Recent lbnl_ees_ce items

Studying Aerosol, Clouds, and Air Quality in the Coastal Urban Environment of Southeastern Texas

Wed, 21 Oct 2026 00:00:00 +0000

Abstract A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups,...

Bias Correction Can Strongly Shape California's Projected Megaflood Risk

Tue, 20 Oct 2026 00:00:00 +0000

Abstract A California “megaflood”—a weeks‐long cluster of storms with centuries‐long return times—would be catastrophic, yet its timing and magnitude under climate change remains uncertain. A central source of uncertainty is whether Earth System Model boundary conditions should be bias corrected before dynamical downscaling. Here, we analyze a large ensemble of downscaled simulations to quantify how this uncertainty shapes California's megaflood risk. Bias correction is necessary to reproduce observed storm statistics and strongly influences both the megafloods historical and future characteristics. Without correction, storm precipitation variability is inappropriately inflated, delaying the emergence of extreme precipitation signals by decades. Further, megaflood intensity estimates based on statistically extended observations are at least 10% drier than explicit computations derived from sufficiently sized storm populations. Our results show that bias correction choices crucially...

ABCFlux v2: Arctic–boreal CO2 and CH4 monthly flux observations and ancillary information across terrestrial and freshwater ecosystems

Mon, 19 Oct 2026 00:00:00 +0000

Measurements of surface-atmosphere carbon dioxide (CO 2 ) and methane (CH 4 ) fluxes have been relatively sparse across the Arctic tundra and boreal biomes, causing significant uncertainties in carbon budget estimates from the region. While the availability of Arctic-boreal carbon flux data has increased substantially over the past decade, the data have remained spread across different repositories, scientific articles, and unpublished sources, making it difficult to leverage. Here we present a new dataset of monthly Arctic-boreal carbon fluxes (ABCFlux v2) across terrestrial (wetlands and uplands) and freshwater (lakes and rivers) ecosystems compiled from previous syntheses including the Arctic-boreal CO 2 flux database (ABCFlux v1), the Boreal-Arctic Wetland and Lake Methane Dataset (BAWLD-CH4), and the Global River Methane Database (GRiMeDB). In addition, we consider data from general-purpose (e.g., Zenodo) and flux network repositories,...

A simplified approach to energy-water modeling for controlled environment agriculture

Mon, 19 Oct 2026 00:00:00 +0000

An increasingly implemented alternative to outdoor farming, controlled environment agriculture (CEA) ensures reliable food production despite volatile growing conditions such as drought, flooding, and extreme temperatures. CEA can bolster local food production and revenue, promoting food resilience; however, the high energy and, in some cases, water demand required to optimize indoor environments for crop growth is a notable barrier to adoption. Understanding the resource consumption of CEA facilities is crucial to the sustainable growth of this sector, but existing models tend to be proprietary, limited in scope, or require detailed design data. To address this issue, we propose a simplified, flexible model (CEAEstA) that integrates fundamental lighting, heating, cooling, and evapotranspiration principles to estimate energy and water demand. The model is designed to be accessible for early-stage feasibility assessments, allowing stakeholders to evaluate sustainability trade-offs...

Quantifying Methane Emissions from Oil Fields in the Central Valley of CA

Tue, 13 Oct 2026 00:00:00 +0000

Abstract In 2024, California was the eighth-largest producer of crude oil in the U.S. by volume with ∼50,000 active wells. Working with the California Energy Commission, we measured methane (CH4) emissions from 172 actively producing oil wells (219 total observations with 47 repeat measurements) either with or without casinghead gas collection systems (GCS) in two oil fields near Bakersfield in Kern County. We also measured benzene (C6H6) emissions at a subset of wells to assess C6H6 to CH4 ratios. The mean mass-based ratio for C6H6:CH4 was 7.8 × 10–7 with a mean benzene emission rate of 0.9 mg h–1. Wells with an open-ended line (OEL) emitted ∼100-fold more methane on average than wells with a GCS: 1.26 kg h–1 and 0.01 kg h–1, respectively. The prevalence of wells with a GCS rose sharply with increasing oil and gas production, rising from 36% for wells producing <2 barrels of oil equivalent per day (boed) to 97% for wells producing ≥15 boed. The top 5.7% highest-emitting wells...

Ecosystem retrogression enhances cross‐domain microbial stability and increases the genetic potential for nutrient cycling

Tue, 13 Oct 2026 00:00:00 +0000

Ecosystem retrogression drives nutrient depletion, reduced productivity, and profound reorganization of soil microbial communities. Using amplicon sequencing and genome-resolved metagenomics, we examined how cross-domain microbial networks and functional gene potential respond to long-term phosphorus and nitrogen limitation along the well-characterized Ecological Staircase chronosequence in Mendocino, California, USA. Microbial diversity and abundance declined sharply with terrace age for prokaryotes, predatory protists, and bacteriophages, whereas fungi and phototrophic protists increased in nutrient-depleted, acidic soils. These compositional shifts were accompanied by major changes in reconstructed microbial networks: relative modularity increased alongside robustness, indicating adaptive reorganization that may sustain ecosystem function under resource scarcity. Fungi emerged as central stabilizers in these restructured networks, carrying enriched genetic potential to degrade...

Improving UAV Magnetic Surveys with a Theory-Guided Empirical Model for Locating and Characterizing Undocumented Orphaned Oil and Gas Wells

Mon, 5 Oct 2026 00:00:00 +0000

Abstract Undocumented orphaned oil and gas wells can pose risks through unintended releases of substances, yet they remain difficult to locate because records are incomplete and surface indicators are often absent. Unmanned aerial vehicle (UAV) magnetometry is increasingly used to identify steel-cased wells, but surveys commonly stop at target detection and provide limited guidance on how sensor height affects anomaly strength, burial-depth estimates, or confidence in non-detection. Here, we develop a physics-informed, calibrated empirical model between peak magnetic-anomaly amplitude and distance from the magnetometer to the top of steel casing. Using anomaly amplitude measured at known sensor height, the model provides three practical outputs: estimated casing-top burial depth where casing is not visible, maximum sensor height at which casing at a specified depth remains detectable, and correction of variable-height anomalies to a common reference height. We calibrate the relationship...

Symmetry and Historicity in the Game of Life: Modifying Rules to Simulate Evolutionary Dynamics

Thu, 1 Oct 2026 00:00:00 +0000

The Game of Life (GoL) is a paradigmatic computer simulation that exhibits the emergence of complex properties of the whole from relatively simple sets of heuristic rules operating at lower organizational levels. Therefore, it is widely understood as a valuable tool for investigating global properties of evolutionary processes. Cognizant of refined concepts that emerged in recent debates on the central role of historical contingency (historicity) in evolution, we modify the original GoL rules by introducing an updating feedback loop and a probability factor that reflect the degree of historicity in pattern evolution as both stochastic path dependence and sensitivity to initial conditions. We examine this trait in simulations of the emergence and breaking of bilateral and radial symmetries commonly observed in the evolution of life, most prominently as evolving body plans. We show that the implementation of historicity parameters leads to a more realistic sequential and gradual...

Bayesian Regression for Dependent Tensor-Valued Data from Exponential Families

Tue, 29 Sep 2026 00:00:00 +0000

In the Earth system sciences, identifying physically meaningful patterns from dependent, high-dimensional, tensor-valued data is important for understanding variability in the Earth system. Orthonormal matrices are fundamental for statistical modeling of dependent data due to their role in matrix and tensor decomposition methods. While significant effort has been devoted to statistical inference for dependent matrix-valued data, these developments have not yet been extended to tensor-valued data. Here, we propose a general framework for dependent tensor-valued generalized linear mixed models (GLMMs) with a non-separable and non-stationary structured random effect. The random effect is parameterized using a tensor decomposition consisting of structured random orthonormal matrices, whose structures and associated coefficients are inferred during model estimation. Fully Bayesian inference enables joint estimation of all components of the dependent random effect and fixed effect within...

Intercropping with legumes in the Congo Basin increases maize yields but not greenhouse gas emissions

Tue, 29 Sep 2026 00:00:00 +0000

Agricultural intensification on existing arable lands has been proposed to reduce deforestation in the Congo Basin, although the effects of intensification on soil greenhouse gas (GHG) emissions have not yet been investigated. Here, we present the first field study to quantify the trade-offs between yield and GHG emissions across different intensification options in this region. We show that intercropping with nitrogen-fixing beans not only provided additional protein-rich food but also increased maize yields by 1.4-fold while leaving N2O emissions and the soil CH4 sink unchanged compared to unfertilized maize. In contrast, a moderate mineral fertilizer application of 66 kg N ha−1 yr−1 doubled yields, but reduced the soil CH4 sink strength, and increased N2O emissions fivefold to about 4 kg N2O-N ha−1 yr−1. These N2O emissions also exceeded those of natural forests by more than a factor of three, highlighting the GHG cost of mineral fertilizer use in addition to CO2 emissions...

Future Changes in Atlantic Tropical Cyclone Precipitation and Size in Convection‐Permitting Regional Model Simulations

Tue, 22 Sep 2026 00:00:00 +0000

Abstract Tropical cyclone (TC) precipitation is projected to increase in the future, although the magnitude and whether its scaling with temperature will exceed the theoretical Clausius‐Clapeyron (CC) rate remains uncertain. In this study, we investigated future changes in TC precipitation and its scaling with temperature in 10 TC events that impacted the United States and Caribbean Islands. We performed four‐member ensembles of convection‐permitting regional model simulations for each TC under historical conditions and under a high‐emissions scenario for the mid‐21st century. We found that future TC precipitation in a reference frame following the TC increased up to ∼1.5 times the historical for all 10 TCs and scaled at super‐CC rates of 9%–17% K −1 for nine of the 10 TCs. Precipitable water scaling was less than precipitation scaling for nine of 10 TCs, indicating that it alone did not fully explain the future TC precipitation changes. Midtropospheric ascent increased in the...

