Global Land Area Research Articles

Assessing the stability of terrestrial water storage to drought based on CMIP6 forcing scenarios

Assessing the stability of terrestrial water storage (TWS) under drought conditions is critical for the sustainable development of water resources. In this study, we integrated surface temperature (ST), leaf area index (LAI), and precipitation (P) data from five different scenarios (History, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to develop a standardized temperature vegetation precipitation index (STVPI). The index was then utilized to monitor global drought conditions and investigate the stability of TWS to drought disaster. The results showed that STVPI can not only monitor meteorological drought, but also has a remarkable sensitivity and applicability to drought caused by sparse vegetation. Notably, 21.16% of the global land area will have a drought trend under the SSP1-2.6 scenario, while it will rise to 35.81% under the SSP5-8.5 scenario, which underscored the potential for an expansion of drought-affected regions worldwide as a result of ongoing global warming and escalating emissions. In addition, the results also found that the warm temperate and tropical regions at lower elevations have an advantage in maintaining the stability of TWS. Unfortunately, the stability of TWS to drought will decline in the western Sahara Desert, central China and northern United States in the future, where will face a serious water crisis. The research framework provides an important reference for deeply evaluating and scientifically allocating water resources under climate change.

Uncertainty in model estimates of global groundwater depth

Abstract Knowing the depth at which groundwater can be found below the land surface is critical for understanding its potential accessibility by ecosystems and society. Uncertainty in global scale water table depth (WTD) limits our ability to assess groundwater’s role in a water cycle altered by changing climate, land cover, and human water use. Global groundwater models offer a top–down pathway to gain this knowledge, but their uncertainty is currently poorly quantified. Here, we investigate four global groundwater models and reveal steady-state WTD disagreements of more than 100 m for one-third of the global land area. We find that model estimates of land areas with shallow groundwater at <10 m depth vary from 10% to 71% (mean of 23%). This uncertainty directly translates into subsequent assessments, as land areas with potential groundwater accessibility for forests, population, and areas equipped for irrigation, differ substantially depending on the chosen model. We explore reasons for these differences and find that contrary to observations, 3 out of 4 models show deeper water tables in humid than in arid climates and greatly overestimate how strongly topographic slope controls WTD. These results highlight substantial uncertainty associated with any global-scale groundwater analysis, which should be considered and ultimately reduced.

Advanced photovoltaic technology can reduce land requirements and climate impact on energy generation

Future changes in solar radiation and rising temperatures will likely reduce global solar photovoltaic potential, but advancing photovoltaic technologies could counteract these effects. We investigate the potential of photovoltaic to satisfy energy demands given climate change and technological development. We find that conventional photovoltaic will require 0.5 to 1.2% of global land area to meet projected energy demands by 2085 without accounting for climate change effects. When considering climate impacts, this requirement increases to 0.7–1.5% of the global land area. However, utilising advanced photovoltaic technologies can reduce this area to 0.3–1.2%, effectively mitigating climate impacts. Regional climate change impacts vary substantially, resulting in photovoltaic potential decreases of up to 3% in Latin America and the Caribbean, and by up to 8% in South Asia. Our results suggest that technology-driven increases in future global photovoltaic energy production can more than compensate for the climate related reductions.

A New, Zero-Iteration Analytic Implementation of Wet-Bulb Globe Temperature: Development, Validation, and Comparison With Other Methods.

Wet-bulb globe temperature (WBGT)-a standard measure for workplace heat stress regulation-incorporates the complex, nonlinear interaction among temperature, humidity, wind and radiation. This complexity requires WBGT to be calculated iteratively following the recommended approach developed by Liljegren and colleagues. The need for iteration has limited the wide application of Liljegren's approach, and stimulated various simplified WBGT approximations that do not require iteration but are potentially seriously biased. By carefully examining the self-nonlinearities in Liljegren's model, we develop a zero-iteration analytic approximation of WBGT while maintaining sufficient accuracy and the physical basis of the original model. The new approximation slightly deviates from Liljegren's full model-by less than 1°C in 99% cases over 93% of global land area. The annual mean and 75%-99% percentiles of WBGT are also well represented with biases within °C globally. This approximation is clearly more accurate than other commonly used WBGT approximations. Physical intuition can be developed on the processes controlling WBGT variations from an energy balance perspective. This may provide a basis for applying WBGT to understanding the physical control of heat stress.

