Hot days induced by precipitation deficits at the global scale

Deep learning-based quantitative analyses of feedback in the land-atmosphere interactions over the Vietnamese Mekong Delta

During the past several decades, the Vietnamese Mekong Delta (VMD) has experienced many severe droughts, resulting in significant impacts on both agriculture and aquaculture. In the evolution and intensification of droughts, local feedbacks in the Land-Atmosphere (LA) interactions were considered to play a crucial role. It is critical to quantify the impact of LA variables on drought processes and severity with the feedback loop of water and energy balances (e.g., soil moisture-latent and sensible heat-precipitation). In this study, a deep learning model, named Long- and Short-term Time-series Network (LSTNet), was applied to simulate the LA interactions over the VMD. With the ERA5 data as modelling inputs, the role of each key variable (e.g., soil moisture, sensible and latent heat) in the LA interactions over the period of 2011-2020 was quantified, and the variations of their inter-relationships in the future period (2015-2099) were also investigated based on the CMIP6 data. The LSTNet model has demonstrated that the deep learning algorithm can effectively capture the relative importance of key variables in the LA interactions. We found that it is crucial to evaluate the effects of soil moisture and sensible heat on the LA interactions, particularly in the dry periods when negative anomalies in soil moisture and sensible heat would significantly reduce the amount of precipitation. In addition, the decline in soil moisture and the rise in sensible heat are anticipated to further diminish precipitation in the future under the changing climate.

Sketching the spatial disparities in heatwave trends by changing atmospheric teleconnections in the Northern Hemisphere

Pronounced spatial disparities in heatwave trends are bound up with a diversity of atmospheric signals with complex variations, including different phases and wavenumbers. However, assessing their relationships quantitatively remains a challenging problem. Here, we use a network-searching approach to identify the strengths of heatwave-related atmospheric teleconnections (AT) with ERA5 reanalysis data. This way, we quantify the close links between heatwave intensity and AT in the Northern Hemisphere. Approximately half of the interannual variability of heatwaves is explained and nearly 80% of the zonally asymmetric trend signs are estimated correctly by the AT changes in the mid-latitudes. We also uncover that the likelihood of extremely hot summers has increased sharply by a factor of 4.5 after 2000 over areas with enhanced AT, but remained almost unchanged over the areas with attenuated AT. Furthermore, reproducing Eastern European heatwave trends among various models of the Coupled Model Intercomparison Project Phase 6 largely depends on the simulated Eurasian AT changes, highlighting the potentially significant impact of AT shifts on the simulation and projection of heatwaves.

Anthropogenic forcing has increased the risk of longer-traveling and slower-moving large contiguous heatwaves

Heatwaves are consecutive hot days with devastating impacts on human health and the environment. These events may evolve across both space and time, characterizing a spatiotemporally contiguous propagation pattern that has not been fully understood. Here, we track the spatiotemporally contiguous heatwaves in both reanalysis datasets and model simulations and examine their moving patterns (i.e., moving distance, speed, and direction) in different continents and periods. Substantial changes in contiguous heatwaves have been identified from 1979 to 2020, with longer persistence, longer traveling distance, and slower propagation. These changes have been amplified since 1997, probably due to the weakening of eddy kinetic energy, zonal wind, and anthropogenic forcing. The results suggest that longer-lived, longer-traveling, and slower-moving contiguous heatwaves will cause more devastating impacts on human health and the environment in the future if greenhouse gas emissions keep rising and no effective measures are taken immediately. Our findings provide important implications for the adaption and mitigation of globally connected extreme heatwaves.

High preseason temperature variability drives convergence of xylem phenology in the Northern Hemisphere conifers

Wood growth is key to understanding the feedback of forest ecosystems to the ongoing climate warming. An increase in spatial synchrony (i.e., coincident changes in distant populations) of spring phenology is one of the most prominent climate responses of forest trees. However, whether temperature variability contributes to an increase in the spatial synchrony of spring phenology and its underlying mechanisms remains largely unknown. Here, we analyzed an extensive dataset of xylem phenology observations of 20 conifer species from 75 sites over the Northern Hemisphere. Along the gradient of increase in temperature variability in the 75 sites, we observed a convergence in the onset of cell enlargement roughly toward the 5th of June, with a convergence in the onset of cell wall thickening toward the summer solstice. The increase in rainfall since the 5th of June is favorable for cell division and expansion, and as the most hours of sunlight are received around the summer solstice, it allows the optimization of carbon assimilation for cell wall thickening. Hence, the convergences can be considered as the result of matching xylem phenological activities to favorable conditions in regions with high temperature variability. Yet, forest trees relying on such consistent seasonal cues for xylem growth could constrain their ability to respond to climate warming, with consequences for the potential growing season length and, ultimately, forest productivity and survival in the future.

Influence paradigms of soil moisture on land surface energy partitioning under different climatic conditions

Soil moisture (SM) directly controls the land surface energy partition which plays an important role in the formation of extreme weather events. However, its dependence on specific climatic conditions is not thoroughly understood due to the complexity of soil moisture effects. Here, we examine the relationship between SM and surface energy partitioning under different climate conditions, and identify the influence paradigms of soil moisture on surface energy partition. We find that temperature changes can explicitly determine the impact paradigm of different physical processes, i.e. evapotranspiration, soil freezing and thawing, and such influence paradigms are also affected by atmospheric aridity (VPD). Globally, there are five paradigms that effects on surface energy partitioning, including the warm-wet paradigm (WW), transitional paradigm (TP), warm-dry paradigm (WD), cool-wet paradigm (CW) and cold paradigm (CP). Since 1981, the global area proportion for TP is observed to increase pronouncedly. We also find that the critical SM threshold exhibits regional variations and the global average is 0.45 m3/m3. The identified paradigms and their long-term change trends provide new insights into the global intensification of land-atmosphere interaction, which has important implications for global warming and the formation of heatwaves.

