Earth System Research Articles

Designing-in WebGIS Tools for digital learning terrains in Natural Environments

Authentic learning environments (Herrington et al., 2014) have been widely acknowledged in creating engaging, meaningful and deep learning experiences, including for “novice” first-year undergraduate students (Roach et al., 2018). Natural Environments (ENVS10001) is a first-year undergraduate subject (unit) that aims to deliver foundational understanding of earth systems and processes to support studies in agriculture, natural resource management and civil engineering. One main obstacle to facilitating understanding in this domain is the unfamiliar scales of the landscape processes and phenomena (Resnick et al., 2017). Natural Environments has been using the granitic geology dominated landscape of Glenrowan in northeastern Victoria (Australia) as an authentic case study. In this presentation we explain how and why we re-designed authentic learning aligned tutorial interactions by integrating student-driven navigation of WebGIS tools such as Geoscience Australia and NatureKit portal to: (a) enable students to build understanding of how geology, geomorphology and ecology interact to result in the dynamic landscapes in the environment; (b) equip students with fundamental and valuable knowledge and skills in accessing free and publicly available datasets useful in their academic and future professional work; (c) demonstrate the authenticity of the curricular content to establish higher levels of learner engagement. The current learning design where dynamic control and interaction with spatial data is central, is just one iteration in the series of previous designs that moved from non-digital to static-digital resources in the learning environment. Generally, an anchored instruction aligned approach (The Cognition and Technology Group at Vanderbilt, 1990) was adopted. Prior to the tutorial, students attended two one-hour lectures explaining the structure of the earth, plate tectonics, and global-scale structural (volcanic and tectonic) landforms. We wanted students to develop an understanding of how, over “unfamiliar” geological (time) and spatial scales, geomorphological processes operating across different rock types resulting from geological processes (e.g. granite pluton emplacement amongst sedimentary rocks) result in the landscapes observed presently. During the class, with tutors as guides, students worked in groups and learnt how to use the Geoscience Australia portal to explore the Glenrowan region, centered around the Warby Ranges and the surrounding plains. Professional instructional videos developed in collaboration with the University of Melbourne Learning Environments media team were used to demonstrate how to use the portal to find geological and geomorphological information. Students were guided in the use of Google Earth to visualise terrain in pseudo-3D and using elevation transects. The spatial correlation of landform patterns and elements with different surface and subsurface geologies was key to unlocking students’ abilities to explain the “why” and “how” of landscape evolution, albeit at the basic level. Students had mostly positive experiences and learning outcomes shown in the post-subject survey (n = 30; scores of 4.6 to 6.0 for 12 questions on 7-point Likert scale) and comments. Technical issues encountered due to simultaneous class access to the portal, and gaps in explaining specific functionalities and their potential for further understanding, were highlighted. The authors acknowledge the strong support for this work through the University of Melbourne’s FlexAP programme.

Space technologies for development? Practicing sovereignty, beyond inclusion

The increasing use and integration of space technologies in International Development projects raises fundamental questions about the ways in which these technologies are produced and applied, for what purposes and what ideas of innovation underpin their knowledge frameworks. With reference to two UK Space Agency (UKSA)-funded projects aiming to create an environmental information system using remotely sensed data, this article considers the possibilities and threats of user-centred technology design for the management of Indigenous territories. The team of Indigenous and non-Indigenous researchers grapples with the contradictions and sites of tension emerging at the intersection of the space sector, development, Earth system science and Indigenous sovereignty. Can space science and development be re-interpreted in the light of local needs, knowledges and right to self-determination? While common reliance on Western epistemologies feeds into deterministic understandings of technological benefits, this article presents Indigenous worldviews and practices as integral to codesign and co-implementation of innovations that are both technical and social. It argues that data are grounded and must be kept in connection with the contexts, culture and knowledges that make up a place. Praxis – as a theoretically inspired practice of doing development projects – thus emerges as a worldmaking activity inspired by a vision of design that foregrounds Indigenous sovereignty.