Global decline in microbial-derived carbon stocks with climate warming and its future projections

Abstract Soil organic carbon (SOC) represents the largest terrestrial pool of organic carbon and is indispensable for mitigating climate change and sustaining soil fertility. As a major component of stable SOC, microbial-derived carbon (MDC) accounts for approximately half of the total SOC and has repercussions on climate feedback. However, our understanding of the spatial and temporal dynamics of MDC stocks is limited, hindering assessments of the long-term impacts of global warming on persistent SOC sequestration in the soil‒atmosphere C cycle. Here, we compiled an extensive global dataset and employed ensemble machine learning techniques to forecast the spatial-temporal dynamics of MDC stocks across 93.4% of the total global land area from 1981 to 2018. Our findings revealed that for every 1°C increase in temperature, there was a global decrease of 6.7 Pg in the soil MDC stock within the predictable areas, equivalent to 1.4% of the total MDC stock or 0.9% of the atmospheric C pool. The tropical regions experienced the most substantial declines in MDC stocks. We further projected future MDC stocks for the next century based on shared socioeconomic pathways, showing a global decline in MDC stocks with a potential 6–37 Pg reduction by 2100 depending on future pathways. We recommend integrating the response of MDC stocks to warming into socioeconomic models to enhance confidence in selecting sustainable pathways.

Assessing the Impacts of Falling Ice Radiative Effects on the Seasonal Variation of Land Surface Properties

AbstractThe impacts of falling ice radiative effects (FIREs) on land‐atmosphere feedback processes were examined, with a focus on the fidelity of land surface properties and their variability as inferred by global climate models (GCMs). We conducted a pair of sensitivity experiments using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 1 (CESM1) in fully coupled modes with FIREs turned on and off. This allowed us to investigate the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature (LST) associated with FIREs across global land areas. Our findings indicate that during boreal winter, excluding FIREs results in less surface downward longwave and net flux (∼5–15 Wm−2), leading to a colder land surface (∼2–4 K) and air temperatures (∼1–4 K) at mid‐ and high latitudes. Consequently, the surface frozen soil layer and snow cover persist through spring, delaying snowmelt and thawing until summer. This delay reduces liquid soil moisture, thereby suppressing vegetation productivity in subsequent seasons. Conversely, tropical regions, exhibit contrasting responses, with a warmer land surface (∼0.5 K) and warmer air temperatures (∼0.1–0.5 K) due to increased surface downward shortwave and net flux (∼2–10 Wm−2). This enhancement in radiation fosters increased vegetation productivity throughout the seasonal cycle. These findings illustrate a local response of land surface properties to changes in the surface energy balance and LST, highlighting the significant role that FIREs play in land surface modeling within GCMs.

Vegetation increases global climate vulnerability risk by shifting climate zones in response to rising atmospheric CO2

Global climate zones are experiencing widespread shifts with ongoing rise in atmospheric CO2, influencing vegetation growth and shifting its distributions to challenge ecosystem structure and function, posing threats on ecological and societal safety. However, how rising atmospheric CO2 affects the pace of global climate zone shifts is highly uncertain. More attentions are urgently required to understand the underlying mechanisms and quantifications of regional climate vulnerability in response to rising CO2. In this study, we employ nine Earth system models from CMIP6 to investigate global climate zone shifts with rising CO2, unravel the effects of vegetation physiological response (PHY), and categorize climate vulnerable regions depending on the extent of climate zone shifts. We find that climate zone shifts over half of the global land area, 16.8% of which is contributed by PHY at 4 × CO2. Intriguingly, besides warming, PHY-induced precipitation changes and their interactions with warming dominate about two-fifths of PHY-forced shifts, providing potential direction for model improvement in future predictions of climate zone shifts. Aided with PHY effects, 4 × CO2 imposes substantial climate zone shifts over about one-fifth of the global land area, suggesting substantial changes in local climate and ecosystem structure and functions. Hence, those regions would experience strong climate vulnerability, and face high risk of climate extremes, water scarcity and food production. Our results quantitatively identify the vulnerable regions and unravel the underlying drivers, providing scientific insights to prioritize conservation and restoration efforts to ensure ecological and social safety globally.