Potential future changes in soil carbon dynamics in the Ziwuling Forest, China under different climate change scenarios

Soil carbon (C) cycling processes in terrestrial ecosystems are significantly influenced by global changes, and soil microorganisms play a crucial role in soil organic carbon (SOC) and its feedbacks to climate change. To investigate the potential future changes in soil C dynamics under different scenarios in the Ziwuling Forest region, China, we conducted a soil observation and sampling experiment from April 2021 to July 2022. By utilizing a microbial ecological model (MEND), we aimed to predict the future dynamics of soil C under different scenarios in the area. Our results demonstrate that under the RCP2.6 (Representative Concentration Pathway) scenario, SOC showed a rapid increase, SOC under the RCP2.6 scenario will be significantly higher than those under the RCP4.5 scenario and RCP8.5 scenario in the topsoil and whole soil. Furthermore, the positive correlation between total litter carbon (LC) and SOC under the RCP2.6 scenario highlights the potential role of total litter carbon in driving SOC dynamics. Our study also revealed that the low greenhouse gas (GHG) emission scenario favors the accumulation of SOC in the study area, while the high GHG emission scenario leads to greater soil carbon loss. Overall, these results underscore the importance of considering the impact of climate change, especially global warming, on soil ecosystems in the future. Protecting the soil ecosystem of the Loess Plateau is critical for maintaining soil carbon sinks, preventing soil erosion, and improving and regulating the surrounding environmental climate.

The severity of dry and hot climate extremes and their related impacts on vegetation in Madagascar

Madagascar is a low-income country, highly vulnerable to natural disasters affecting the small-scale subsistence farming system. Recently, climate change and environmental degradation have contributed to an intensification of food insecurity. We aim to monitor the link between dry and hot extremes on vegetation conditions, separated or concurrently, using satellite data, such as LST, ET, ET0, and FAPAR products from SEVIRI/MSG disseminated by LSASAF-EUMETSAT. The analysis was made for a long record from 2004 to 2021, focusing on the extreme seasons of 2020 and 2021. Results highlight the higher impact of combined dry and hot events when compared with isolated events, with a strong response of vegetation in the southern part of Madagascar. Results point to the added value of using the recent data records from geostationary satellites with high temporal resolution and updated in near real-time, to early detect, monitor, and characterize the impact of climate extremes on vegetation dynamics.

Decoupling between stomatal conductance and photosynthesis occurs under extreme heat in broadleaf tree species regardless of water access

High air temperatures increase atmospheric vapor pressure deficit (VPD) and the severity of drought, threatening forests worldwide. Plants regulate stomata to maximize carbon gain and minimize water loss, resulting in a close coupling between net photosynthesis (Anet ) and stomatal conductance (gs ). However, evidence for decoupling of gs from Anet under extreme heat has been found. Such a response both enhances survival of leaves during heat events but also quickly depletes available water. To understand the prevalence and significance of this decoupling, we measured leaf gas exchange in 26 tree and shrub species growing in the glasshouse or at an urban site in Sydney, Australia on hot days (maximum Tair  > 40°C). We hypothesized that on hot days plants with ample water access would exhibit reduced Anet and use transpirational cooling leading to stomatal decoupling, whereas plants with limited water access would rely on other mechanisms to avoid lethal temperatures. Instead, evidence for stomatal decoupling was found regardless of plant water access. Transpiration of well-watered plants was 23% higher than model predictions during heatwaves, which effectively cooled leaves below air temperature. For hotter, droughted plants, the increase in transpiration during heatwaves was even more pronounced-gs was 77% higher than model predictions. Stomatal decoupling was found for most broadleaf evergreen and broadleaf deciduous species at the urban site, including some wilted trees with limited water access. Decoupling may simply be a passive consequence of the physical effects of high temperature on plant leaves through increased cuticular conductance of water vapor, or stomatal decoupling may be an adaptive response that is actively regulated by stomatal opening under high temperatures. This temperature response is not yet included in any land surface model, suggesting that model predictions of evapotranspiration may be underpredicted at high temperature and high VPD.

Assessment of Ruminating, Eating, and Locomotion Behavior during Heat Stress in Dairy Cattle by Using Advanced Technological Monitoring

Heat stress (HS) significantly impacts dairy farming, prompting interest in precision dairy farming (PDF) for gauging its effects on cow health. This study assessed the influence of the Temperature-Humidity Index (THI) on rumination, eating, and locomotor activity. Various parameters, like rumination time, drinking gulps, chews per minute, and others were analyzed. The hypothesis was that precision dairy farming technology could help detect HS. Nine healthy Lithuanian Black-and-White cows were randomly selected for the trial. RumiWatch noseband sensors recorded behaviors, while SmaXtec climate sensors monitored THI. The data collection spanned from 14 June to 30 June. Cows in the THI class ≥ 72 exhibited reduced drinking time (51.16% decrease, p < 0.01), fewer chews per minute (12.9% decrease, p < 0.01), and higher activity levels (16.99% increase, p < 0.01). THI showed an inverse correlation with drinking time (r = -0.191, p < 0.05) and chews per bolus (r = -0.172, p < 0.01). Innovative technologies like RumiWatch are effective in detecting HS effects on behaviors. Future studies should explore the impact of HS on RWS biomarkers, considering factors such as lactation stage, number, yield, and pregnancy.

Soil moisture-atmosphere coupling accelerates global warming

Soil moisture-atmosphere coupling (SA) amplifies greenhouse gas-driven global warming via changes in surface heat balance. The Scenario Model Intercomparison Project projects an acceleration in SA-driven warming due to the 'warmer climate - drier soil' feedback, which continuously warms the globe and thereby exerts an acceleration effect on global warming. The projection shows that SA-driven warming exceeds 0.5 °C over extratropical landmasses by the end of the 21st Century. The likelihood of extreme high temperatures will additionally increase by about 10% over the entire globe (excluding Antarctica) and more than 30% over large parts of North America and Europe under the high-emission scenario. This demonstrates the high sensitivity of SA to climate change, in which SA can exceed the natural range of climate variability and play a non-linear warming component role on the globe.

The role of body mass in limiting post heat-coma recovery ability in terrestrial ectotherms

Under global warming, animal species show shrinking body size responses, cascading deep changes in community structure and ecosystem functions. Although the exact physiological mechanisms behind this phenomenon remain unsolved, smaller individuals may benefit from warming climate more than larger ones. Heat-coma, a physiological state with severe consequences on locomotion ability, is often considered as an "ecological death" scenario under which individuals are unable to escape and exposed to predation, further heat injury, and other hazards. Species are expected to increasingly encounter heat-coma temperature thresholds under warming climate, and body size may be an important trait for thermoregulation in particular for ectotherms. The relationship between heat-coma and shrinking body size remains, however, unclear. Yet, recovery after short-term heat-coma is possible, but little is known about its importance in thermal adaptation and how organismal size correlates with post heat-coma recovery. Here, using ants as a model system, we firstly examined the fate of heat-comatose individuals under field conditions to quantify the ecological benefits of post heat-coma recovery. Then, we quantified ants' recovery ability after heat-coma using a dynamic thermal assay in the laboratory and asked if thermal resilience varies between species with different body mass. Our results confirm that heat-coma represents an inherent ecological death where individuals failed to recover from coma suffer strong predation pressure. Additionally, following phylogenetic signals inclusion, organisms with small mass were more likely to recover, supporting the temperature-size rule in thermal adaptation and recent studies showing a decrease in body size composition of ectotherm community under warmer climatic conditions. Body size as a fundamental trait in ecology thus affects ectotherm survival under thermal stress, which may drive species body size adaptations and community composition under future warming scenarios.