An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation

Abstract. Aerosols constitute important substance components of the Earth's atmosphere and have a profound influence on climate dynamics, radiative properties, and biogeochemical processes. Here we introduce updated emission schemes for dust, sea-salt, and marine primary organic aerosols (MPOA), as well as augmented secondary organic aerosol (SOA) formation pathways within the Community Earth System Model (CESM; version 2.1.3). The modified dust emission scheme shifts the original hotspot-like dust emission to a more continuous distribution, improving the dust aerosol optical depth (DAOD) simulations at stations in north Africa and central Asia. This update also reduces dust residence time from 4.1 to 1.6 d, enhancing concentration simulations downwind of dust source regions. For sea-salt emissions, we incorporate an updated sea surface temperature (SST) modulation and introduce a relative-humidity-dependent correction factor for sea-salt particle size, with SST having a significantly larger impact on sea-salt emissions (16.1 %) compared to the minor effect of humidity (−0.3 %). We then extend our modelling to incorporate emissions of marine primary organic aerosols (MPOA) as mixed externally with sea-salt aerosols, coupled offline with the ocean component Parallel Ocean Program (POP2). The results underscore the substantial influence of phytoplankton diversity on MPOA emissions, with 148 % variability simulated among different phytoplankton types, highlighting the role of biological variability in aerosol modelling. Furthermore, we refine the model's chemical mechanisms by including the irreversible aqueous uptake of dicarbonyl compounds as a new pathway for SOA formation, contributing an additional 37 % to surface SOA concentrations. These improvements enrich the ability of the CESM to use intricate linkages between different components of the Earth system, thereby enabling a more comprehensive description of natural aerosol emissions, chemical processes, and their impacts.

Projected future changes in extreme precipitation over China under stratospheric aerosol intervention in the UKESM1 climate model

Abstract. Extreme precipitation events are linked to severe economic losses and casualties in China every year; hence, exploring the potential mitigation strategies to minimize these events and their changes in frequency and intensity under global warming is of importance, particularly for the populous subregions. In addition to global warming scenarios, this study examines the effects of the potential deployment of stratospheric aerosol injection (SAI) on hydrological extremes in China based on the SAI simulations (G6sulfur) of the Geoengineering Model Intercomparison Project (GeoMIP) by the UK Earth System Model (UKESM1) simulations. G6sulfur is compared with simulations of the future climate under two different emission scenarios (SSP5-8.5 and SSP2-4.5) and a reduction in the solar constant (G6solar) to understand the effect of SAI on extreme precipitation patterns. The results show that under global warming scenarios, precipitation and extreme wet climate events during 2071–2100 are projected to increase relative to the control period (1981–2010) across all the subregions in China. Extreme drought events show a projected increase in southern China. The G6sulfur and G6solar experiments show statistically similar results to those under SSP2-4.5 in extreme precipitation intensities of China in UKESM1. These results are encouraging. The efficacy of SAI in decreasing extreme precipitation events and consecutive wet days is more pronounced than that of G6solar when compared to SSP2-4.5. While both G6sulfur and G6solar show drying at high-latitude regions, which is consistent with our understanding of the spin-down of the hydrological cycle under SRM. Given the limitations of the current model and the small ensemble size, and considering that the hydrological effects are less beneficial than those indicated for temperature, it is recommended that further, more comprehensive research be performed, including using multiple models, to better understand these impacts.

Cenozoic surface Earth system evolution and dynamic paleogeomorphic reconstruction from the Tibet Plateau to the Western Pacific linked by the Yangtze River

The formation of the modern east-flowing Yangtze River is marked by the incision of the Three Gorges (TG) between the Sichuan and Jianghan basins. However, it is still controversial on the timing of the TG incision, due to diverse tectonic, sedimentological and geochemical records. These records, together with other geological data, i.e. curves of paleo-climate and sea level fluctuation, are critical parameters in the software Badlands , a tool to simulate large-scale and long-term geomorphic evolution. Using Badlands , we modeled the geomorphology and drainage evolutionary process of the Yangtze River since the Late Cretaceous (80 Ma). It revealed that the drainage system in the Sichuan Basin was gradually reversed from southward flowing to northward flowing during the Late Eocene and the Oligocene, due to the periodic uplift of the eastern Tibet Plateau and the southwestern Yangtze Block. Coevally, the Jianghan Basin experienced a base level drop, controlled by the collapse of a paleo-coastal mountain range and the subsequent continental rifting along the Southeast China continental margin. The tectono-geomorphic interplay eventually led to the incision of the TG at the Late Oligocene (about 24Ma), when the drainage system of the Upper Yangtze River was captured by the Middle-Lower Yangtze River.