Continuous wildfires threaten public and ecosystem health under climate change across continents

Wildfires burn approximately 3%–4% of the global land area annually, resulting in massive emissions of greenhouse gases and air pollutants. Over the past two decades, there has been a declining trend in both global burned area and wildfire emissions. This trend is largely attributed to a decrease in wildfire activity in Africa, which accounts for a substantial portion of the total burned area and emissions. However, the northern high-latitude regions of Asia and North America have witnessed substantial interannual variability in wildfire activity, with several severe events occurring in recent years. Climate plays a pivotal role in influencing wildfire activity and has led to more wildfires in high-latitude regions. These wildfires pose significant threats to climate, ecosystems, and human health. Given recent changes in wildfire patterns and their impacts, it is critical to understand the contributors of wildfires, focus on deteriorating high-latitude areas, and address health risks in poorly managed areas to mitigate wildfire effects.

Soil Moisture‐Temperature Coupling Increases Population Exposure to Future Heatwaves

AbstractHeatwaves have significant effects on ecosystems and human health. Human habitability is impacted severely as human exposure to heatwaves is projected to increase, however, the contribution of soil moisture effects to the increased exposure is unknown. We use data from four climate models, in which two experiments are used to isolate soil moisture effects and in this way to examine projected changes of soil moisture contributions to projected increases in heatwave events. Contributions from soil moisture to future population exposure to heatwaves are also investigated. With soil moisture effects combined with global warming, the longest yearly heatwaves are found to increase by up to 20 days, intensify by up to 2°C in mean temperature, with an increasing of frequency by 15% (the percentage relative to the total number of days for a year) over most mid‐latitude land regions by 2040–2070 under the SSP585 high emissions scenario. Furthermore, soil moisture changes are found to have a significant role in projected increases of multiple heatwave characteristics regionally compared with the global land area and contribute to more global population exposed to heatwaves.

A scalable big data approach for remotely tracking rangeland conditions

Rangelands, covering half of the global land area, are critically degraded by unsustainable use and climate change. Despite their extensive presence, global assessments of rangeland condition and sustainability are limited. Here we introduce a novel analytical approach that combines satellite big data and statistical modeling to quantify the likelihood of changes in rangeland conditions. These probabilities are then used to assess the effectiveness of management interventions targeting rangeland sustainability. This approach holds global potential, as demonstrated in Mongolia, where the shift to a capitalist economy has led to increased livestock numbers and grazing intensity. From 1986 to 2020, heavy grazing caused a marked decline in Mongolia’s rangeland condition. Our evaluation of diverse management strategies, corroborated by local ground observations, further substantiates our approach. Leveraging globally available yet locally detailed satellite data, our proposed condition tracking approach provides a rapid, cost-effective tool for sustainable rangeland management.

A high-quality global elevation control point dataset from ICESat-2 altimeter data

ABSTRACT The ICESat-2 satellite equipped with a new photon-counting laser altimeter has received much attention as a source of accurate elevation observations. However, in this research field, there is a lack of an open-source high-accuracy elevation control point dataset with the specific quality requirements at a global scale. To this end, using ICESat-2 altimeter data as the main data source, we constructed and organized a dataset as a useful supplement for this research field. The dataset was generated by a methodology based on detection environment evaluation, photon spatial analysis, and the redundant observation statistics. The dataset includes more than 600 million elevation control points and covers the global land areas, except for Greenland and Antarctica. The dataset has been validated by multiple digital elevation models (DEMs) from around the world (sourced from airborne LiDAR data). The results show that the dataset has high-accuracy elevation control points. The overall root-mean-square error (RMSE) of the original elevations of ICESat-2 is about 1.384–4.820 m, but the overall RMSE of the elevation control points in the new dataset is about 0.279–0.642 m. Moreover, the results obtained in this study show that the dataset is suitable for application within high vegetation cover areas.