The compound event that triggered the destructive fires of October 2017 in Portugal

Portugal is regularly affected by destructive wildfires that have severe social, economic, and ecological impacts. The total burnt area in 2017 (∼540,000 ha) marked the all-time record value since 1980 with a tragic toll of 114 fatalities that occurred in June and October events. The local insurance sector declared it was the costliest natural disaster in Portugal with payouts exceeding USD295 million. Here, the 2017 October event, responsible for more than 200,000 ha of burnt area and 50 fatalities is analyzed from a compound perspective. A prolonged drought led to preconditioned cumulative hydric stress of vegetation in October 2017. In addition, on 15 October 2017, two other major drivers played a critical role: 1) the passage of hurricane Ophelia off the Coast of Portugal, responsible for exceptional meteorological conditions and 2) the human agent, responsible for an extremely elevated number of negligent ignitions. This disastrous combination of natural and anthropogenic drivers led to the uncontrolled wildfires observed on 15 October.

Crown dieback and mortality of urban trees linked to heatwaves during extreme drought

Cities have been described as 'heat islands' and 'dry islands' due to hotter, drier air in urban areas, relative to the surrounding landscape. As climate change intensifies, the health of urban trees will be increasingly impacted. Here, we posed the question: Is it possible to predict urban tree species mortality using (1) species climate envelopes and (2) plant functional traits? To answer these, we tracked patterns of crown dieback and recovery for 23 common urban tree and shrub species in Sydney, Australia during the record-breaking austral 2019-2020 summer. We identified 10 heat-tolerant species including five native and five exotic species, which represent climate-resilient options for urban plantings that are likely to continue to thrive for decades. Thirteen species were considered vulnerable to adverse conditions due to their mortality, poor health leading to tree removal, and/or extensive crown dieback. Crown dieback increased with increasing precipitation of the driest month of species climate of origin, suggesting that species from dry climates may be better suited for urban forests in future climates. We effectively grouped species according to their drought strategy (i.e., tolerance versus avoidance) using a simple trait-based framework that was directly linked with species mortality. The seven most climate-vulnerable species used a drought-avoidance strategy, having low wood density and high turgor loss points along with large, thin leaves with low heat tolerance. Overall, plant functional traits were better than species climate envelopes at explaining crown dieback. Recovery after stress required two mild, wet years for most species, resulting in prolonged loss of cooling benefits as well as economic losses due to replacement of dead/damaged trees. Hotter, longer, and more frequent heatwaves will require selection of more climate-resilient species in urban forests, and our results suggest that future research should focus on plant thermal traits to improve prediction models and species selection.

Climate warming and summer monsoon breaks drive compound dry and hot extremes in India

Considering the severe impacts of compound dry and hot extremes, we examine the primary drivers of CDHEs during the summer monsoon in India. Using ERA5 reanalysis, we show that most of the CDHEs in India occur during the droughts caused by the summer monsoon rainfall deficit. Despite a decline in the frequency of summer monsoon droughts in recent decades, increased CDHEs are mainly driven by warming and dry spells during the summer monsoon particularly in the Northeast, central northeast, and west central regions. A strong land-atmospheric coupling during droughts in the summer monsoon season leads to frequent CDHEs in the Northwest and southern peninsular regions. Furthermore, regional variations in land-atmospheric coupling cause substantial differences in the CDHE occurrence in different parts of the country. Summer monsoon rainfall variability and increased warming can pose a greater risk of compound dry and hot extremes with severe impacts on various sectors in India.

Limited influence of irrigation on pre-monsoon heat stress in the Indo-Gangetic Plain

Hot extremes are anticipated to be more frequent and more intense under climate change, making the Indo-Gangetic Plain of India, with a 400 million population, vulnerable to heat stress. Recent studies suggest that irrigation has significant cooling and moistening effects over this region. While large-scale irrigation is prevalent in the Indo-Gangetic Plain during the two major cropping seasons, Kharif (Jun-Sep) and Rabi (Nov-Feb), hot extremes are reported in the pre-monsoon months (Apr-May) when irrigation activities are minimal. Here, using observed irrigation data and regional climate model simulations, we show that irrigation effects on heat stress during pre-monsoon are 4.9 times overestimated with model-simulated irrigation as prescribed in previous studies. We find that irrigation increases relative humidity by only 2.5%, indicating that irrigation is a non-crucial factor enhancing the moist heat stress. On the other hand, we detect causal effects of aerosol abundance on the daytime land surface temperature. Our study highlights the need to consider actual irrigation data in testing model-driven hypotheses related to the land-atmosphere feedback driven by human water management.

Pre-monsoon irrigation over the Indo-Gangetic Plain is often misrepresented in model-driven hypothesis. Using actual census-based data and realistic model simulations, the authors show that irrigation has limited role in enhancing heat stress in the region.

Towards species-level forecasts of drought-induced tree mortality risk

Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344-1424 mm yr^-1 ). We conducted three experiments: applying CABLE to the 2017-2019 drought; a 20% drier drought; and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO₂ ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within-species' ranges, but we also pinpointed resilience in species found in predominantly semiarid areas. The importance of the role of CO₂ in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.