AI-based Validation of Deforestation Using High-Resolution Satellite Imagery in the Brazilian Amazon

Abstract. Forests play an important role in the Earth systems for carbon sequestration and climate change mitigation, yet they have been increasingly disturbed by deforestation and forest degradation at an unprecedented pace. The Brazilian Amazon, for instance, experienced a 140% rise in deforestation from 2012 to 2020, with a record loss of 13,200 km2 between August 2020 and July 2021. Alarmingly, 87% of 2019 deforestation alerts occurred on private properties, with 61% in legally restricted areas. Existing deforestation monitoring systems, such as PRODES and the Global Forest Change dataset, use about 30m resolution satellite imagery, which is insufficient for operational validation at fine scales. The Deforestation Alert System by Imazon leverages high-resolution PlanetScope data (3-4m) but faces challenges due to fewer spectral bands and variations in reflectance values across different satellite sensors and dates. As a result, current validation is based mainly on manual inspection which is highly time-consuming. To address the challenges and automate the validation process, this work develops a system based on deep learning – known for its ability to capture complex texture patterns in high-resolution images – to inspect and confirm new deforestation sites. Specifically, the system takes inputs from potential deforestation sites suggested by coarse-resolution products and uses a pair of PlanetScope images before and after the change at each site to determine new deforestation (excluding existing deforestation). Our results demonstrate that the new system achieves robust and high-quality accuracy under various test conditions.

A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2

Abstract. Recent studies have suggested that injection of solid particles such as alumina and calcite particles for stratospheric aerosol injection (SAI) instead of sulfur-based injections could reduce some of the adverse side effects of SAI such as ozone depletion and stratospheric heating. Here, we present a version of the global aerosol–chemistry–climate model SOCOL-AERv2 and the Earth system model (ESM) SOCOLv4 which incorporate a solid-particle microphysics scheme for assessment of SAI of solid particles. Microphysical interactions of the solid particle with the stratospheric sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code (RTC) for the first time within an ESM. Therefore, the model allows simulation of heterogeneous chemistry at the particle surface as well as feedbacks between microphysics, chemistry, radiation and climate. We show that sulfur-based SAI results in a doubling of the stratospheric aerosol burden compared to the same mass injection rate of calcite and alumina particles with a radius of 240 nm. Most of the sulfuric acid aerosol mass resulting from SO2 injection does not need to be lifted to the stratosphere but is formed after in situ oxidation and subsequent water uptake in the stratosphere. Therefore, to achieve the same radiative forcing, larger injection rates are needed for calcite and alumina particle injection than for sulfur-based SAI. The stratospheric sulfur cycle would be significantly perturbed, with a reduction in stratospheric sulfuric acid burden by 53 %, when injecting 5 Mt yr−1 (megatons per year) of alumina or calcite particles of 240 nm radius. We show that alumina particles will acquire a sulfuric acid coating equivalent to about 10 nm thickness if the sulfuric acid is equally distributed over the whole available particle surface area in the lower stratosphere. However, due to the steep contact angle of sulfuric acid on alumina particles, the sulfuric acid coating would likely not cover the entire alumina surface, which would result in available surface for heterogeneous reactions other than the ones on sulfuric acid. When applying realistic uptake coefficients of 1.0, 10−5 and 10−4 for H2SO4, HCl and HNO3, respectively, the same scenario with injections of calcite particles results in 94 % of the particle mass remaining in the form of CaCO3. This likely keeps the optical properties of the calcite particles intact but could significantly alter the heterogeneous reactions occurring on the particle surfaces. The major process uncertainties of solid-particle SAI are (1) the solid-particle microphysics in the injection plume and degree of agglomeration of solid particles on the sub-ESM grid scale, (2) the scattering properties of the resulting agglomerates, (3) heterogeneous chemistry on the particle surface, and (4) aerosol–cloud interactions. These uncertainties can only be addressed with extensive, coordinated experimental and modelling research efforts. The model presented in this work offers a useful tool for sensitivity studies and incorporating new experimental results on SAI of solid particles.