Increased precipitation decelerates temporal succession of grassland soil microbial communities

Mon, 21 Sep 2026 00:00:00 +0000

Global precipitation regimes have been shifted in recent decades, imposing significant consequences in water-limited grassland ecosystems. However, the effects of increased precipitation on the succession of soil microbial communities remain unclear, mainly due to the scarcity of long-term experiments with time-series data. Here, we examined temporal succession of grassland soil microbial communities in a long-term increased precipitation experiment. Both soil microbial taxonomic and functional structures were significantly altered by increased precipitation. Increased precipitation significantly decelerated the succession rates of soil microbial functional structure (i.e. time-decay relationships). Consistent with the increased microbial decomposition and heterotrophic respiration, the abundances of soil microbial carbon decomposition genes were markedly enhanced by increased precipitation. Furthermore, increased precipitation stimulated genes involved in nutrient cycling processes,...

Modeling the Distribution, Impacts, and Mitigation of Anthropogenic Heat in Los Angeles

Thu, 17 Sep 2026 00:00:00 +0000

Abstract Anthropogenic heat emissions from human energy consumption contribute to the urban heat island (UHI) effect, yet their spatiotemporal distributions and impacts remain uncertain. In this study, we develop a 100 m resolution, hourly anthropogenic heat flux (AHF) data set for Los Angeles County and use the Weather Research and Forecasting model to quantify the meteorological impacts of AHF and the heat mitigation potential of electrification and energy efficiency measures. Annual mean AHF across the county was 2.54 W m −2 , increasing to 9.65 W m −2 over urban areas, with substantial variability across both space and time. AHF increased urban mean 2 m air temperature by approximately ∼0.3°C and canopy air temperature by more than 1°C, with localized canopy warming exceeding 4°C in certain neighborhoods. Electrification and energy efficiency measures can substantially mitigate warming caused by AHF, with stronger cooling effects near highways....

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Tue, 1 Sep 2026 00:00:00 +0000

Atmospheric methane (CH₄) concentrations are accelerating global warming as net emissions increase. Observing systems that quantify sources remain too sparse and fragmented to detect trends-especially in remote regions where climate-driven natural emissions may be rising. We provide a framework for quantifying uncertainty reductions through the implementation of a global ecosystem-methane observing system designed to: (i) substantially lower uncertainty in sectoral and regional emissions, (ii) separate co-occurring anthropogenic and natural fluxes, and (iii) trend detection at regional scales to verify mitigation progress and provide early warning of natural feedbacks. Using bottom-up inventories and process-model ensembles for 2014-2023, we show that anthropogenic emissions remain uncertain by ∼32% globally, while natural sources-tropical and boreal-arctic wetlands, fires, and inland waters-carry far larger uncertainties (+ 70%) and trend uncertainties reaching ∼200%....

Imprint of Anthropogenic Sources and Soil Removal on the Surface Concentration of H2 in the Contiguous US

Mon, 24 Aug 2026 00:00:00 +0000

Hydrogen (H₂) is experiencing renewed interest throughout the world as a low carbon fuel alternative or complement to fossil fuels. Significant uncertainties remain regarding the environmental impact of increasing H₂ usage, in part due to gaps in our understanding of the H₂ atmospheric budget, including the H₂ release from industrial activities and the H₂ soil removal, the most important sink of H₂. This study focuses on H₂ dry air mole fractions measured by the NOAA Global Monitoring Laboratory in discrete ambient air samples collected every few days at sites located in the contiguous United States between 2010 and 2022. We take advantage of the long-term observations from this network to study the regional distribution of H₂ sources using the potential source contribution function (PSCF). We find that H₂ PSCF is consistent with a large anthropogenic source of atmospheric H₂...

Surface Quantitative Precipitation Estimates (SQUIRE) of Snow Water Equivalent from the Surface Atmospheric Integrated Field Laboratory

Fri, 21 Aug 2026 00:00:00 +0000

Abstract The upper Colorado River basin is the primary source of water for 40 million people. With declining snowpack in the basin, forecasting hydrological budgets in the Southwest United States is more important than ever. However, due in part, to a lack of reliable observations of precipitation in complex terrain, hydrological models struggle to assess and forecast snowpack snow water equivalent (SWE) in the upper Colorado River basin (UCRB). Therefore, the need for more reliable SWE forecasts in the UCRB motivated the U.S. Department of Energy Atmospheric Radiation Measurement Facility’s Surface Atmospheric Integrated Field Laboratory (SAIL) that occurred from June 2021 to June 2023. During SAIL, the X-band precipitation radar from Colorado State University conducted volume scans sampling the precipitation properties over the UCRB. The ARM facility developed a gridded Surface Quantitative Precipitation Estimates (SQUIRE) product from the radar observations. To do this, various...

Accelerating Bilevel Optimization With Hierarchical Many-Threaded Parallel Differential Evolution

Fri, 21 Aug 2026 00:00:00 +0000

Bilevel optimization is encountered in many relevant real-world applications. The main feature of this type of problem is that an upper-level optimization problem is constrained by a nested lower-level optimization problem. Because of this nested structure, bilevel problems (BLPs) are usually computationally expensive to solve. Differential evolution (DE) has demonstrated promising results in solving BLPs of relatively small scales. As the problem scale increases, the decision space becomes intrinsically larger, requiring a growing number of function evaluations for the method to work properly. In this context, heavy parallelization and high-performance computing techniques are indispensable to enable the resolution of more complex and challenging optimization problems. Hence, we propose a hierarchical many-threaded parallel DE approach for BLPs, where both levels are parallelized. The computational experiments demonstrate that the parallel implementation achieved runtime speeds...

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Thu, 20 Aug 2026 00:00:00 +0000

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill,...

Snow-eater heat waves of the western United States

Thu, 20 Aug 2026 00:00:00 +0000

Abrupt snowmelt, triggered by rain-on-snow events or "snow-eater heat waves," can cause flooding, initiate or accelerate snow drought, and affect water availability. However, the characteristics (e.g., area, duration, and frequency), impacts, and trends of snow-eater heat waves have received little attention. To address this gap, we developed a method to identify snow-eater heat waves and estimate their melt potential using 20th Century Reanalysis version 3 air temperature data, the TempestExtremes algorithm, and an operational snowmelt model (SNOW-17) across 1850-2015. Melt season snow-eater heat waves typically last 3 to 5 days, with three to five events, doubling snowmelt rates. Seven of 11 spring superfloods are shown to coincide with snow-eater heat waves. Since the 1850s, snow-eater heat waves have increased in area and frequency, decreased in duration, and shifted earlier in the melt season. Incorporating snow-eater heat-wave impacts into SNOW-17 enhances extreme melt estimates,...

Wind stilling shapes grassland water use efficiency by enhancing soil moisture retention

Tue, 4 Aug 2026 00:00:00 +0000

Covering more than 40% of Earth's vegetated surface, grasslands critically regulate terrestrial carbon and water cycles. Their ecosystem water use efficiency (WUE_eco), the ratio of carbon uptake to water loss, governs drought resilience in these water-limited ecosystems. While global terrestrial wind speed declined substantially from the 1960s to 2000s followed by a recovery in the subsequent decade, the extent and mechanisms of its influence on grassland WUE_eco remain poorly understood. Using site observations, satellite data, Earth system models, and wind manipulation experiments, we found a consistent negative sensitivity of grassland WUE_eco to wind speed. Mechanistically, declining winds reduce evaporative water loss, improve soil moisture, and promote stomatal opening, thereby enhancing carbon uptake. Wind speed changes accounted for 7.7 to 25.7% of WUE_eco increases under historical and future climates, making wind the second most...

Soil fertility controls on tropical forest productivity and mortality: synthesis and roadmap

Thu, 30 Jul 2026 00:00:00 +0000

Tropical forests are highly diverse and productive ecosystems and store nearly 60% of vegetation biomass. Across the tropics, forests span large gradients of soil fertility, from vast regions situated on highly weathered, ancient geological formations to others on young, nutrient-rich landscapes. Tropical forest productivity, mortality, and biomass all vary systematically across these gradients in soil fertility. Aboveground forest productivity tends to increase with higher soil fertility, while counterintuitively, aboveground biomass does not increase proportionally. This disconnect is likely due to coinciding increases in mortality with higher soil fertility. However, we know relatively little about the mechanisms underlying how soil fertility regulates productivity or mortality - two critical determinants of forest biomass - and even less about how these relationships will shape tropical forest responses to global change. Here, we present a mechanistic framework for understanding...

ENVnet provides a global molecular resource of dissolved organic matter

Thu, 30 Jul 2026 00:00:00 +0000

Dissolved organic matter (DOM) is a central component of Earth’s carbon cycle and one of the planet’s most chemically diverse pools, yet the molecular structures of its constituents remain largely unresolved. This limitation has hindered our ability to link DOM composition to microbial processes and ecosystem function. Here we present ENVnet, a global molecular repository built from tandem mass spectrometry data collected across 13 terrestrial and aquatic environment types, including 419 newly generated samples that expand publicly available DOM metabolomics data and cover previously underrepresented environments. By computationally deconvolving chimeric mass spectra, a longstanding challenge in environmental metabolomics, we recover high-quality fragmentation data for >22,000 distinct molecular features (defined by a specific precursor mass and fragmentation pattern). Using ENVnet, we uncover conserved and environment-specific molecular patterns in DOM composition and underlying...