The March 2012 Heat Wave in Northeast America as a Possible Effect of Strong Solar Activity and Unusual Space Plasma Interactions

In the past two decades, the world has experienced an unprecedented number of extreme weather events, some causing major human suffering and economic damage. The March 2012 heat wave is one of the most known and broadly discussed events in the Northeast United States (NE-USA). The present study examines in depth the possible influence of solar activity on the historic March 2012 heat wave based on a comparison of solar/space and meteorological data. Our research suggests that the historic March 2012 heat wave (M2012HW) and the March 1910 heat wave (M1910HW), which occurred a century earlier in NE-USA, were related to Sun-generated special space plasma structures triggering large magnetic storms. Furthermore, the largest (Dst = −222 nT) magnetic storm during solar cycle 24 in March 2015 (only three years later than the March 2012 events) occurred in relation to another heat wave (M2015HW) in NE-USA. Both these heat waves, M2012HW and M2015HW, resemble each other in many ways: they were characterized by extremely huge temperature increases ΔΤΜ = 30° and 32° (with maximum temperatures ΤΜ = 28° and 23°, respectively) during a positive North Atlantic Oscillation index, the high temperatures coincided with large-scale warm air streaming from southern latitudes, they were accompanied by superstorms caused by unexpected geoeffective interplanetary coronal mass ejections (ICMEs), and the ICME-related solar energetic particle (SEP) events were characterized by a proton spectrum extending to very high (>0.5 GeV) energies. We infer that (i) all three heat waves examined (M2012HW, M2015HW, M1910HW) were related with strong magnetic storms triggered by effective solar wind plasma structures, and (b) the heat wave in March 2012 and the related solar activity was not an accidental coincidence; that is, the M2012HW was most probably affected by solar activity. Future case and statistical studies are needed to further check the hypothesis put forward here, which might improve atmospheric models in helping people’s safety, health and life.

Two Nothofagus Species in Southernmost South America Are Recording Divergent Climate Signals

Recent climatic trends, such as warming temperatures, decrease in rainfall, and extreme weather events (e.g., heatwaves), are negatively affecting the performance of forests. In northern Patagonia, such conditions have caused tree growth reduction, crown dieback, and massive die-back events. However, studies looking at these consequences in the southernmost temperate forest (Nothofagus betuloides and Nothofagus pumilio) are much scarcer, especially in southernmost South America (SSA). These forests are also under the influence of the positive phase of Antarctic Oscillation (AAO, also known as Southern Annular Mode, SAM) that has been associated with increasing trends in temperature, drought, and extreme events in the last decades. This study evaluated the growth patterns and the climatic response of eight new tree-ring chronologies from Nothofagus species located at the upper treeline along different environmental gradients in three study areas: Punta Arenas, Yendegaia National Park, and Navarino Island in SSA. The main modes of the ring-width index (RWI) variation were studied using principal component analysis (PCA). We found that PC1 has the higher loadings for sites with precipitation values over 600 mm/yr, PC2 with N. betuloides sites, and PC3 with higher loadings for sites with precipitation values below 600 mm/yr. Our best growth-climate relationships are between N. betuloides and AAO and the most northeastern site of N. pumilio with relative humidity (which coincides with heatwaves and extreme drought). The climatic signals imprinted in the southernmost forests are sensitive to climatic variability, the climate forcing AAO, and the effects of climate change in the last decades.

Can Surface Soil Moisture Information Identify Evapotranspiration Regime Transitions?

The transition of evapotranspiration between energy- and water-limitation regimes also denotes a nonlinear change in surface water and energy coupling strength. The regime transitions are primarily dominated by available moisture in the soil, although other micro-meteorological factors also play a role. Remotely sensed soil moisture is frequently used for detecting evapotranspiration regime transitions during inter storm dry downs. However, its sampling depth does not include the entire soil profile, over which water uptake is dominated by plant root distribution. We use flux tower, surface (θ _s ; observations at 5 cm), and vertically integrated in situ soil moisture ( θ v ; 0-50 cm) observations to address the question: Can surface soil moisture robustly identify evapotranspiration regime transitions? Results demonstrate that θ _s and θ _v are hydraulically linked and have synchronized evapotranspiration regime transitions. As such, θ _s and θ _v capture comparable statistics of evapotranspiration regime prevalence, which supports the utility of remote-sensing θ _s for large-scale land-atmosphere exchange analysis.

Modeling of the air temperature using the Extreme Value Theory for selected biomes in Mato Grosso do Sul (Brazil)

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007-2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov-Smirnov test, the corrected Akaike criterion AIC c , the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R 2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28-32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00477-022-02206-1.

Evaluating the effects of water and food limitation on the life history of an insect using a multiple-stressor framework

Many environmental stressors naturally covary, and the frequency and duration of stressors such as heat waves and droughts are increasing globally with climate change. Multiple stressors may have additive or non-additive effects on fitness-related traits, such as locomotion, reproduction, and somatic growth. Despite its importance to terrestrial animals, water availability is rarely incorporated into multiple-stressor frameworks. Water limitation often occurs concurrently with food limitation (e.g., droughts can trigger famines), and the acquisition of water and food can be linked because water is necessary for digestion and metabolism. Thus, we investigated the independent and interactive effects of water and food limitation on life-history traits using female crickets (Gryllus firmus), which exhibit a wing dimorphism mediating a life-history trade-off between flight and fecundity. Our results indicate that traits vary in their sensitivities to environmental factors and factor-factor interactions. For example, neither environmental factor affected flight musculature, only water limitation affected survival, and food and water availability non-additively (i.e., interactively) influenced body and ovary mass. Water availability had a larger effect on traits than food availability, affected more traits than food availability, and mediated the effects of food availability. Further, life-history strategy influenced the costs of multiple stressors because females investing in flight capacity exhibited greater reductions in body and ovary mass during stress relative to females lacking flight capacity. Therefore, water is important in the multiple-stressor framework, and understanding the dynamics of covarying environmental factors and life history may be critical in the context of climate change characterized by concurrent environmental stressors.

Airborne GNSS Reflectometry for Water Body Detection

This article is dedicated to the study of airborne GNSS-R signal processing techniques for water body detection and edge localization using a low-altitude airborne carrier with high rate reflectivity measurements. A GNSS-R setup on-board a carrier with reduced size and weight was developed for this application. We develop a radar technique for automatic GNSS signal segmentation in order to differentiate in-land water body surfaces based on the reflectivity measurements associated to different areas of reflection. Such measurements are derived from the GNSS signal amplitudes. We adapt a transitional model to characterize the changes in the measurements of the reflected GNSS signals from one area to another. We propose an on-line/off-line change detection algorithm for GNSS signal segmentation. A real flight experimentation took place in the context of this work obtaining reflections from different surfaces and landforms. We show, using the airborne GNSS measurements obtained, that the proposed radar technique detects in-land water body surfaces along the flight trajectory with high temporal (50 Hz ) and spatial resolution (order of 10 to 100 m2). We also show that we can localize the edges of the detected water body surfaces at meter accuracy.

