreme hot‐wet events with concurrence in the same month and year would be expected for China under the continuously‐warming scenarios. This is particularly obvious for the west where more than 6 hot‐wet months are likely to take place under future warming scenarios. This may imply that more extreme heat waves and flooding events would coincide in the same month or year for China in the future. For univariate ultra‐extreme events, both extreme hot events and extreme wet events would drop by above 25% from 2.0°C to 1.5°C global warming level, particularly under the SSP245 scenario. When the global mean temperature is limited to 1.5°C rather than 2°C, the avoided impacts of hot‐wet and cold‐wet extremes concurring in the same month will be larger than those of dry‐related compound extremes. Overall, the results suggest that slowing down global warming can reduce the frequency of concurrent climate extreme conditions in China, highlighting the importance of immediate action toward carbon emission reduction.

Global concurrent climate extremes exacerbated by anthropogenic climate change

Increases in concurrent climate extremes in different parts of the world threaten the ecosystem and our society. However, spatial patterns of these extremes and their past and future changes remain unclear. Here, we develop a statistical framework to test for spatial dependence and show widespread dependence of temperature and precipitation extremes in observations and model simulations, with more frequent than expected concurrence of extremes around the world. Historical anthropogenic forcing has strengthened the concurrence of temperature extremes over 56% of 946 global paired regions, particularly in the tropics, but has not yet significantly affected concurrent precipitation extremes during 1901-2020. The future high-emissions pathway of SSP585 will substantially amplify the concurrence strength, intensity, and spatial extent for both temperature and precipitation extremes, especially over tropical and boreal regions, while the mitigation pathway of SSP126 can ameliorate the increase in concurrent climate extremes for these high-risk regions. Our findings will inform adaptation strategies to alleviate the impact of future climate extremes.

Global Soil Moisture–Climate Interactions during the Peak Growing Season

Abstract Soil moisture (SM) during the vegetation growing season largely affects plant transpiration and photosynthesis, and further alters the land energy and water balance through its impact on the energy partition into latent and sensible heat fluxes. To highlight the impact of strong vegetation activity, we investigate global SM–climate interactions over the peak growing season (PGS) during 1982–2015 based on multisource datasets. Results suggest widespread positive SM–precipitation (P), SM–evapotranspiration (ET), and negative SM–temperature (T) interactions with non-negligible negative SM–P, SM–ET, and positive SM–T interactions over PGS. Relative to the influence of individual climate factors on SM, the compounding effect of climate factors strengthens SM–climate interactions. Simultaneously, variations of SM are dominated by precipitation from 50°N toward the south, by evapotranspiration from 50°N toward the north, and by temperature over the Sahara, western and central Asia, and the Tibetan Plateau. Importantly, the higher probability of concurrent SM wetness and climate extremes indicates the instant response of SM wetness to extreme climate. In contrast, the resistance of vegetation partially contributes to a consequent slower response of SM dryness to extreme climate. We highlight the significance of the compounding effects of climate factors in understanding SM–climate interaction in the context of strong vegetation activity, and the response of SM wetness and dryness to climate extremes.