Changes in the severity of compound hot-dry-windy events over global land areas

Hot-dry-windy events (HDWEs), characterized by concurrent high temperature, low humidity, and strong wind speeds, are associated with reduced crop yields, accelerated spread of wildfire, increased human health risks, and dust storms across various regions. A comprehensive understanding of global HDWE severity is crucial for mitigating these detrimental consequences. However, current assessments of HDWE show notable regional constraints due to the lack of a universal definition for its severity. In this study, we introduce a standardized hot-dry-windy index (SHDWI) using multi-source datasets to assess spatial and temporal changes in the severity of HDWEs across the globe. Influenced by significantly rising temperatures, intensified wind speeds, and declining humidity, a notable decreasing trend (-0.09/decade, p < 0.01) in SHDWI indicates a rise in warm-season HDWE severity on average across the global land areas, particularly in South America, North Africa, western Europe, and southeastern Asia. Geospatially, Europe, Africa, South America, and Asia have experienced substantial increases in HDWE severity and expanded areas affected by strong HDWEs between 1980–1998 and 1999–2017. Notably, HDWE severity is predominated by temperature in the south of 30°N but by humidity in the north of 30°N. The standardized index proposed in this study would be beneficial for a worldwide assessment of future HDWE risks under climate change.

The Timing of Detectable Increases in Seasonal Soil Moisture Droughts Under Future Climate Change

AbstractGlobal warming exacerbates the increase of soil moisture drought by accelerating the water cycle, posing potential threats to food security and ecological sustainability. The design of drought prevention and mitigation policies should be based on the reliable detection of the future change signal in droughts, so it is critical to know when the signal can be detected (Time of Emergence, ToE) in the background noise of the climate system. While the ToE framework has been successfully applied for temperature‐related signal detection, the ToE for changes in drought has not been well studied. Based on 66 Coupled Model Intercomparison Project Phase 6 model ensemble members under four Shared Socio‐economic Pathways, we conduct a global ToE analysis of seasonal soil moisture drought characteristics and discuss the impact of different warming levels. Six subregions with robust increase in soil moisture droughts are identified. For drought frequency, most of the subregion's ToE is centered around 2080, however for drought intensity it is much earlier and can even reach around 2040 in AMZ. For drought frequency and drought intensity, approximately 14%–22% and 47%–49% of global land areas would reach ToE in 21st century. The global land areas with ToE of increasing droughts would increase by at least 1/5 when global warming level is kept to 2°C rather than 1.5°C above pre‐industrial conditions. This suggests that limiting global warming can significantly delay the emergence time of increases in seasonal soil moisture droughts, allowing additional adaptation time for the drought‐related sectors.

Future changes in global rainfall erosivity: Insights from the precipitation changes

Quantifying future changes in rainfall erosivity is essential to address potential water erosion risks. This study reveals a significant power function relationship between rainfall erosivity and precipitation both globally and across various climatic zones. Building on this foundation, new empirical models were developed to project relative changes in rainfall erosivity. These models, predicted on the understanding that General Circulation Models (GCMs) provide more accurate predictions of climate change trends than exact meteorological values, utilizes the ratio of modeled historical precipitation to future precipitation under various scenarios as the variable, formulated as a power function. Data from three GCMs runs from both the Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP6–including historical, mid-term, and long-term periods–were employed. The analysis suggests that by the end of the 21st century, global annual rainfall erosivity could increase by 2.6% under the Shared Socio-Economic Pathway (SSP)1–2.6 scenario, by 3.5% under SSP2-4.5, and by a significant 6.4% under SSP5-8.5, relative to the 2000–2010 baseline. Furthermore, over 76% of the global land area is projected to experience an increase in rainfall erosivity over the century. Regions with projected changes in rainfall erosivity, whether increase or decrease, are likely to face more pronounced changes from mid-century onwards. The CMIP6 exhibits improved model consistency over its predecessor, CMIP5, indicating a greater water erosion risk as global warming progresses. These projections offer insights for strategies to combat soil degradation due to climate changes.