Disentangling increasing compound extremes at regional scale during Indian summer monsoon

Compound extremes exhibit greater adverse impacts than their univariate counterparts. Studies have reported changes in frequency and the spatial extent of extremes in India; however, investigation of compound extremes is in the infancy state. This study investigates the historical variation of compound dry and hot extremes (CDHE) and compound wet and cold extremes (CWCE) during the Indian summer monsoon period from 1951 to 2019 using monthly data. Results are analyzed for 10 identified homogeneous regions for India. Our results unravelled that CDHE (CWCE) frequency has increased (decreased) by 1-3 events per decade for the recent period (1977-2019) relative to the base period (1951-1976). Overall, the increasing (decreasing) pattern of CDHE (CWCE) is high across North-central India, Western India, North-eastern India and South-eastern coastlines. Our findings help in identification of the parts of the country affected by frequent and widespread CDHE during the recent period, which is alarming. More detailed assessments are required to disentangle the complex physical process of compound extremes to improve risk management options.

Temperature Changes and Their Impact on Drought Conditions in Winter and Spring in the Vistula Basin

Inter-annual variability of hydro-meteorological variables indirectly influence soil moisture conditions in winter and early spring seasons. The interactions between temperature changes and drought conditions are studied by an application of statistical analyses of minimum temperature (Tmin), consecutive days with temperature exceeding the 0 °C threshold value, the number of melting pulses in the winter season and Standardized Evaporation Precipitation Index (SPEI). Additionally, shifts in the onset of days with spring temperature and snow cover occurrence are analysed. A Mann–Kendall test is applied for the trend analysis. Studies have shown significant changes in thermal characteristics in the winter season over the past 70 years, which affect the moisture conditions in the Vistula River Basin. As a result of those changes, the Vistula Basin is more prone to droughts.

Compound and cascading drought impacts do not happen by chance: A proposal to quantify their relationships

The understanding of compounding and cascading impacts is becoming increasingly central to the risk reduction debate as hazard consequences are strongly coupled. Still, studies on their quantification and visualization are limited. This restricts the establishment of impact-based early warning systems. Here, a novel method for quantifying drought compound impacts and their cascading paths is presented by integrating network analysis and data mining tools. The 2018/19 drought in Germany is used as a case study. Network graphs are employed to display impact co-occurrences and cascades of agriculture, livestock, forestry, industry, and recreation impacts. Furthermore, sequential pattern mining is used to predict the next impact that is likely to take place. A synthesis of the identified relationships is presented using accessible visual formats. Results show that simultaneous and cascading drought impacts may not happen by chance but follow a pattern. Indeed, statistically significant co-occurrence associations outnumbered randomly distributed ones (91.1% versus 8.9%). With regard to the cascading paths, cross-validation results show that within three attempts, the next impact class was accurately predicted in 72.9% of the cases. Crop losses were usually followed up by a shortage of feed for livestock and consequent early slaughtering of animals. This implies that in order to limit drought impacts, there is a need to consider their compounding and cascading effects. Hence, researchers need to move from the analysis of single impacts to the understanding of how multi-sectoral impacts are connected with each other. The methodology proposed here paves towards this direction. The visualization tools used can help to increase awareness of the possible impact interactions and dependency, improving drought managers' decision-making ability. Moreover, the obtained results can serve as the basis for inferring impact causal relationships.

Global soil moisture data derived through machine learning trained with in-situ measurements

While soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0-10 cm, 10-30 cm, and 30-50 cm) at 0.25° spatial and daily temporal resolution over the period 2000-2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

Review: Can temperature be used to inform changes to flood extremes with global warming?

As climate change alters flood risk, there is a need to project changes in flooding for water resource management, infrastructure design and planning. The use of observed temperature relationships for informing changes in hydrologic extremes takes many forms, from simple proportional change approaches to conditioning stochastic rainfall generation on observed temperatures. Although generally focused on understanding changes to precipitation, there is an implied transfer of information gained from precipitation-temperature sensitivities to flooding as extreme precipitation is often responsible for flooding. While reviews of precipitation-temperature sensitivities and the non-stationarity of flooding exist, little attention has been given to the intersection of these two topics. Models which use temperature as a covariate to assess the non-stationarity of extreme precipitation outperform both stationary models and those using a temporal trend as a covariate. But care must be taken when projecting changes in flooding on the basis on precipitation-temperature sensitivities, as antecedent conditions modify the runoff response. Although good agreement is found between peak flow-temperature sensitivities and historical trends across Australia, there remains little evaluation of flood projections using temperature sensitivities globally. Significant work needs to be done before the use of temperature as a covariate for flood projection can be adopted with confidence. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Changing summer precipitation variability in the Alpine region: on the role of scale dependent atmospheric drivers

Summer precipitation totals in the Alpine Region do not exhibit a systematic trend over the last 120 years. However, we find significant low frequency periodicity of interannual variability which occurs in synchronization with a dominant two-phase state of the atmospheric circulation over the Alps. Enhanced meridional flow increases precipitation variability through positive soil moisture precipitation feedbacks on the regional scale, whereas enhanced zonal flow results in less variability through constant moisture flow from the Atlantic and suppressed feedbacks with the land surface. The dominant state of the atmospheric circulation over the Alps in these periods appears to be steered by zonal sea surface temperature gradients in the mid-latitude North Atlantic. The strength and the location of the westerlies in the mid-latitude Atlantic play an important role in the physical mechanisms linking atmosphere and oceanic temperature gradients and the meridional/zonal circulation characteristics.

Impacts of climate change on the livestock food supply chain; a review of the evidence

The potential impacts of climate change on current livestock systems worldwide are a major concern, and yet the topic is covered to a limited extent in global reports such as the ones produced by the Intergovernmental Panel on Climate Change. In this article, we review the risk of climate-related impacts along the land-based livestock food supply chain. Although a quantification of the net impacts of climate change on the livestock sector is beyond the reach of our current understanding, there is strong evidence that there will be impacts throughout the supply chain, from farm production to processing operations, storage, transport, retailing and human consumption. The risks of climate-related impacts are highly context-specific but expected to be higher in environments that are already hot and have limited socio-economic and institutional resources for adaptation. Large uncertainties remain as to climate futures and the exposure and responses of the interlinked human and natural systems to climatic changes over time. Consequently, adaptation choices will need to account for a wide range of possible futures, including those with low probability but large consequences.

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Risk results from the interaction of climate-related hazards with the exposure and vulnerability of human and natural systems.

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Climate change will impact the livestock sector throughout the food supply chain⁠—from farm production to human consumption.

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Key hazards relate to climate change trends but also, and importantly, to climate variability and climate extremes.

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Large uncertainties remain as to climate futures and the exposure and responses of the interlinked human and natural systems.