The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System

Wed, 29 Jul 2026 00:00:00 +0000

Abstract The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol‐cloud interactions, convection, and microphysics. The ocean features a new time‐stepping scheme and a higher‐resolution unstructured mesh with sub‐ice‐shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub‐grid topographic treatment of solar radiation. A new tri‐grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non‐linear remapping between the atmosphere and land. E3SMv3...

Flux Footprints: A Critical Link to Bridge Eddy‐Covariance Measurements With Models, Remote Sensing, and Other Observations

Tue, 28 Jul 2026 00:00:00 +0000

Global networks of eddy-covariance flux towers play a pivotal role in enhancing our predictive understanding of carbon and water cycling of biological systems in response to regional and global environmental change. Despite their broad application in numerous studies, the spatial aspects of the flux measurements have often been ignored or treated ambiguously, thereby remaining a primary source of uncertainty. The area contributing to the flux-referred to as the flux footprint-varies over time depending on wind direction, atmospheric turbulence, effective measurement heights, surface characteristics, and mesoscale forcings. The footprint dynamics, along with underlying source-sink heterogeneity, lead to spatial and temporal variability in the sensed fluxes, complicating the interpretation of flux data and their integration with a range of observations and models. This article addresses this critical link by reviewing the most up-to-date research, identifying knowledge gaps and...

LocatingUndocumentedWells Using Historical Oil andGas Exploration Maps: A Case Study in Osage County, Oklahoma

Tue, 28 Jul 2026 00:00:00 +0000

Undocumented oil and gas wells lack reliable information about their locations and characteristics, making them difficult to identify. These wells can result in unanticipated delays and costs in the development of nearby surface and subsurface resources, and, if improperly plugged, can cause contamination. This study leverages historical petroleum exploration maps to locate such wells, focusing on Osage County, Oklahoma. Two sets of early 20th century oil and gas exploration maps by the United States Geological Survey were georeferenced and analyzed using a computer vision model to detect well symbols. The locations of detected wells were compared to the location of known wells in the database from the Bureau of Indian Affairs Osage Agency to identify potential undocumented wells. The analysis yielded over 500 potential undocumented wells, with dry holes constituting the largest fraction. Field verification confirmed the presence of some undocumented wells. Comparison with prior...

Divergent carbon use efficiency-growth rate tradeoff in popular biological growth models

Wed, 22 Jul 2026 00:00:00 +0000

Carbon use efficiency (CUE) is an important trait emerging from processes regulating biological growth. CUE can be computed either based on the growth of structural biomass or total biomass divided by substrate uptake rate. Nonequilibrium thermodynamics and observations suggest that, for an exponentially growing population of cells, structural biomass CUE should first increase, then peak, and finally decrease with specific growth rate; meanwhile, total biomass CUE increases asymptotically with specific growth rate. We compared predictions from six popular models that are often used for plant and microbial growth in existing ecosystem models. We found that, for an exponentially growing population of biological cells, (1) the source-driven Pirt and Compromise models predict that structural biomass CUE increase asymptotically with growth rate; (2) the apparent sink-driven modified Droop model predicts that structural biomass CUE decreases with growth rate; and (3) the sink-driven...

Warming and snow loss increase reliance on old groundwater in a Colorado River headwater

Tue, 21 Jul 2026 00:00:00 +0000

Atmospheric warming is reducing snowpack, with uncertain effects on mountainous streamflow, a crucial water resource. Despite limited historical observations of groundwater–streamflow interactions above 2,500 m, new measurements in the Upper Colorado River headwaters indicate declining groundwater storage that is dated decades to millennia old. Here we use integrated hydrologic modelling spanning water years 2015–2021 to determine whether the loss of old-age groundwater buffers streamflow during low-snow years and whether that loss is exacerbated with warming. Results show that old-groundwater contributions to streams remain relatively steady through time, unlike the more variable contributions from young groundwater. Numerical experiments of increased surface air temperatures (+2.5 °C and +4 °C) increase rain–snow fractions and evapotranspiration and decrease runoff ratio by 2–3% per degree Celsius increase. As streamflow declines with warming, the age of groundwater supporting...

A Statistician’s Overview of Physics-Informed Neural Networks for Spatio-Temporal Data

Thu, 16 Jul 2026 00:00:00 +0000

The recent success of deep neural network models with physical constraints (so-called, Physics-Informed Neural Networks, PINNs) has led to renewed interest in the incorporation of mechanistic information in predictive models. Statisticians and others have long been interested in this problem, which has led to several practical and innovative solutions dating back decades. In this overview, we focus on the problem of data-driven prediction and inference of dynamic spatio-temporal processes that include mechanistic information, such as would be available from partial differential equations, with a strong focus on the quantification of uncertainty associated with data, process, and parameters. We give a brief review of several paradigms and focus our attention on Bayesian implementations given they naturally accommodate uncertainty quantification. We then show that it is straight-forward to include the Bayesian PINN (B-PINN) within the Bayesian hierarchical model (BHM) framework...

Improving energy efficiency while reducing anthropogenic heat from buildings: how retrofits influence the building stock and urban microclimate in Los Angeles

Thu, 16 Jul 2026 00:00:00 +0000

Anthropogenic heat (AH) from buildings contributes to urban overheating, especially during heat waves, yet building retrofit studies usually evaluate energy savings without assessing impacts on AH. This study quantifies how common building retrofit measures affect both building energy use and AH emissions across the City of Los Angeles. Using a bottom-up urban building energy modeling framework coupled with high-resolution local weather from the Weather Research and Forecasting model with Building Effect Parameterization (WRF-BEP), we evaluate eleven retrofit measures and two multi-measure retrofit packages. HVAC and LED lighting retrofits provide the largest city-wide annual site energy savings, while roof coating is most effective for reducing AH. A package optimized for energy savings reduces summer site energy use by about 32% (2.3 TWh), while a package incorporating AH-focused measures reduces the total AH by over 50% (137 PJ) with minimal difference in energy savings. The...

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Wed, 15 Jul 2026 00:00:00 +0000

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and...

Evaluating Soil Carbon Models for Sub‐Saharan Africa: Revealing Knowledge Gaps in Subtropical and Tropical Soil Biogeochemistry

Tue, 14 Jul 2026 00:00:00 +0000

Abstract Process‐based soil carbon (C) models are increasingly used to project regional and global C cycle responses to climate change. However, the development and evaluation of these models has largely focused on temperate regions of North America and Europe. This geographic bias raises a critical question: Do these models capture generalizable mechanisms that can be applied to underrepresented pedological regions or encode processes specific to their developmental context? We evaluated three process‐based models—Century, Millennial, and MIMICS—across 777 topsoil samples spanning the climate and pedological diversity of sub‐Saharan Africa. Despite their differences in mechanistic detail, all three models performed similarly (adjusted R 2 = 0.09–0.18) in predicting soil organic carbon (SOC) stocks. Using random forest algorithms trained on observed and modeled SOC data, we identified divergences between the drivers of SOC. All three models overemphasized net primary...

Long-term warming of a forest soil reduces microbial biomass and its carbon and nitrogen use efficiencies

Tue, 14 Jul 2026 00:00:00 +0000

Global warming impacts biogeochemical cycles in terrestrial ecosystems, but it is still unclear how the simultaneous cycling of carbon (C) and nitrogen (N) in soils could be affected in the longer-term. Here, we evaluated how 14 years of soil warming (+4 °C) affected the soil C and N cycle across different soil depths and seasons in a temperate mountain forest. We used H2 18O incorporation into DNA and 15N isotope pool dilution techniques to determine gross rates of C and N transformation processes. Our data showed different warming effects on soil C and N cycling, and these were consistent across soil depths and seasons. Warming decreased microbial biomass C (−22%), but at the same time increased microbial biomass-specific growth (+25%) and respiration (+39%), the potential activity of β-glucosidase (+31%), and microbial turnover (+14%). Warming reduced gross rates of protein depolymerization (−19%), but stimulated gross N mineralization (+63%) and the potential activities...

Congo Basin Carbon Cycle Responses to Global Change

Tue, 14 Jul 2026 00:00:00 +0000

The Congo Basin and its contiguous forests harbor globally significant carbon stocks, estimated at 65 gigatons of C (GtC) above and belowground. Despite rising temperatures and intensifying droughts, they have remained a carbon sink, albeit weak: 0.26-0.50 GtC yr.^-1 carbon uptake since 1980. However, these forests' carbon stocks and fluxes, including gross primary productivity, respiration, net primary productivity, and riverine carbon transport, remain poorly quantified. This limits understanding of the region's role in the global carbon cycle, its vulnerability to environmental change, and its potential as a long-term carbon sink. We review and quantify Congo Basin and contiguous forest carbon stocks and fluxes and synthesize the current knowledge on how key global change drivers shape the region's carbon cycle. We find limited responses to long-term precipitation variability, but declining stocks and fluxes in response to long-term and increasing temperature and...