Future changes in spatially compounding hot, wet or dry events and their implications for the world’s breadbasket regions

Recent years were characterized by an increase in spatially co-occurring hot, wet or dry extreme events around the globe. In this study we analyze data from multi-model climate projections to analyze the occurrence of spatially compounding events and area affected in future climates under scenarios at +1.5 ∘C, +2.0 ∘C, +3.0 ∘C and higher levels of global warming using Earth System Model simulations from the 6th Phase of the Coupled Model Intercomparison Project. Since spatially compounding extreme events can strongly amplify societal impacts as economic supply chains are increasingly interdependent, we want to highlight that the world’s breadbasket regions are projected to be particularly affected by an increase in spatially co-occurring hot, wet or dry extreme events, posing risks to the global food security. We show that the spatial extent of top-producing agricultural regions being potentially threatened by climate extremes will increase drastically if global mean temperatures shift from +1.5 ∘C to +2.0 ∘C. Further we identify a large increase in the projected global land area concurrently affected by hot, wet or dry extremes with increased global warming posing risk to other industries and sectors in addition to the agricultural sector.

Precipitation Seasonality Amplifies as Earth Warms

AbstractPrecipitation exhibits a pronounced seasonal cycle, of which the phase and amplitude are closely associated with water resource management. While previous studies suggested an emerged delaying phase in the past decades, whether the amplified amplitude has emerged is controversial. Using multiple observational data sets and climate simulations, here we show that the amplification of precipitation annual cycle has emerged in most global land areas since the 1980s, especially in the tropics. These amplifications are mainly driven by anthropogenic emissions, and will be further intensified by 17.6% in the future (2081–2100) under high emission scenario (Shared Socioeconomic Pathways, SSP585), and limited to 7.2% under SSP126 scenario, relative to the historical period (1982–2014). Precipitation seasonality will be amplified by 4.2% for each 1°C of global warming, which is seen in all emission scenarios. The mitigation of lower emissions is helpful for alleviating the amplification of precipitation seasonality in a warming world.

Statistical downscaling of GRACE terrestrial water storage changes based on the Australian Water Outlook model

The coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE) dataset has limited its application in local water resource management and accounting. Despite efforts to improve GRACE spatial resolution, achieving high resolution downscaled grids that correspond to local hydrological behaviour and patterns is still limited. To overcome this issue, we propose a novel statistical downscaling approach to improve the spatial resolution of GRACE-terrestrial water storage changes (ΔTWS) using precipitation, evapotranspiration (ET), and runoff data from the Australian Water Outlook. These water budget components drive changes in the GRACE water column in much of the global land area. Here, the GRACE dataset is downscaled from the original resolution of 1.0° × 1.0° to 0.05° × 0.05° over a large hydro-geologic basin in northern Australia (the Cambrian Limestone Aquifer—CLA), capturing sub- grid heterogeneity in ΔTWS of the region. The downscaled results are validated using data from 12 in-situ groundwater monitoring stations and water budget estimates of the CLA’s land water storage changes from April 2002 to June 2017. The change in water storage over time (ds/dt) estimated from the water budget model was weakly correlated (r = 0.34) with the downscaled GRACE ΔTWS. The weak relationship was attributed to the possible uncertainties inherent in the ET datasets used in the water budget, particularly during the summer months. Our proposed methodology provides an opportunity to improve freshwater reporting using GRACE and enhances the feasibility of downscaling efforts for other hydrological data to strengthen local-scale applications.