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Adaptation choices will need to account for a wide range of possible futures.

A First Assessment of the 2018 European Drought Impact on Ecosystem Evapotranspiration

The combined heatwave and drought in 2018 notably affected the state and functioning of European ecosystems. The severity and distribution of this extreme event across ecosystem types and its possible implication on ecosystem water fluxes are still poorly understood. This study estimates spatio-temporal changes in evapotranspiration (ET) during the 2018 drought and heatwave and assesses how these changes are distributed in European ecosystems along climatic gradients. We used the ET eight-day composite product from the MODerate Resolution Imaging Spectroradiometer (MODIS) together with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF ERA5). Our results indicate that ecosystem ET was strongly reduced (up to −50% compared to a 10-year reference period) in areas with extreme anomalies in surface air temperature (Tsa) and precipitation (P) in central, northern, eastern, and western Europe. Northern and Eastern Europe had prolonged anomalies of up to seven months with extreme intensities (relative and absolute) of Tsa, P, and ET. Particularly, agricultural areas, mixed natural vegetation, and non-irrigated agricultural areas were the most affected by the increased temperatures in northern Europe. Our results show contrasting drought impacts on ecosystem ET between the North and South of Europe as well as on ecosystem types.

Multidecadal variability in the Nile River basin hydroclimate controlled by ENSO and Indian Ocean dipole

Climate change impacts on the hydroclimate of the Nile River Basin (NRB) tend to be analyzed mostly based on short-term data and confined to a specific hydroclimate variable at sub-basin level. This study provides a better understanding of the hydrological cycle and the hydroclimate variability of NRB and aim to find the origin of the driving forces. Firstly, eight change point detection methods were used to investigate the abrupt changes in the NRB hydroclimate. Next, we used wavelet transform coherence (WTC), spatial correlation, and detrended cross-correlation (DCCA) to analyze the inter-annual to multidecadal variabilities of the hydroclimate of NRB because they are effective in capturing the temporal variability at multiple scales. Our results show significant hydroclimatic changes and trends attributed to climate change impact after the 1970s. For instance, precipitation and relative humidity (RH) decreasing at 16.2 mm/decade and 0.3 5%/decade, respectively. In contrast, geopotential height (GPH), climate warming, wind speed and zonal wind stress increasing at 3.1 m/decade, 0.19 °C/decade, 0.02 m/decade and 1.51 m²/s²/decade, respectively. These observed changes are strongly linked to El Niño and Indian Ocean Dipole (IOD). Our results also indicate that the largely strengthened IOD and El Niño amplitudes since the 1970s controlled the multidecadal variability of NRB's hydroclimate. In addition to ENSO-induced warming in NRB, El Niño exhibited a strong negative (positive) influence on precipitation and RH (GPH, surface temperature, wind speed, AET) over lowlands of Ethiopia, Kenya, Uganda, Sudan, Eritrea, Rwanda, and Burundi over the past 70 years. Our analysis revealed that IOD can either intensify or decrease the impacts of El Niño on the NRB's hydroclimate. For instance, IOD have a greater negative influence on the precipitation variability over Sudan, Ethiopia, Congo, Egypt, and Eritrea. These results were further confirmed by the changes in atmospheric circulation patterns in NRB during active El Niño and La Niño episodes. The increase in GPH anomalies associated with El Niño warming indicates a greater saturation vapor pressure, which at lower levels cause a lower dew point and a higher surface temperature. In addition, El Niño-driven changes to vector and meridional wind patterns created a strong anti-cyclonic wave of dry air that keeps moving dry air into the NRB. These waves propagate southward towards the NRB, controlling the circulation of air mass, heat, and moisture fluxes and affect the surface weather patterns of NRB.

A global database of plant production and carbon exchange from global change manipulative experiments

Numerous ecosystem manipulative experiments have been conducted since 1970/80 s to elucidate responses of terrestrial carbon cycling to the changing atmospheric composition (CO₂ enrichment and nitrogen deposition) and climate (warming and changing precipitation regimes), which is crucial for model projection and mitigation of future global change effects. Here, we extract data from 2,242 publications that report global change manipulative experiments and build a comprehensive global database with 5,213 pairs of samples for plant production (productivity, biomass, and litter mass) and ecosystem carbon exchange (gross and net ecosystem productivity as well as ecosystem and soil respiration). Information on climate characteristics and vegetation types of experimental sites as well as experimental facilities and manipulation magnitudes subjected to manipulative experiments are also included in this database. This global database can facilitate the estimation of response and sensitivity of key terrestrial carbon-cycling variables under future global change scenarios, and improve the robust projection of global change‒terrestrial carbon feedbacks imposed by Earth System Models.

Measurement(s)	organic material • plant production • carbon exchange
Technology Type(s)	digital curation
Factor Type(s)	climate characteristics • vegetation traits
Sample Characteristic - Environment	climate system
Sample Characteristic - Location	global

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12932843

More frequent and widespread persistent compound drought and heat event observed in China

Compound drought and heat event (CDHE) causes severe impacts on agriculture, ecosystem, and human health. Based on daily maximum surface air temperature and meteorological drought composite index data in China, changing features of CDHEs in warm season from 1961 to 2018 is explored at a daily time scale based on a strict and objective definition in this study. Results reveal that CDHEs have occurred more frequently and widely in China, especially since the late 1990s. Notably, such changes are more obvious in Southwest China, eastern Northwest China, northern North China, and the coastal area of southeastern China. A prominent feature is that persistent CDHEs on a daily scale have increased significantly. To better understand climate change of compound extreme events, further studies on the physical mechanism, especially attribution analyses at a regional scale, are urgently needed.

A century of observations reveals increasing likelihood of continental-scale compound dry-hot extremes

Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

Drought severity and all-cause mortality rates among adults in the United States: 1968-2014

BACKGROUND

Little is known about the effect of drought on all-cause mortality, especially in higher income countries such as the United States. As the frequency and severity of droughts are likely to increase, understanding the connections between drought and mortality becomes increasingly important.

METHODS

Our exposure variable was an annual cumulative drought severity score based on the 1-month, county-level Standardized Precipitation Evapotranspiration Index. The outcome variables of demographic subgroup-specific all-cause mortality count data per year were obtained from the National Vital Statistics System. Any counts below 10 deaths were censored in that demographic group per county. We modeled county-stratum-year mortality using interval-censored negative binomial regression with county-level random intercepts, for each combined age-race-sex stratum either with or without further stratification by climate regions. Fixed effects meta-regression was used to test the associations between age, race, sex, and region with the drought-mortality regression coefficients. Predictive margins were then calculated from the meta-regression model to estimate larger subgroup (e.g., 'race' or 'sex') associations of drought with mortality.