Increased Belowground Carbon Allocation Reduces Soil Carbon Losses Under Long‐Term Warming

Tue, 14 Jul 2026 00:00:00 +0000

The response of the carbon cycle in forests to global warming could lead to a positive climate feedback if warming accelerates the mineralization of soil organic carbon (SOC), thereby causing net emissions of CO₂ into the atmosphere. In Europe, carbon-rich alpine forest soils could be particularly affected by global warming, as a greater rise in temperature is expected in this region than the global average. Here we show that nearly two decades of experimental soil warming (+4°C during the snow-free seasons) in a mountain forest in the Northern Limestone Alps significantly (~13% per 1°C warming) and persistently (no change in response over 18 years) increased soil CO₂ effluxes. The SOC stocks in the warmed plots decreased compared to controls, yet non-significantly, and quantitatively much less than the surplus carbon outflux from warmed soil suggests. We attribute the increase in soil CO₂ efflux primarily to stimulation of root respiration, which...

The Role of Tropical Cyclone—Ocean Interactions in Future Changes in Hurricane Katrina

Tue, 23 Jun 2026 00:00:00 +0000

Abstract Tropical cyclone (TC) intensity and precipitation are projected to increase in the future. However, some projections are based on atmosphere‐only models in which sea surface temperatures are prescribed, whereas projections based on global atmosphere‐ocean coupled models can be subject to long‐term ocean biases. We investigated the role of TC‐ocean interactions in future changes in TC intensity and precipitation in Hurricane Katrina. We performed four‐member ensembles using convection‐permitting atmosphere‐only and atmosphere‐ocean regional models for the historical climate and four future climates. We found that although future TC intensity and precipitation increased regardless of ocean coupling, ocean coupling dampened the future minimum sea‐level pressure decrease by half and amplified future precipitation scaling. Compared to future changes in upper‐ocean temperature, changes in salinity contributed little to future changes in TC intensity. This study highlights the...

Unprecedented Shifts in Hydrology Are Emerging Across California's Critical Basins: An Evaluation From 0.5 to 3.5°C

Thu, 18 Jun 2026 00:00:00 +0000

Abstract With advances in climate models and downscaling techniques, stakeholders anticipate high‐resolution analysis to inform regional to local changes in water management. Here, we produce hydrologic projections from an ensemble of Earth System Models (ESMs) that were selected and downscaled to support California's 5th Climate Assessment. An ensemble of 19 ESMs was downscaled to a 3‐km resolution across California using a statistical‐dynamical downscaling approach and subsequently run through two calibrated hydrology models. Although California has been extensively studied in the context of climate change, we provide the first evaluation of the warming thresholds at which hydroclimate metrics demonstrate statistically significant shifts. We show that present‐day to near‐term warming levels in Klamath and Northern Sierra Nevada basins, which serve as a critical source of water for California, show statistically significant decreases in snowfall and peak snowpack and associated...

Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning

Thu, 11 Jun 2026 00:00:00 +0000

Measurement of methane fluxes (FCH₄) from natural systems, such as wetlands, has lagged far behind carbon dioxide fluxes. Short and fragmented wetland FCH₄ data limit our ability to assess its long-term dynamics and potential climate feedbacks. Extrapolating short-term FCH₄ records to recent decades remains challenging for both process-based models and data-driven machine learning (ML) approaches. Here, we develop a knowledge-guided ML framework that integrates eddy covariance (EC) FCH₄ observations, field warming experiments, and biogeochemical knowledge to reconstruct the long-term FCH₄ budgets and trends. Focusing on the 11 longest EC monitoring sites in the AmeriFlux network, we found considerable variability in multi-decadal trends of wetland FCH₄, with increases up to 14% per decade from 2000 to 2024. We also found that the strength of these increasing trends declines from high to low latitudes, highlighting...

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Wed, 10 Jun 2026 00:00:00 +0000

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets:...

Emergent constraints on future methane emissions from global wetlands

Wed, 10 Jun 2026 00:00:00 +0000

Future methane (CH4) emissions from natural wetlands are predicted to increase due to global warming, leading to positive feedback on climate change. However, the magnitude of this increase remains highly uncertain. Here we present novel ensemble simulations of seven state-of-the-art terrestrial biosphere models to estimate wetland CH4 emissions (eCH4) during the twenty-first century. Our estimates suggest that for every 1 °C increase in global land surface temperature, there is a 24 ± 10 Tg CH4 yr−1 increase in eCH4. We also identify an emergent relationship between contemporary temperature dependence and projected eCH4. When constrained by 163 site-year eddy-covariance measurements of eCH4, we show that wetland emissions can increase by 50–60% by the 2090s relative to the 2010s under a high-warming scenario. The projected decadal increase in eCH4 from the 2010–2019 baseline to the 2030s would very likely (90% probability) offset an amount equivalent in scale to 8–10% of anthropogenic...

Compound Mesoscale Convective Systems and Low‐Pressure Systems in Tropical Monsoon Regions: Assessing Their Meteorology and Precipitation

Wed, 10 Jun 2026 00:00:00 +0000

Abstract Mesoscale convective systems (MCS) and low‐pressure systems (LPS) are both strongly associated with precipitation across the regions where they occur, particularly within global monsoon systems; however, their co‐occurrence and its relationship to precipitation have not been systematically examined. Here, we use LPS and MCS trackers to detect compound MCS and LPS events in five monsoon regions and assess the association of this co‐occurrence with anomalies of winds, precipitation, and other atmospheric variables. Additionally, we investigate the spatial distribution of precipitating MCS and LPS events. Our results show that most (∼60%) MCS and LPS co‐occurrences are located in the lower latitudes, where they contribute up to 40% of annual precipitation. We find that compound events generally produce more extreme precipitation than MCS‐only or LPS‐only events. Furthermore, our assessment of the synoptic and mesoscale composites reveals that the underlying dynamics of compound...

Machine-learning-based estimates of global natural vegetated wetland methane emissions (2000–2025)

Wed, 10 Jun 2026 00:00:00 +0000

Wetlands are the largest natural source of atmospheric methane (CH 4 ), yet comprehensive global budgets are typically delayed by years, preventing a timely understanding of CH 4 sources, sinks, and trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates using a machine-learning emulator to reconstruct spatially explicit monthly emission fields at 1° × 1° resolution. We apply this framework to a global dataset of natural vegetated wetland CH 4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record that covers the 2000–2020 emissions through 2025. In the test data (∼ 30 % of the total dataset), the emulator achieved a global R 2 of 0.65 ± 0.003 (mean ± 95 % CI, hereafter) and an RMSE of 5.49±0.12×10-3 Tg CH 4 yr −1 . The emulator is trained on 35 GMB model estimates, including 22 process-based models and 13 atmospheric inversions, paired with 10 ensemble...

Leveraging Crowdsourced Data for Extreme Heat Monitoring

Wed, 3 Jun 2026 00:00:00 +0000

ABSTRACT The combined effects of urban microclimate heterogeneity and climate change exacerbate the disproportionate impact of heatwaves on urban areas, a trend expected to intensify. Crowdsourcing is a promising tool to monitor temperatures at a high spatiotemporal scale, which is now deemed critical. However, quality control is essential before the use of such data. Traditional quality control methods often fail to capture short extreme weather events like heatwaves, as they frequently eliminate crucial observations from these intense, brief episodes. Here, a quality control methodology, tailored to short‐term heatwaves built on existing quality control methods, is introduced and tested on crowdsourced monitoring networks for five North American cities and three heatwave episodes. This framework is centred around a systematic comparison with traditional weather stations. The results show that the designed procedure can effectively filter out false data points and corrupt stations...

Identification of Rac guanine nucleotide exchange factors promoting Lgl1 phosphorylation in glioblastoma.

Thu, 21 May 2026 00:00:00 +0000

The protein Lgl1 is a key regulator of cell polarity. We previously showed that Lgl1 is inactivated by hyperphosphorylation in glioblastoma as a consequence of PTEN tumour suppressor loss and aberrant activation of the PI 3-kinase pathway; this contributes to glioblastoma pathogenesis both by promoting invasion and repressing glioblastoma cell differentiation. Lgl1 is phosphorylated by atypical protein kinase C that has been activated by binding to a complex of the scaffolding protein Par6 and active, GTP-bound Rac. The specific Rac guanine nucleotide exchange factors that generate active Rac to promote Lgl1 hyperphosphorylation in glioblastoma are unknown. We used CRISPR/Cas9 to knockout PREX1, a PI 3-kinase pathway-responsive Rac guanine nucleotide exchange factor, in patient-derived glioblastoma cells. Knockout cells had reduced Lgl1 phosphorylation, which was reversed by re-expressing PREX1. They also had reduced motility and an altered phenotype suggestive of partial neuronal...

Participatory modeling in the AI era

Tue, 5 May 2026 00:00:00 +0000

PM is a now established approach to improve the utility and actionability of modeling for decision making and management. With the advent of the AI era, there are multiple avenues for its use in the context of PM. We reviewed a number of recent papers that describe how various AI tools have been used to assist the PM process, both in improving the quality of modeling and the participation efficiency. We have identified AI applications that can help stakeholders in the process of knowledge acquisition and decision making during the steps of the PM process. We also looked at how AI has been put to several innovative uses in PM related areas, such as collective intelligence, deliberative democracy and participatory governance, and how these can be adopted and used in the PM process. These enhancements escalate in degree of AI intervention and autonomy. They start with augmenting approaches such as informing, modeling and data processing, and can lead to deeper AI engagement such...

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Fri, 24 Apr 2026 00:00:00 +0000

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience...