“Planetary phase shift” as a new systems framework to navigate the evolutionary transformation of human civilisation

Purpose The paper aims to address a gap in foresight study and practice relating to the lack of unifying theoretical systems frameworks capable of examining empirical data from across a wide range of different ecological, social, political and economic systems. It attempts to develop a new “collective forward intelligence” that can not only make sense of these disparate trends and processes as symptoms of a wider planetary system but also, on this basis, construct accurate and plausible future scenarios to underpin national and international decision-making. Design/methodology/approach This study conducts a transdisciplinary integration of C. S. Holling’s adaptive cycle with phase-transition phenomena across biology, physics and chemistry, applied on societal and civilisational scales. A systems methodology is then applied to integrate historical and empirical data across the energy, food, transport, materials and information sectors of civilisation’s production system. Findings The paper develops planetary phase shift theory as a new collective forward intelligence framework for foresight study and practice, formalising the notion that humanity has arrived at an unprecedented historic and geological turning point. It finds that multiple global crises across both earth and human systems are symptoms of the last stages of the life-cycle of global industrialisation civilisation, which is the potential precursor either for collapse, or for a new civilisational life-cycle that may represent a new stage in the biological and cultural evolution of the human species. Research limitations/implications The research sets out a new empirically grounded theoretical framework for complex scenario analysis. This can develop more robust approaches to foresight study and practice, scenario development and forecasting. It suggests the need for a new research programme to understand the dynamics of the planetary phase shift and its diverse implications for societies, industry, technology and politics. The research is limited in that the current paper does not explore how it can be applied in this way. It identifies broad scenarios for a post-industrial civilisational life-cycle but does not identify the variety of complex subsets of these. Practical implications The paper provides powerful practical implications to develop new methodology based on planetary phase shift theory for strategic planning, risk assessment and management, as well as public policy and decision-making. Social implications The paper suggests the urgency and necessity of bold and radical societal transformation and implies key areas for civil society to focus on in innovating new values, worldviews and operating systems with a focus on the next life-cycle. Originality/value To the best of the author’s knowledge, this paper provides the first integrated transdisciplinary theoretical and empirical framework to understand how the interplay of earth system crises, societal change and technology disruptions is driving large-scale civilisational transformation with complex local ramifications.

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications

Abstract Robust quantification of predictive uncertainty is a critical addition needed for machine learning applied to weather and climate problems to improve understanding of what is driving prediction sensitivity. Ensembles of machine learning models provide predictive uncertainty estimates in a conceptually simple way but require multiple models for training and prediction, increasing computational cost and latency. Parametric deep learning can estimate uncertainty with one model by predicting the parameters of a probability distribution but does not account for epistemic uncertainty. Evidential deep learning, a technique that extends parametric deep learning to higher-order distributions, can account for both aleatoric and epistemic uncertainty with one model. This study compares the uncertainty derived from evidential neural networks to that obtained from ensembles. Through applications of classification of winter precipitation type and regression of surface layer fluxes, we show evidential deep learning models attaining predictive accuracy rivaling standard methods, while robustly quantifying both sources of uncertainty. We evaluate the uncertainty in terms of how well the predictions are calibrated and how well the uncertainty correlates with prediction error. Analyses of uncertainty in the context of the inputs reveal sensitivities to underlying meteorological processes, facilitating interpretation of the models. The conceptual simplicity, interpretability, and computational efficiency of evidential neural networks make them highly extensible, offering a promising approach for reliable and practical uncertainty quantification in Earth system science modeling. In order to encourage broader adoption of evidential deep learning, we have developed a new Python package, MILES-GUESS (https://github.com/ai2es/miles-guess), that enables users to train and evaluate both evidential and ensemble deep learning.