RESULTS

Most of the results were null for associations between drought severity and mortality, across joint strata of race, age, sex and region, but incidence rate ratios (IRRs) for 17 subgroups were significant after accounting for the multiple testing; ten were < 1 indicating a possible protective effect of drought on mortality for that particular subpopulation. The meta-regression indicated heterogeneity in the association of drought with mortality according to race, climate region, and age, but not by sex. Marginal means of the estimated log-incidence rate ratios differed significantly from zero for age groups 25-34, 35-44, 45-54 and 55-64; for the white race group; and for the South, West and Southwest regions, in the analysis that included wet county-years. The margin of the meta-regression model suggested a slightly negative, but not statistically significant, association of drought with same-year mortality in the overall population.

CONCLUSIONS

There were significant, heterogeneous-direction associations in subpopulation-stratified models, after controlling for multiple comparisons, suggesting that the impacts of drought on mortality may not be monolithic across the United States. Meta-regression identified systematic differences in the associations of drought severity with all-cause mortality according to climate region, race, and age. These findings suggest there may be important contextual differences in the effects of drought severity on mortality, motivating further work focused on local mechanisms. We speculate that some of the estimated negative associations of drought severity with same-year mortality could be consistent with either a protective effect of drought on total mortality in the same year, or with a delayed health effect of drought beyond the same year. Further research is needed to clarify associations of drought with more specific causes of death and with sublethal health outcomes, for specific subpopulations, and considering lagged effects occurring beyond the same year as the drought.

Improving the Processes in the Land Surface Scheme TERRA: Bare Soil Evaporation and Skin Temperature

Newly improved formulations of the bare soil evaporation and the surface temperature are presented, using the multilayer land surface scheme TERRA of the Consortium for Small-scale Modeling (COSMO) atmospheric model. The simulations were carried out in offline mode with atmospheric forcing data from the Meteorological Observatory Lindenberg–Richard-Aßmann-Observatory of the German Meteorological Service. The results show that the bare soil evaporation simulated by the reference version of TERRA is substantially overestimated under wet conditions, and underestimated under dry conditions. Furthermore, the amplitude of the diurnal cycle of the surface temperature is systematically underestimated. In contrast, the diurnal cycles of the temperatures in the soil are overestimated instead. The new description of the bare soil evaporation in TERRA is based on a resistance formulation analogue to Ohm’s law, while the surface temperature is now based on the skin temperature formulation by Viterbo and Beljaars. The new formulation improves the simulated bare soil evaporation substantially. In particular, the overestimation under wet conditions is reduced, also acting against an extensive drying of the soil during the annual cycle. Additionally, the underestimation under dry conditions is reduced as well. Furthermore, the simulated amplitude of the diurnal cycle of the surface temperature is substantially increased. In particular, a nocturnal warm bias is systematically reduced. In addition to this, the new formulations were also applied in coupled mode in the COSMO model, resulting in improved diurnal cycles of near-surface temperature and dew point.

Emerging Advanced Technologies to Mitigate the Impact of Climate Change in Africa

Agriculture remains critical to Africa's socioeconomic development, employing 65% of the work force and contributing 32% of GDP (Gross Domestic Product). Low productivity, which characterises food production in many Africa countries, remains a major concern. Compounded by the effects of climate change and lack of technical expertise, recent reports suggest that the impacts of climate change on agriculture and food systems in African countries may have further-reaching consequences than previously anticipated. Thus, it has become imperative that African scientists and farmers adopt new technologies which facilitate their research and provide smart agricultural solutions to mitigating current and future climate change-related challenges. Advanced technologies have been developed across the globe to facilitate adaptation to climate change in the agriculture sector. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9), synthetic biology, and genomic selection, among others, constitute examples of some of these technologies. In this work, emerging advanced technologies with the potential to effectively mitigate climate change in Africa are reviewed. The authors show how these technologies can be utilised to enhance knowledge discovery for increased production in a climate change-impacted environment. We conclude that the application of these technologies could empower African scientists to explore agricultural strategies more resilient to the effects of climate change. Additionally, we conclude that support for African scientists from the international community in various forms is necessary to help Africans avoid the full undesirable effects of climate change.

Predominant regional biophysical cooling from recent land cover changes in Europe

Around 70 Mha of land cover changes (LCCs) occurred in Europe from 1992 to 2015. Despite LCCs being an important driver of regional climate variations, their temperature effects at a continental scale have not yet been assessed. Here, we integrate maps of historical LCCs with a regional climate model to investigate air temperature and humidity effects. We find an average temperature change of −0.12 ± 0.20 °C, with widespread cooling (up to −1.0 °C) in western and central Europe in summer and spring. At continental scale, the mean cooling is mainly correlated with agriculture abandonment (cropland-to-forest transitions), but a new approach based on ridge-regression decomposing the temperature change to the individual land transitions shows opposite responses to cropland losses and gains between western and eastern Europe. Effects of historical LCCs on European climate are non-negligible and region-specific, and ignoring land-climate biophysical interactions may lead to sub-optimal climate change mitigation and adaptation strategies.

Land cover change contributes to regional climate trends. Here, the authors use high-resolution land cover maps and state-of-the-art climate modelling to assess land cover change effects across Europe over 1992-2015, showing widespread cooling after agricultural abandonment but also different, region-specific effects.

Anthropogenically-driven increases in the risks of summertime compound hot extremes

Compared to individual hot days/nights, compound hot extremes that combine daytime and nighttime heat are more impactful. However, past and future changes in compound hot extremes as well as their underlying drivers and societal impacts remain poorly understood. Here we show that during 1960-2012, significant increases in Northern Hemisphere average frequency (~1.03 days decade^-1) and intensity (~0.28 °C decade^-1) of summertime compound hot extremes arise primarily from summer-mean warming. The forcing of rising greenhouse gases (GHGs) is robustly detected and largely accounts for observed trends. Observationally-constrained projections suggest an approximate eightfold increase in hemispheric-average frequency and a threefold growth in intensity of summertime compound hot extremes by 2100 (relative to 2012), given uncurbed GHG emissions. Accordingly, end-of-century population exposure to compound hot extremes is projected to be four to eight times the 2010s level, dependent on demographic and climate scenarios.