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Thu, 23 Apr 2026 00:00:00 +0000

Abstract Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space‐for‐time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water‐limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall....

Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity

Thu, 23 Apr 2026 00:00:00 +0000

Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy...

A global methane observation system to track climate feedbacks for verifiable climate impact

Wed, 22 Apr 2026 00:00:00 +0000

Methane measurements, particularly of natural sources, need to be expanded considerably.

Contrasting Parametric Sensitivities in Two Global Vegetation Models Using Parameter Perturbation Ensembles

Wed, 15 Apr 2026 00:00:00 +0000

Abstract Uncertainty in land model projections remains high and the roles of parametric and structural uncertainty are difficult to disentangle. To compare parametric sensitivity across model structures we present two parameter perturbation ensembles using the Community Land Model (CLM) operating in satellite phenology mode. The ensembles contrast two vegetation modules: (a) the default CLM vegetation module and (b) the Functionally Assembled Terrestrial Ecosystem Simulator (CLM‐FATES). We perturbed over 300 parameters and quantified their effects on biophysical fluxes globally and across biomes. Most parameters have minimal impact on biophysical fluxes, with only a few substantially influencing results. While both models exhibit similar parameter sensitivity for some fluxes, CLM‐FATES shows larger spread in gross primary productivity (GPP), driven by strong sensitivity to carboxylation rate. CLM‐FATES also shows a weaker GPP response to soil hydrology parameters and exhibits...

Recent Increasing Trend in October–November Caribbean Tropical Cyclone Activity

Tue, 14 Apr 2026 00:00:00 +0000

Abstract October–November Caribbean tropical cyclone (TC) activity has significant impacts for both the Caribbean islands and Central America (e.g., Hurricanes Eta and Iota in 2020). October–November Caribbean TCs can also track northward and make continental United States landfall, resulting in substantial damage and fatalities (e.g., Hurricane Michael in 2018 and Delta and Zeta in 2020). We find significant increasing trends in October–November Caribbean hurricanes, rapidly intensifying hurricanes (winds increasing by ≥15 m s −1 within 24 hr), and landfalling hurricanes during the global satellite era (1979–present). Since 1979, we also observe significant warming trends in the western Atlantic Warm Pool and anomalous relative cooling in the eastern Pacific during October–November. These trends yield a more conducive dynamic and thermodynamic environment for Caribbean TCs, including reductions in Caribbean vertical wind shear, increases in Caribbean...

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed

Thu, 2 Apr 2026 00:00:00 +0000

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically...

Depth of nutrient uptake by deep-rooted plants is regulated by water availability

Mon, 30 Mar 2026 00:00:00 +0000

The capacity of some plants to access water and nutrients at depths greater than one meter is a critical functional trait that confers resistance to drought and impacts both belowground and shallow soil processes. Here, we report water and strontium isotopic data from an alpine meadow transect showing the correlation between water and nutrient acquisition depths. The isotopic compositions of Sr (⁸⁷Sr/⁸⁶Sr ratio) and water in rock and soil, and in plant leaf tissues, reveal that deeper-rooted plants acquire a higher proportion of water, Sr, and cation nutrients that are derived from the saprolite, a zone of silicate weathering, than shallow-rooted grass. A three-decade dendrochemical record reveals that reductions of wet precipitation drive deep-rooted plants to acquire cation nutrients from deeper saprolite or bedrock regions. Thus, the depth of cation nutrient acquisition by deep-rooted plant species at this site is tightly coupled with, and likely determined...

Dataset about Warming Effects on Carbon Cycling and Greenhouse Gas Fluxes in Permafrost Ecosystems

Fri, 27 Mar 2026 00:00:00 +0000

Field observations provide direct evidence of how does carbon cycling in permafrost ecosystems respond to climate change. This study provides a comprehensive dataset on the impact of warming on carbon cycling and greenhouse gas (GHG) fluxes in permafrost ecosystems. The dataset is extracted and integrated from 132 peer-reviewed studies with 1430 paired observations across eight major permafrost ecosystems, including Arctic and subarctic tundra and wetland, and alpine meadow, steppe, tundra and wetland. This dataset includes 17 variables from experiments conducted during the growing season, covering the plant and soil carbon pools, soil nitrogen pool, and GHG (i.e., CO2, CH4, and N2O) fluxes, among others. Background information on site climate conditions, vegetation and soil characteristics, and details of the warming experiments, including timing, methods, and warming magnitude, are also contained in the dataset. This dataset facilitates a comprehensive understanding of the impact...

A tale of two towers: comparing NEON and AmeriFlux data streams at Bartlett Experimental Forest

Thu, 19 Mar 2026 00:00:00 +0000

Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. We focused our analysis on standard meteorological variables; fluxes of CO2, sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO2 and latent heat fluxes occurred at the annual scale, with...

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Wed, 18 Mar 2026 00:00:00 +0000

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related...

Thermal stress in degraded forests in the Brazilian Amazon Arc of Deforestation

Fri, 13 Mar 2026 00:00:00 +0000

Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled...

Topography and functional traits shape the distribution of key shrub plant functional types in low-Arctic tundra

Wed, 11 Mar 2026 00:00:00 +0000

The expansion of shrubs in the Arctic tundra fundamentally modifies land-atmosphere interactions. However, it remains unclear how shrub distribution and expansion differ across key species due to challenges with discriminating tundra plant species at regional scales. Here, we combined multi-scale, multi-platform remote sensing and in situ trait measurements to elucidate the distribution patterns and primary controls of two representative deciduous-tall-shrub (DTS) genera, Alnus and Salix, in low-Arctic tundra. We show that topographic features were a key control on DTSs, creating heterogeneous, but predictable distributions of Alnus and Salix fractional cover (fCover). Alnus was more tolerant of elevation and slope and was found on hilly uplands (slope >10°) within a specific elevational band (200-400 m above sea level [MSL]). In contrast, Salix occurred at lower elevations (50-300 m MSL) on gentler slopes (3-10°) and required...

Tradeoffs between uniform land protection and biodiversity-specific land protection with <2 °C global warming

Tue, 10 Mar 2026 00:00:00 +0000

Nearly 200 countries have pledged to conserve 30% of terrestrial ecosystems to stop the global biodiversity crisis. However, biodiversity is not uniformly distributed across countries. Adequately addressing this crisis requires a scientific basis for selecting protected land that considers both ecological benefits and impacts to humans. We use the global change analysis model to evaluate land use tradeoffs of four land protection cases under two climate cases. We find that biodiversity-specific land protection up to 39% globally can reduce land use constraints and food prices compared to protecting 30% of land uniformly in each country (’30 × 30’ initiative). Valuing terrestrial carbon for climate change mitigation reduces land conversion pressure and can complement protection strategies. Global impacts to agriculture of additional land protection are small, but regional impacts vary and may be considerable. Overall, biodiversity-specific land protection has greater potential...

Radiative, Hydrologic, and Circulation Responses to Warming in Cess‐Potter Simulations Using the Global 3.25‐km SCREAM

Tue, 10 Mar 2026 00:00:00 +0000

Abstract Using the global 3.25‐km Simple Cloud Resolving E3SM Atmosphere Model (SCREAM 3 km), a pair of 13‐month Cess‐Potter simulations are performed to quantify the radiative feedbacks and the hydrologic and circulation responses to warming. Large‐scale aspects of SCREAM 3 km's top‐of‐atmosphere radiative fluxes, precipitation rates, and circulations are in good agreement with observations and reanalysis, with notable differences, including a drier lower free‐troposphere in the Tropics, reduced precipitation and humidity over the Tropical West Pacific, and poleward shifted Southern Hemisphere midlatitude jet. In response to warming, SCREAM 3 km predicts a total radiative feedback within the top 15% of the CMIP5 and CMIP6 models, which puts it substantially higher than the feedback reported by other kilometer‐scale models. SCREAM 3 km's high radiative feedback stems from a strongly positive shortwave cloud feedback, most prominent over the mid‐ and high‐latitudes....

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Fri, 6 Mar 2026 00:00:00 +0000

Abstract Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of...

Duration of super-emitting oil and gas methane sources

Thu, 26 Feb 2026 00:00:00 +0000

The duration of super-emitting events (>100 kg h-1) in oil and gas basins remains insufficiently understood but is key for reporting programs and mitigation strategies. Carbon Mapper conducted aerial surveys from April 30 to May 17, 2024, over the New Mexico Permian Basin, covering 276,000 wells, 1100 compressor stations, 175 gas processing plants, and 27,000 km of pipeline. We find over 500 super-emitting sources with 300 of these sources observed repeatedly across multiple days. We quantify total super emissions by integrating individual events with observationally constrained event durations (5.98 −14.7 Gg CH4) and compare to total emissions derived from basin average snapshots (12.7 ± 0.92 Gg CH4). This gap between emission estimates is reconciled through assumptions on missed detections, characteristic event duration, detection frequency, and diurnal variability. Emission events generally lasted for at least 2 hours, and a small subset of sources (18 total), persistently...