Food and land system transformations under different societal perspectives on sustainable development

Abstract The future of food and land systems is crucial for achieving multiple UN Sustainable Development Goals, given their essential role in providing adequate nutrition and their significant impact on Earth system processes. Despite widespread consensus on the need for transformation, discussed strategies vary widely, from technology-driven to sufficiency-focused approaches, emphasizing different agents of change and policy mixes. This study assesses the implications of a new generation of target-seeking scenarios incorporating such diverse sustainability perspectives. We apply two integrated assessment models to explore food and land futures under three whole-economy Sustainable Development Pathways (SDPs): Economy-driven Innovation, Resilient Communities, and Managing the Global Commons. Our assessment shows that all SDPs align sufficient food supply with progress towards planetary integrity, halting biodiversity loss, mitigating adverse impacts from irrigation, and significantly reducing nitrogen pollution. While all pathways comply with the Paris climate target, they diverge in the timing of climate mitigation efforts and focus on different greenhouse gases and emission sources. The Economy-driven Innovation pathway rapidly achieves net-negative CO2 emissions from the land system, whereas Resilient Communities and Managing the Global Commons significantly decrease agricultural non-CO2 emissions. Moreover, sustainability interventions attenuate trade-offs associated with narrowly focused mitigation pathways and reduce reliance on carbon dioxide removal strategies like re/afforestation and bioenergy with carbon capture and storage.

Asymmetric ENSO teleconnections in a symmetric CO2 concentration pathway

Abstract El Niño-Southern Oscillation (ENSO) is the strongest interannual phenomenon occurring in the tropical Pacific, significantly affecting the entire world. The ENSO response to increasing CO2 concentrations have been extensively studied, but the reverse scenario is still not well understood. Here, we investigate the hysteresis of ENSO teleconnections in a CO2 removal simulation of an earth system model. During the ramp-up period of CO2 concentrations, Pacific-North American and Pacific-South American patterns are intensified, with the eastward shift of their poles, which are even further intensified during the ramp-down period. This ENSO teleconnection hysteresis is closely linked to the tropical-origin hysteresis, in which, during the ramp-down periods, the prevalence of the eastern-Pacific type El Niño leads to the hysteresis in the eastern Hemispheric ENSO teleconnections and the enhanced ENSO skewness and the eastward shift of ENSO-induced tropical atmospheric convection do to that in the western Hemispheric ENSO teleconnection. The alterations by the tropical origin are predominantly associated with intensified southward migration of the Intertropical Convergence Zone, along with a stronger El Niño-like warming trend. We also demonstrate that the hysteretic change in the mid-latitude mean state over the North Pacific region could lead to hysteresis of the ENSO teleconnection without invoking a tropical origin.

Regionally Coupled Climate Model ROM Projects More Plausible Precipitation Change Over Central Equatorial Africa

AbstractUnraveling plausible future rainfall change (ΔPr) patterns is crucial for tailoring societies' responses to climate change‐induced hazards. This study compares rainfall projections from the regionally coupled ocean model (ROM) and its atmospheric component, the regional atmospheric model REMO, over Central Equatorial Africa (CEA). Both models are forced by the Earth system model MPI‐ESM‐LR following the Representative Concentration Pathway 8.5. Results reveal increased rainfall across most of CEA, with ROM projecting more widespread and intensified wetting than REMO, although REMO produces more precipitation under future conditions, underscoring the influence of historical biases on REMO's projection. Examining processes underpinning changes unveils strong controls of sea and land surface temperature changes in ΔPr differences between the two models. Specifically, ROM mitigates warming more over the Atlantic than over CEA landmass compared to REMO, inducing enhancement of the Congo Basin cell and increased precipitable water content through specific humidity, affecting deep convection. Both models project enhanced Sahel and Kalahari thermal lows, with ROM better depicting the Kalahari low's warmer nature than the Sahel low. The resulting temperature gradients strengthen the northern and southern shallow meridional Hadley overturning circulation. ROM simulates the wetter conditions than REMO, attributed to its weaker northern Hadley Cell, which restricts the likelihood of northward moisture divergence toward the Sahel. Additionally, differences in mid‐tropospheric moisture convergence differentiate between ROM and REMO's wetness relative to the historical period and under future conditions. ROM projections are more plausible, in association with the reliability of its added value under the historical climate and mechanisms underlying Δpr.