Assessing Global and Regional Trends in Spatially Co‐Occurring Hot or Wet Annual Maxima Under Climate Change

AbstractRecent years were characterized by spatially co‐occurring hot and wet extremes around the globe, raising questions about the contribution of human‐induced global warming to the changing likelihoods of such extreme years. To characterize spatially co‐occurring extremes we investigate recent trends in global and regional land area that is concurrently affected by hot or wet annual maxima taking observational uncertainty into account. Observed trends in the land area affected by extreme events are assessed in the context of Earth System Model (ESM) simulations for present‐day and early‐industrial climate conditions in a detection and attribution setting. We compare different reanalysis and station‐based observational products to account for observational data uncertainty. At the global scale, trends of spatially co‐occurring hot or wet annual maxima in all observational products can be explained by ESM simulations driven by historical radiative forcing that accounts for human‐induced changes in the composition of the atmosphere but cannot be explained by ESM simulations that account for an early‐industrial radiative forcing. At the regional scale, trends in spatially co‐occurring hot annual maxima are in general coherent among observational products and can in most cases be attributed to human influence on the climate system. Trends in spatially co‐occurring wet annual maxima show differences in some regions, highlighting the importance of a multi‐dataset approach to overcome observational product dependencies. Despite observational uncertainty, we find robust detection and attribution results for many regions. These results can complement previous assessments on regional exposure to hot and wet events from the new IPCC AR6 report.

Identifying global conservation priorities for terrestrial vertebrates based on multiple dimensions of biodiversity.

The Kunming-Montreal Global Biodiversity Framework of the Convention on Biological Diversity calls for an expansion of the current protected areas (PAs) to cover at least 30% of global land and water areas by 2030 (i.e., the 30×30 target). Efficient spatial planning for PA expansion is an urgent need for global conservation practice. A spatial prioritization framework considering multiple dimensions of biodiversity is critical for improving the efficiency of the spatial planning of PAs, yet it remains a challenge. We developed an index for the identification of priority areas based on functionally rare, evolutionarily distinct, and globally endangered species (FREDGE) and applied it to 21,536 terrestrial vertebrates. We determined species distributions, conservation status (global endangerment), molecular phylogenies (evolutionary distinctiveness), and life-history traits (functional rarity). Madagascar, Central America, and the Andes were of high priority for the conservation of multiple dimensions of terrestrial vertebrate biodiversity. However, 68.8% of grid cells in these priority areas had <17% of their area covered by PAs, and these priority areas were under intense anthropogenic and climate change threats. These results highlight the difficulties of conserving multiple dimensions of biodiversity. Our global analyses of the geographical patterns of multiple dimensions of terrestrial vertebrate biodiversity demonstrate the insufficiency of the conservation of different biodiversity dimensions, and our index, based on multiple dimensions of biodiversity, provides a useful tool for guiding future spatial prioritization of PA expansion to achieve the 30×30 target under serious pressures.

Edible dragonflies and damselflies (order Odonata) as human food – A comprehensive review

Abstract The rapid growth of the human population leads to a big concern about the food y and demand worldwide. However, due to the reduction in global arable land area, humans need to find alternative food sources to fulfil their needs. Consequently, edible insects have been identified as a promising solution to ameliorate food security and increase global nutrition. Among more than 2,100 identified edible insect species, dragonflies and damselflies (order Odonata) are considered as one of nutritious food resources. Nevertheless, detailed information on the frequency and distribution of consumption of odonatans around the world is scattered and poorly documented. Based on this review, at least 61 out of 1,964 species of odonatans were reported consumed by people worldwide. The most consumed dragonflies (suborder Epiprocta; infraorder Anisoptera) are from the family of Libellulidae, followed by Aeshnidae and Gomphidae, whereas the most consumed edible damselflies (suborder Zygoptera) are from the Coenagrionidae family. Many nutrients, including proteins, lipids, energy, fibre, vitamins, and minerals are abundant in edible odonatans. Moreover, studies reported that humans employed these insects as therapeutic agents to remedy various ailments. Challenges associated with the consumption of edible odonatans include safety concerns, legal frameworks, and limited information on their bioecology which become barrier for their successful mass-rearing. However, because entomophagy is gradually gaining recognition, new and more improved methods of rearing are now being developed including for edible odonatans, encouraging sustainable insect farming. As the world strives to achieve the sustainable development goals, insect farming will pave a way for resources to be utilised for sustainable economic development.