Long-term soil warming decreases fungal biomass and alters fungal but not bacterial communities in a temperate forest

Tue, 24 Feb 2026 00:00:00 +0000

Long-term soil warming may alter microbial community structure and functioning in forest soils, thereby affecting carbon and nutrient cycling processes. We examined the effects of >14 years of soil warming (+4°C during snow-free seasons) on the fungal biomass marker ergosterol, and on fungal and bacterial communities in a spruce dominated mountain forest in the Austrian Alps. Soil warming decreased ergosterol, and the ergosterol-to-microbial biomass carbon (MBC) ratio at 0-10 and 10-20 cm soil depth, with a stronger decline in ergosterol, indicating a higher sensitivity of fungi than bacteria to long-term warming. Warming also shifted the fungal community at both soil depths, favoring Boletus luridus, an ectomycorrhizal (ECM) fungus, which emerged as the dominant OTU in warmed plots. The dominance of ECM over saprotrophic fungi (SAP) under warming at topsoil likely resulted from increased fine root production and enhanced competition for substrates and nutrients. Bacterial...

Water availability modulates maximum canopy heights of low-elevation Amazonian second-growth forests

Tue, 17 Feb 2026 00:00:00 +0000

Tropical second-growth forests of the Amazon sequester large amounts of carbon and are important carbon sinks, contributing substantially to climate change mitigation, biodiversity conservation, and providing crucial ecosystem services. Deforestation due to selective logging and shifting cultivation is expanding second-growth forest areas in tropical forest regions, which if well managed, regenerate rapidly over time. Maximum forest canopy height is an important metric of biomass and carbon accumulation in second-growth forests and is strongly influenced by water availability. The water limitation hypothesis explains the positive influence of water availability on maximum tree heights and has been examined and demonstrated at a small-scale using field data, and at a global scale, with limited accuracy, using remote sensing data in tropical ecosystems. However, this hypothesis concerning maximum canopy height has not been much studied at regional and national scales for tropical...

The Influence of African Easterly Waves on Atlantic Tropical Cyclone Tracks and Landfall in Large Ensembles

Wed, 11 Feb 2026 00:00:00 +0000

Abstract African easterly waves (AEWs) are an important precursor or “seed” for Atlantic tropical cyclones (TCs), with 60%–80% of major hurricanes observed to originate from AEWs. However, climate model simulations indicate that AEWs are not necessary to maintain annual Atlantic TC frequency. Furthermore, small ensembles suggest that AEWs may impact the spatial distribution and landfall of Atlantic TCs. Here, we investigated the influence of AEWs on the spatial distribution of Atlantic TC tracks and landfall using 50‐member ensembles of TC‐permitting regional model simulations for five hurricane seasons characterized by different levels of TC activity. The control simulations are seasonal hindcasts in which AEWs were prescribed through the eastern lateral boundary condition using reanalysis. In the experiments, we suppressed AEWs by applying a 2–10 day filter to the eastern lateral boundary condition. In response to AEW suppression, we discovered statistically significant...

Characterizing the vertical structure of forests in the Brazilian Amazon

Tue, 10 Feb 2026 00:00:00 +0000

Little is known about the structure of tropical forests despite its critical role in the provisioning of ecosystem services. Here we assess the vertical structure of forests in the Brazilian Amazon with a large-scale airborne LiDAR dataset. We show that fire has greater impact in the lowest forest strata, differently from selective logging and windthrow. We also find that secondary forests quickly recover or even exceed reference areas at the 1-10 m height stratum but that full recovery for the 20-30 m height stratum has not been achieved even after 35 years. Our modeling results suggest that proximity to roads, elevation, precipitation, soil pH, and proportion of sand in the soil are the most important predictors of forest structure. Finally, we identify 5 forest structural types (FSTs) and use them to visualize the spatial distribution of forest structure. This study provides important information for forest monitoring, management, and conservation.

Microbial inoculants and invasions: a call to action

Wed, 28 Jan 2026 00:00:00 +0000

Microbial inoculants are increasingly used for beneficial purposes in agriculture, bioremediation, and medicine, but they can carry risks of generating invasive microbes. Here, we present a roadmap for guarding against these invasions, proposing developing (i) coherent mechanistic understandings of how microbial inoculants can effect invasions, (ii) predictive models forecasting microbial invasion risks, and (iii) effective management strategies. To guide mechanistic understandings, we distill 17 guiding hypotheses. For predictive modeling, we highlight data collection needs and qualitative approaches. For management strategies, we stress the importance of accurately weighing the risks against benefits. The unified approach presented here provides a route toward an effective research and management infrastructure for microbial inoculants in order to avoid potentially catastrophic microbial invasions.

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity

Tue, 27 Jan 2026 00:00:00 +0000

Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity....

Future implications of enhanced hydroclimate variability and reduced snowpack on California’s water resources

Tue, 27 Jan 2026 00:00:00 +0000

The Sierra Nevada snowpack, which supplies sixty percent of California’s consumptive water use, is under threat due to anthropogenic climate change. While previous studies have examined the impacts of climate change on mountain snowpack in the Sierra Nevada and across the Western US, few have quantified the risks to monthly irrigation water resources posed by shifting hydroclimate patterns and declining snowmelt runoff. Because they use coarse-resolution models, existing global-scale studies lack regional specificity, while existing regional studies rely on statistical or dynamical ‘downscaling’ of coarse-resolution global models. We use a new simulation of the variable resolution Community Earth System Model 2, which provides high spatiotemporal resolution estimates (14 km horizontal grid spacing, daily-to-hourly outputs) of California’s historical and future hydroclimate. We leverage the US Geological Survey’s recent irrigation water use reanalysis to evaluate basin-scale irrigation...

High-resolution mountain topography can inform global snow vulnerability estimates

Tue, 27 Jan 2026 00:00:00 +0000

Snow is changing globally. Computationally intensive snow reanalysis products and downscaled climate model projections allow for the estimation of historical and projected changes in snow over ∼4–10 km resolutions, but these resolutions are coarse relative to the scales needed for water supply and flood planning. Fine-scale digital elevation models (DEMs) are widely available but are underutilized to make first-order assessments of snow vulnerability. Here, we leverage DEMs at a 7.5 arc s (∼250 m) resolution, combining these with historical freezing level height estimates from ERA-5 to derive estimates of changes in the snow-receiving area (SRA) and its variability across global mountain ranges. Results show estimated SRA declines in 29% (1.9 million km2) of the global mountain area from 1982–2020; 66% of the mountainous areas had no change over the historical period. At +1.5 °C of warming relative to the pre-industrial control, global mountain SRA would decline by 9.5% (1.0 million...

Multi-omics reveals nitrogen dynamics associated with soil microbial blooms during snowmelt

Tue, 27 Jan 2026 00:00:00 +0000

Snowmelt triggers a soil microbial bloom and crash that affects nitrogen (N) export in high-elevation watersheds. The mechanisms underlying these microbial dynamics are uncertain, making soil nitrogen processes difficult to predict as snowpack declines globally. Here, integration of genome-resolved metagenomics, metatranscriptomics and metabolomics in a high-elevation watershed revealed ecologically distinct soil microorganisms linked across the snowmelt time-period by their unique nitrogen cycling capacities. The molecular properties and transformations of dissolved organic N suggested that degradation or recycling of microbial biomass provided N for biosynthesis during the microbial bloom. Winter-adapted Bradyrhizobia spp. oxidized amino acids anaerobically and had the highest gene expression for denitrification during the microbial bloom. A pulse of nitrate was driven by spring-adapted Nitrososphaerales after snowmelt, but dissimilatory nitrate reduction to ammonia (DNRA) gene...

Agile Allocation in the Tundra: A Single Growing Season of Warming Increases Nutrient Availability While Decreasing Fine-Root Length

Tue, 27 Jan 2026 00:00:00 +0000

The majority of plant biomass is located belowground in Arctic ecosystems and plant roots are responsible for the uptake of the nutrients that constrain plant growth in these infertile ecosystems. Despite performing a crucial role connecting primary producers to the soil, roots are relatively understudied in the Arctic and their functional response to a rapidly warming and increasingly variable climate is unknown. We assessed whether one growing season with elevated temperatures would have an impact on nutrient uptake and allocation by applying a warming technique that increased daily air temperatures by 3.2 °C. Destructive sampling was performed at the peak of the growing season to quantify biomass pools of carbon (C) and nitrogen (N), root traits, and uptake of a 15N tracer (15NH4+) for the dominant plant species, Arctagrostis latifolia. We found that soil nutrient availability increased with short-term warming, but A. latifolia NH4+ uptake remained unchanged. Fine-root...

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Thu, 22 Jan 2026 00:00:00 +0000

Abstract Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe‐ and mineral‐surface‐explicit model, the Reaction‐network‐based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM‐ReSOM and show a case study at a conifer forest in California. ELM‐ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM‐ReSOM sensitivity to microbial traits, enzyme properties, and organo‐mineral interactions. Microbial traits such as the maximum mortality rate, transporter‐density scaling factor, and maximum monomer...

Earlier snowmelt increases the strength of the carbon sink in montane meadows unequally across the growing season

Wed, 21 Jan 2026 00:00:00 +0000

Abstract Warming temperatures are changing winters, leading to earlier snowmelt. This shift can lead to an earlier and potentially longer growing season, which in turn may affect various plant‐mediated ecosystem functions. Despite its relevance in the carbon cycle, we still know little about how earlier snowmelt impacts the carbon balance in ecosystems over the growing season, for example, does it only shift phenology, or does it affect the overall carbon uptake? Most studies rely on interannual variability in snowmelt timing, making it difficult to isolate snowmelt effects from other confounding variables, for example, temperature and moisture anomalies. To address this uncertainty, we investigated how experimentally advancing snowmelt affects the carbon cycling of montane meadows across the growing season. We experimentally advanced the snowmelt date in a montane meadow by approximately 12 days and collected data every 2 weeks throughout the growing season, including net...