Experimental access to volcanic eruptions

Well-chosen experiments provide access to a vast array of magmatic and volcanic processes, from magma transport within the lithosphere through volcanic eruptive phenomena to the fate of erupted materials in the earth system. This selected overview of contributions from our labs collates examples from early work on rheology and fragmentation to some recent experimental excursions into postfragmentation modification and the thermal and chemical journey of lavas and pyroclasts leading up to their deposition and lithification.

Widening of wind-stress anomalies amplifies ENSO in a warming climate

Abstract Climate change simulations generally indicate the strengthening of El Niño Southern Oscillation (ENSO) sea surface temperature (SST) variability through the 21st century, yet a robust physical mechanism explaining this change across different models is still lacking, and the projections for ENSO amplitude exhibit a large spread. Most commonly, changes in the background state of the tropical Pacific are invoked to explain these changes of ENSO. Here we show that changes in the structure of wind-stress anomalies associated with ENSO are potentially as important as these background state changes. Specifically, changes in the magnitude, meridional width, and zonal structure of wind-stress anomalies can explain approximately 53% of the inter-model variance in the projected change of ENSO magnitude through the 21st century as well as 43% in ENSO periodicity changes. Among these changes in the wind structure, the meridional widening of wind anomalies plays the most important role. To demonstrate that these changes are indeed critical, we develop a hybrid model of ENSO based on the Community Earth System Model version 2, which incorporates a dynamical ocean coupled to a simplified statistical atmosphere within the tropical Pacific. In the absence of external forcing and corresponding mean-state changes, the imposed changes in wind stress anomalies in this hybrid model result in an increase of ENSO amplitudes of nearly 10% along the equator. Our results are also theoretically supported by a recharge-oscillator model that incorporates the meridional wind structure. Thus, changes in the structure of wind-stress anomalies, together with changes in the mean state, likely play a critical role in the projected strengthening of ENSO.

Toward Modeling Continental‐Scale Inland Water Carbon Dioxide Emissions

AbstractInland waters emit significant amounts of carbon dioxide (CO2) to the atmosphere; however, the global magnitude and source distribution of inland water CO2 emissions remain uncertain. These fluxes have previously been “statistically upscaled” by independently estimating dissolved CO2 concentrations and gas exchange velocities to calculate fluxes. This scaling, while robust and defensible, has known limitations in representing carbon source limitations and spatial variability. Here, we develop and calibrate a CO2 transport model for the continental United States, simulating carbon transport and transformation in >22 million hydraulically connected rivers, lakes, and reservoirs. We estimate 25% lower CO2 fluxes compared to upscaling estimates forced by the same observational calibration data. While precise CO2 source distribution estimates are limited by the resolution of model parameterizations, our model suggests that stream corridor CO2 production dominates over groundwater inputs at the continental scale. Our results further suggest that the lack of observational networks for groundwater CO2 and scalable metabolic models of aquatic CO2 production remain the most salient barriers to further coupling of our model with other Earth system components.

Land Processes Can Substantially Impact the Mean Climate State

AbstractTerrestrial processes influence the atmosphere by controlling land‐to‐atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model version 2 under preindustrial conditions. We find that an observationally‐informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (σ = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagate to the entire Earth system, and provides insights into where and how land process uncertainty influences climate.

Spatiotemporal variations of surface albedo in Central Asia and its influencing factors and confirmatory path analysis during the 21st century

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 °C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

Cities Are Concentrators of Complex, MultiSectoral Interactions Within the Human‐Earth System

AbstractCities are concentrators of complex, multi‐sectoral interactions. As keystones in the interconnected human‐Earth system, cities have an outsized impact on the Earth system. We describe a multi‐lens framework for organizing our understanding of the complexity of urban systems and scientific research on urban systems, which may be useful for natural system scientists exploring the ways their work can be made more actionable. We then describe four critical dimensions along which improvements are needed to advance the urban research that addresses urgent climate challenges: (a) solutions‐oriented research, (b) equity‐centered assessments which rely on fine‐scale human and ecological data, (c) co‐production of knowledge, and (d) better integration of human and natural systems occurring through theory, observation, and modeling.