The impact of drought spells on forests depends on site conditions: The case of 2017 summer heat wave in southern Europe

A major component of climate change is an increase in temperature and precipitation variability. Over the last few decades, an increase in the frequency of extremely warm temperatures and drought severity has been observed across Europe. These warmer and drier conditions may reduce productivity and trigger compositional shifts in forest communities. However, we still lack a robust, biogeographical characterization of the negative impacts of climate extremes, such as droughts on forests. In this context, we investigated the impact of the 2017 summer drought on European forests. The normalized difference vegetation index (NDVI) was used as a proxy of forest productivity and was related to the standardized precipitation evapotranspiration index, which accounts for the temperature effects of the climate water balance. The spatial pattern of NDVI reduction in 2017 was largely driven by the extremely warm summer for parts of the central and eastern Mediterranean Basin (Italian and Balkan Peninsulas). The vulnerability to the 2017 summer drought was heterogeneously distributed over Europe, and topographic factors buffered some of the negative impacts. Mediterranean forests dominated by oak species were the most negatively impacted, whereas Pinus pinaster was the most resilient species. The impact of drought on the NDVI decreased at high elevations and mainly on east and north-east facing slopes. We illustrate how an adequate characterization of the coupling between climate conditions and forest productivity (NDVI) allows the determination of the most vulnerable areas to drought. This approach could be widely used for other extreme climate events and when considering other spatially resolved proxies of forest growth and health.

Warming of hot extremes alleviated by expanding irrigation

Irrigation affects climate conditions - and especially hot extremes - in various regions across the globe. Yet how these climatic effects compare to other anthropogenic forcings is largely unknown. Here we provide observational and model evidence that expanding irrigation has dampened historical anthropogenic warming during hot days, with particularly strong effects over South Asia. We show that irrigation expansion can explain the negative correlation between global observed changes in daytime summer temperatures and present-day irrigation extent. While global warming increases the likelihood of hot extremes almost globally, irrigation can regionally cancel or even reverse the effects of all other forcings combined. Around one billion people (0.79-1.29) currently benefit from this dampened increase in hot extremes because irrigation massively expanded throughout the 20[Formula: see text] century. Our results therefore highlight that irrigation substantially reduced human exposure to warming of hot extremes but question whether this benefit will continue towards the future.

Coupling of Soil Moisture and Air Temperature from Multiyear Data During 1980–2013 over China

Soil moisture is an important parameter in land surface processes, which can control the surface energy and water budgets and thus affect the air temperature. Studying the coupling between soil moisture and air temperature is of vital importance for forecasting climate change. This study evaluates this coupling over China from 1980–2013 by using an energy-based diagnostic method, which represents the momentum, heat, and water conservation equations in the atmosphere, while the contributions of soil moisture are treated as external forcing. The results showed that the soil moisture–temperature coupling is strongest in the transitional climate zones between wet and dry climates, which here includes Northeast China and part of the Tibetan Plateau from a viewpoint of annual average. Furthermore, the soil moisture–temperature coupling was found to be stronger in spring than in the other seasons over China, and over different typical climatic zones, it also varied greatly in different seasons. We conducted two case studies (the heatwaves of 2013 in Southeast China and 2009 in North China) to understand the impact of soil moisture–temperature coupling during heatwaves. The results indicated that over areas with soil moisture deficit and temperature anomalies, the coupling strength intensified. This suggests that soil moisture deficits could lead to enhanced heat anomalies, and thus, result in enhanced soil moisture coupling with temperature. This demonstrates the importance of soil moisture and the need to thoroughly study it and its role within the land–atmosphere interaction and the climate on the whole.

Disentangling Drivers of Meteorological Droughts in the European Greater Alpine Region During the Last Two Centuries

This study investigates the atmospheric drivers of severe precipitation deficits in the Greater Alpine Region during the last 210 years utilizing a daily atmospheric circulation type reconstruction. Precipitation deficit tends to be higher during periods with more frequent anticyclonic (dry) and less frequent cyclonic (wet) circulation types, as would be expected. However, circulation characteristics are not the main drivers of summer precipitation deficit. Dry soils in the warm season tend to limit precipitation, which is particularly the case for circulation types that are sensitive to a soil moisture-precipitation feedback. This mechanism is of specific relevance in explaining the major drought decades of the 1860s and 1940s. Both episodes show large negative precipitation anomalies in spring followed by increasing frequencies of circulation types sensitive to soil moisture precipitation feedbacks. The dry springs of the 1860s were likely caused by circulation characteristics that were quite different from those of recent decades as a consequence of the large spatial extent of Arctic sea ice at the end of the Little Ice Age. On the other hand, the dry springs of the 1940s developed under a persistent positive pressure anomaly across Western and Central Europe, triggered by positive sea surface temperatures in the western subtropical Atlantic.

Countrywide climate features during recorded climate-related disasters

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ^∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ^∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.

Nature-based solutions for hydro-meteorological hazards: Revised concepts, classification schemes and databases

Hydro-meteorological hazards (HMHs) have had a strong impact on human societies and ecosystems. Their impact is projected to be exacerbated by future climate scenarios. HMHs cataloguing is an effective tool to evaluate their associated risks and plan appropriate remediation strategies. However, factors linked to HMHs origin and triggers remain uncertain, which pose a challenge for their cataloguing. Focusing on key HMHs (floods, storm surges, landslides, droughts, and heatwaves), the goal of this review paper is to analyse and present a classification scheme, key features, and elements for designing nature-based solutions (NBS) and mitigating the adverse impacts of HMHs in Europe. For this purpose, we systematically examined the literature on NBS classification and assessed the gaps that hinder the widespread uptake of NBS. Furthermore, we critically evaluated the existing literature to give a better understanding of the HMHs drivers and their interrelationship (causing multi-hazards). Further conceptualisation of classification scheme and categories of NBS shows that relatively few studies have been carried out on utilising the broader concepts of NBS in tackling HMHs and that the classification and effectiveness of each NBS are dependent on the location, architecture, typology, green species and environmental conditions, as well as interrelated non-linear systems. NBS are often more cost-effective than hard engineering approaches used within the existing systems, especially when taking into consideration their potential co-benefits. We also evaluated the sources of available data for HMHs and NBS, highlighted gaps in data, and presented strategies to overcome the current shortcomings for the development of the NBS for HMHs. We highlighted specific gaps and barriers that need to be filled since the uptake and upscaling studies of NBS in HMHs reduction is rare. The fundamental concepts and the key technical features of past studies reviewed here could help practitioners to design and implement NBS in a real-world situation.