Hydrology controls thermokarst and alters carbon cycling and methane emissions in peatlands near the southern limit of permafrost

Wed, 21 Jan 2026 00:00:00 +0000

Permafrost peatlands store vast amounts of frozen carbon across northern landscapes. When ground ice melts, surface subsidence produces thermokarst landforms that expand wetlands at the edges of permafrost plateaus. Thermokarst represents an accelerating climate feedback, but uncertainties remain about how ground ice, hydrology, and vegetation interact to shape landscape change and carbon fluxes. We extended the process-based model ecosys to simulate thermokarst dynamics in laterally coupled 2D transects at a well-characterized boreal peatland site in Canada’s Northwest Territories. After benchmarking against site observations, we varied ground ice content and hydrologic boundary conditions across ranges typical near the southern permafrost limit. Simulations revealed distinct degradation regimes governed by the elevation difference between the frost table and the external water table. Rates of lateral retreat, the thaw-driven encroachment of wetlands into adjacent plateaus, ranged...

Crop diversification improves water-use efficiency and regional water sustainability

Wed, 21 Jan 2026 00:00:00 +0000

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s...

High-resolution national mapping of natural gas composition substantially updates methane leakage impacts

Wed, 14 Jan 2026 00:00:00 +0000

Methane is emitted from oil and gas operations alongside heavier hydrocarbons and non-hydrocarbon gases, shaping emissions management decision-making, including air quality impacts. Yet, most assessments assume fixed gas composition, overlooking significant spatial and temporal variations. Here, we generate a high-resolution, data-driven map of natural gas composition across the United States, reconstructing methane, heavier hydrocarbons, and non-hydrocarbon species using spatio-temporal interpolation and oil-and-gas production patterns. Our approach is able to reduce composition prediction errors by 39% in terms of Mean Absolute Error (MAE) compared to standard techniques and reveals that methane loss rates have been underestimated by more than 50% in some regions. Beyond methane, we uncover substantial variability in co-emitted gases, exposing blind spots in current emissions inventories and emissions management frameworks. Our work enables more accurate emissions assessments,...

Nutrient limitation shapes functional traits of mycorrhizal fungi and phosphorus-cycling bacteria across an elevation gradient

Wed, 14 Jan 2026 00:00:00 +0000

In nutrient-limited high-elevation ecosystems, plants rely on arbuscular mycorrhizal (AM) fungi to provide mineral phosphorus (P) in the form of phosphate (PO₄^3-). AM fungi gather these nutrients from phosphorus-cycling bacteria (PCBs) that can mineralize PO₄^3- from organic matter and solubilize mineral-bound P. How climate, soil factors, and nutrient limitation influence AM fungi and PCB assembly remains unclear. We collected soil from montane meadows across a 1,000-m elevation gradient on three replicate mountainsides and analyzed AM fungal marker genes, P-cycling genes from shotgun metagenomes, and edaphic measurements. High-elevation soils had nearly 50-fold less soil PO₄³⁻ and 60% more AM fungal hyphae than low-elevation soils. AM fungal turnover was linked to changes in pH, organic carbon, and PO₄³^-. The composition of 198 P-cycling genes was influenced by the AM fungal community structure. Drivers of individual PCB...

Observations and modeling reveal that heatwaves reduce photosynthesis, plant carbon reserves, and net carbon uptake

Wed, 14 Jan 2026 00:00:00 +0000

Heatwaves threaten ecosystem carbon balances, yet the mechanisms driving short-term carbon flux responses remain poorly understood. Here, integrating high-frequency eddy covariance (EC) data from 140 global flux tower sites (872 site-years) with detailed process-based modeling, we examine ecosystem responses during and immediately after heatwaves. We show that heatwaves caused a −40% (range [−29%, −128%]) reduction in net ecosystem productivity (NEP) compared to pre-heatwave values, with this reduction persisting over the following two weeks (−38% range [+3%, −154%]). We attributed NEP decreases to photosynthesis decreases more than to ecosystem respiration (RE) increases. Forest sites had greater NEP decreases during heatwaves than non-forest sites, but remained carbon sinks afterwards, indicating resilience. Our modeling analysis of extreme heatwaves at selected EC sites shows that decreased photosynthesis, increased maintenance respiration, and decreased plant non-structural...

Using Machine Learning to Discover Parsimonious and Physically‐Interpretable Representations of Catchment‐Scale Rainfall‐Runoff Dynamics

Tue, 13 Jan 2026 00:00:00 +0000

Abstract Due largely to challenges associated with physical interpretability of machine learning (ML) methods, and because model interpretability is key to credibility in management applications, many scientists and practitioners are hesitant to discard traditional physical‐conceptual modeling approaches despite their poorer predictive performance. Here, we examine how to develop parsimonious minimally‐optimal representations that can facilitate better insight regarding system functioning. The term “minimally‐optimal” indicates that the desired outcome can be achieved with the smallest possible effort and resources, while “parsimony” is widely held to support understanding. Accordingly, we suggest that ML‐based modeling should use computational units that are inherently physically‐interpretable, and explore how generic network architectures comprised of Mass‐Conserving‐Perceptron can be used to model dynamical systems in a physically‐interpretable manner. In the context of spatially‐lumped...

Tropical intertidal microbiome response to the 2024 Marine Honour oil spill

Tue, 13 Jan 2026 00:00:00 +0000

Marine fuel oil (MFO) spills in tropical coastal environments are under-characterized despite increasing risk from maritime activities. Microbial and geochemical responses to the June 2024 Marine Honour MFO spill on Singapore's intertidal sediments were analyzed in real time over 185 days. Using metagenomics and hydrocarbon profiling, microbial community shifts and hydrocarbon degradation were quantified across visibly oiled (high-impact) and clean (low-impact) sites. Microbiomes at all sites adapted rapidly to the spill through increased diversity and abundance of genes encoding alkane and aromatic compound degradation, detoxification, and biosurfactant production. The dominant hydrocarbon-degrading bacteria differed markedly from those reported in other crude oil spills and in regions with different climates. Oil deposition intensity strongly influenced microbial succession and hydrocarbon-degrading gene profiles, and this reflected early toxicity constraints in heavily oiled...

A worldwide climatology of extreme air masses

Mon, 12 Jan 2026 00:00:00 +0000

Extreme temperature events are among the most damaging weather phenomena. In a warming world, more heat extremes and fewer cold extremes are expected in most regions in the future, a trade-off that warrants further understanding of such events. Here, we track and analyze large, persistent areas of hot and cold extreme temperatures in parallel, relative to the location and time of year, to quantify overall regional exposure to extreme temperatures. To accomplish this, we compare the frequencies, movements, trends, and sources/sinks in each type of extreme air mass, calling them extreme cold or extreme hot air masses (ECAMs/EHAMs). For most land regions, ECAMs occur more often than EHAMs, and ECAMs are more common in each hemisphere’s winter, when cold-air advection is strongest and most widespread. Average movement of ECAMs has a stronger equatorward component in winter than in summer, while movement of EHAMs is eastward all year, with less meridional movement than ECAMs. EHAMs...

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Mon, 12 Jan 2026 00:00:00 +0000

Abstract Emissions‐driven (prognostic CO 2 ) simulations are essential for representing two‐way carbon‐climate feedback in Earth System Models. We present an emissions‐driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land‐atmosphere emission‐hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions‐driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land‐atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40‐ppm...

Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins

Fri, 9 Jan 2026 00:00:00 +0000

We quantify weekly methane emissions and trends from oil and gas production in the US Permian Basin for 2019-2023, and in nearby basins for 2022-2023, by analytical inversion of Tropospheric Monitoring Instrument (TROPOMI) satellite observations with the Integrated Methane Inversion (IMI) at 25 km resolution. Permian oil and gas emissions averaged 4.0 ± 1.1 Tg a^-1 over 2019-2023, with large seasonal variation but little interannual variability. Methane intensity fell from 5.2 to 3.2% as production surged. Intensity in the New Mexico Permian fell from 4.5 to 2.1%, approaching the state's 2026 target of <2%. Emissions were on average 50 ± 10% higher in winter than summer, which we corroborate with Permian Basin Tower Network measurements, Insight M aircraft data, and GHGSat satellite observations. This seasonality may be driven in part by higher winter emissions from liquid storage tanks due to decreased separator efficiency in cold conditions. Similar but weaker seasonality...

Multidecadal Fluctuations in the Observed ENSO‐Tropical Cyclone Teleconnection

Tue, 23 Dec 2025 00:00:00 +0000

Abstract El Niño‐Southern Oscillation (ENSO) is a skillful predictor for seasonal tropical cyclone (TC) activity in most TC basins. This study examines recent changes in the observed ENSO‐TC teleconnection strength, as measured by ENSO modulation of hurricane frequency. We find that the ENSO‐North Atlantic TC teleconnection fluctuated over time, with the strongest relationship occurring from the 1980s to the mid‐2000s. In the western and eastern North Pacific, the ENSO‐TC teleconnection has strengthened in recent decades. Periods with a strong ENSO‐TC teleconnection are associated with more favorable environmental conditions for TCs, with higher values of genesis potential indices. Positive phases of the Atlantic Multidecadal Oscillation coincided with periods of strong ENSO‐TC teleconnections in the Atlantic and North Pacific basins. A weaker Atlantic ENSO‐TC relationship was associated with negative phases of the Pacific Decadal Oscillation and the North Atlantic Oscillation....