Real-time modeling of transient crustal deformation through the quantification of uncertainty deduced from GNSS data

We propose a new method for real-time uncertainty monitoring of earthquake and volcano source models using data from the global navigation satellite system (GNSS) and explore its application concerning observation station placement. The Geospatial Information Authority of Japan operates two main types of GNSS earth observation network system (GEONET) coordinates for crustal deformation monitoring on different time scales: post-processing analysis values and real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD uses the Markov Chain Monte Carlo (MCMC) method termed real-time automatic uncertainty estimation of a coseismic single rectangular model using GNSS data (RUNE) for single rectangular fault model estimation to handle uncertainty. Thus far, no GNSS monitoring system can automatically detect transient crustal deformation events, such as volcanic activity and earthquake swarms, on timescales of a day or less. We extended RUNE and developed a core program for a new monitoring system for earthquake and volcanic source models and their uncertainties. Our program achieved automatic and stable MCMC utilization for rectangular fault, dike, Mogi, and spheroid models by increasing the computational speed, improving search efficiency, and adjusting hyperparameters. The program automatically determines the standard deviation of the likelihood function assuming a normal distribution with weights for each observation station. The calculation time was within 15 s for 1 × 106 samples on a standard 1U server. We assessed the reliability of the developed method using synthetic and observed GNSS data from the 2015 Sakurajima volcanic event. The results were consistent with the assumed model and previous studies and indicated an advantage in automatically quantifying uncertainty in a short computation time. Based on MCMC samples, we developed a new visualization algorithm to indicate areas on a map in which the number of observation stations should be expanded. We assessed the reliability using data from the 2023 Noto Peninsula earthquake [Mj 6.5]. The results indicate that the algorithm is helpful in studying the placement of stations. The above model extensions and their application are essential to achieve a rapid quantitative understanding of disaster events near urban areas and for utilizing this information in emergency response activities.Graphical

Anthropogenic Climate Change Will Intensify European Explosive Storms Analogous to Alex, Eunice, and Xynthia

Abstract Extratropical storms, particularly explosive storms or “weather bombs” with exceptionally high deepening rates, present substantial risks and are susceptible to climate change. Individual storms may exhibit a complex and hardly detectable response to human-driven climate change because of the atmosphere’s chaotic nature and variability at the regional level. It is thus essential to understand changes in specific storms for building local resilience and advancing our overall comprehension of storm trends. To address this challenge, this study compares analogs—storms with a similar backward track until making landfall—in two climates of three explosive storms impacting different European locations: Alex (October 2020), Eunice (January 2022), and Xynthia (February 2010). We use a large ensemble dataset of 105 members from the Community Earth System Model, version 1 (CESM1). These analogs are identified in two periods: the present-day climate (1991–2001) and a future climate scenario characterized by high anthropogenic greenhouse gas emissions [representative concentration pathway 8.5 (RCP8.5), 2091–2101]. We evaluate future changes in the frequency of occurrence of the storms and intensity, as well as in meteorological hazards and the underlying dynamics. For all storms, our analysis reveals an increase in precipitation and wind severity over land associated with the explosive analogs in the future climate. These findings underscore the potential consequences of explosive storms modified by climate change and their subsequent hazards in various regions of Europe, offering evidence that can be used to prepare and enhance adaptation processes. Significance Statement This study investigates the impact of climate change on explosive storms, or weather bombs, and their potential consequences for European regions. We project future scenarios of three specific storms, Alex, Eunice, and Xynthia, using a state-of-the-art climate model. Our findings reveal an increase in precipitation and wind over land associated with these storms, emphasizing the heightened risks associated with climate change. The significance lies in understanding the local implications of explosive storms, aiding in the development of resilient strategies and adaptation measures.