A Climatology and Life‐Cycle Characteristics of Atmospheric Fronts and Their Associated Precipitation

Tue, 23 Dec 2025 00:00:00 +0000

Abstract Atmospheric fronts are one of the main sources of mid‐latitude variability. We employ a novel method for identifying and tracking fronts and frontal precipitation. Thermal and dynamical variables are used to identify fronts as areal objects in space, which are tracked in time using the open‐source TempestExtremes software package. Precipitation objects are co‐located to identify frontal precipitation. The method is subjected to validation and sensitivity tests using manually curated data from the National Weather Service. Climatologies of fronts and frontal precipitation are computed from reanalysis and observations; fronts are present upwards of 14% of the time in the storm tracks, and represent the majority (up to 90%) of total and extreme precipitation. Novel aspects of the method are showcased through the lifetime characteristics of fronts across North America. Three sets of warm and cold fronts were discovered, and their duration, distance‐traveled, and translation...

Evaluating Mean State Cloud Properties in the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM)

Fri, 19 Dec 2025 00:00:00 +0000

Abstract Accurately simulating clouds remains a key challenge in global climate models, primarily because cloud formation involves sub‐grid processes that are parameterized and crudely represented in models. This study examines the performance of DOE's Simple Cloud‐Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) in simulating cloud properties and their spatio‐temporal distribution by comparing against satellite observations. Two horizontal resolutions of SCREAM (3 and 12 km) are examined, and both depict a realistic spatial structure of mean‐state cloud cover but underestimate its global mean magnitude. SCREAM 3 km reasonably reproduces the distribution of mean‐state cloud properties across various cloud optical thickness and cloud‐top pressure regimes, with performance comparable to CMIP5 and CMIP6 ensemble and marginally outperforming SCREAM 12 km. Still, SCREAM 3 km tends to underpredict low clouds and optically thin clouds, highlighting...

Atmospheric Feedbacks Reverse the Sensitivity of Modeled Photosynthesis to Stomatal Function

Wed, 17 Dec 2025 00:00:00 +0000

Abstract Stomata mediate fluxes of carbon and water between terrestrial plants and the atmosphere. These fluxes are governed by stomatal function and can be modulated in many Earth system models by an empirical parameter within the calculation of stomatal conductance, the stomatal slope . Intuitively, represents the marginal water cost of carbon, relating it to the emergent plant property of water use efficiency. Observations show that can range widely across and within plant types in varying environments, and this distribution of is not captured within Earth system models which represent each plant type with a single value. Here we examine how influences photosynthesis using coupled Earth system model simulations by perturbing to observed and percentiles for each plant type. We find that high reduces photosynthesis nearly everywhere, while low has regionally dependent responses. Under fixed atmospheric conditions, low increases photosynthesis in the Amazon and central North America...

High Performance, High Fidelity: A GPU‐Accelerated Doubly‐Periodic Configuration of the Simple Cloud‐Resolving E3SM Atmosphere Model Version 1 (DP‐SCREAMv1)

Wed, 17 Dec 2025 00:00:00 +0000

Abstract The development of the Simplified Cloud Resolving Energy Exascale Earth System Atmosphere Model (SCREAMv1) enables global storm‐resolving simulations on modern GPU‐based supercomputers. However, the high computational cost of SCREAMv1 limits its routine use for process‐level studies, creating a need for efficient proxy configurations. This study addresses this gap by introducing DP‐SCREAMv1, a doubly periodic cloud‐resolving model designed to be fully consistent with SCREAMv1 while enabling high‐resolution, long‐duration simulations at significantly reduced computational expense by simulating a limited doubly periodic domain rather than the entire globe. Built on a C++/Kokkos architecture, DP‐SCREAMv1 achieves exceptional performance scalability on GPU systems and includes a rich library of cases for validation and scientific exploration. In this work, we demonstrate short wall‐clock times at SCREAMv1's default resolution and show that DP‐SCREAMv1 supports routine execution...

Soil oxygen dynamics: a key mediator of tile drainage impacts on coupled hydrological, biogeochemical, and crop systems

Wed, 17 Dec 2025 00:00:00 +0000

Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the US Midwest and throughout the world. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although examining the complex interactions and feedbacks in an integrated hydrology–biogeochemistry–crop system remains elusive. Oxygen dynamics are critical to unraveling these interactions and have been ignored or oversimplified in existing models. Understanding these impacts is essential, particularly so because tile drainage has been highlighted as an adaptation under projected wetter springs and drier summers in the changing climate in the US Midwest. We used the ecosys model that uniquely incorporates first-principle soil oxygen dynamics and crop oxygen uptake mechanisms to quantify the impacts of tile drainage on hydrological and biogeochemical...

Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California

Tue, 16 Dec 2025 00:00:00 +0000

ABSTRACT Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using...

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Fri, 12 Dec 2025 00:00:00 +0000

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale...

The Remarkable 2024 North Atlantic Mid‐Season Hurricane Lull

Wed, 10 Dec 2025 00:00:00 +0000

Abstract The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto's dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid‐to‐late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer tropical cyclone seed disturbances that also traversed unfavorably cool ocean water. During early‐to‐mid September, subseasonal variability driven by the Madden‐Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic....

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Thu, 4 Dec 2025 00:00:00 +0000

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm^-2 yr^-1 for boreal, temperate and tropical sites, respectively),...

Brief communication: Decadal changes in topography, surface water and subsurface structure across an Arctic coastal tundra site

Mon, 1 Dec 2025 00:00:00 +0000

In ice-rich polygonal tundra, spatiotemporal heterogeneity in ground-ice melt reshapes topography, impacting infrastructure, water and carbon cycles. This study evaluates changes in topography and subsurface structure at a coastal Arctic site by comparing data from two surveys conducted a decade apart. Each survey includes electrical resistivity tomography, active layer thickness, photogrammetry, and topographic data. Results reveal subsidence and decrease in permafrost table elevation with varying intensity and spatial distribution across polygons, alongside diverse thermal-hydrological responses, such as thermokarst pool formation in high-centered-polygons and more even subsidence in flat-centered-polygons. The study also underscores the value and limitations of sporadic surveys.

Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands

Fri, 21 Nov 2025 00:00:00 +0000

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of...

Improving the Integration of Diversity, Equity, Inclusion, and Justice Goals in Total Maximum Daily Load Model Implementation for Water Quality Management

Fri, 21 Nov 2025 00:00:00 +0000

Water quality modeling is used globally to assess surface water impairment and manage watershed pollution in formal programs like the United States' (US) total maximum daily load and in less structured initiatives elsewhere. Despite these programs, progress toward realizing equitable water quality benefits to society is stymied through an inability to recognize, plan, and incorporate diversity, equity, inclusion, and justice (DEIJ) principles in the modeling efforts. In this paper, we describe the major barriers and limitations to the inclusion of DEIJ principles in the design and implementation of pollution load reduction programs in the US. We offer a blueprint to embrace participatory modeling approaches to engage more openly, honestly, and fairly with relevant participants (stakeholders) to achieve just and equitable water quality outcomes and upgrade water quality management principles nationwide. We provide case studies where the DEIJ principles have been applied and synthesized,...

A minor respiratory process with major global implications: is atmospheric methane oxidation in tree stems driven by stem respiration rather than microbial methanotrophy?

Thu, 20 Nov 2025 00:00:00 +0000

Tree stem surfaces are widely recognized as sites of carbon dioxide (CO₂) efflux and oxygen (O₂) influx, reflecting the dynamics of aerobic respiration of photosynthate substrates, such as sugars, delivered via the phloem. Stems are also largely considered passive conduits for methane (CH₄) produced in anoxic soils via microbial methanogenesis, where CH₄ is thought to be transported upward through the transpiration stream and/or diffusion and emitted through stem surfaces and the canopy. However, recent observations from dynamic stem chambers suggest that stems may also act as active sinks for atmospheric CH₄. Despite these findings, the extent and drivers of stem CH₄ consumption remain poorly characterized across biomes, species, and environmental gradients, and its quantitative relationship to stem respiration has not been established. Moreover, previous studies captured only snapshot fluxes, leaving diurnal patterns of CH₄ exchange uncharacterized. Here, we address these limitations...

The Role of Wind‐Moisture Characteristics in Shaping Atmospheric River Flood Hazards

Tue, 18 Nov 2025 00:00:00 +0000

Abstract Atmospheric rivers (ARs) are key drivers of extreme precipitation in the Western U.S. Using regionally downscaled thermodynamic global warming (TGW) simulations, we examine how ARs with varying wind and moisture characteristics respond to warming. We classified 812 historical AR events into Gusty‐Wet, Gusty‐Dry, Calm‐Wet, and Calm‐Dry groups to evaluate differences in precipitation behavior. ARs with stronger winds and higher moisture content exhibit higher precipitation efficiency (PE) and greater integrated water vapor (IWV). Regionally, Calm ARs show higher IWV accumulation due to slower inland transport and reduced PE. Projections indicate increases in storm‐total (sub‐Clausius‐Clapeyron (CC) scaling) and maximum 3‐hourly precipitation (super‐CC scaling) across all groups, with the most pronounced changes in Gusty‐Wet and Calm‐Wet ARs. Spatial differences in surface runoff, PE, and inland reach highlight the importance of AR subtype in shaping future flood hazards....

Huge ensembles – Part 2: Properties of a huge ensemble of hindcasts generated with spherical Fourier neural operators

Mon, 17 Nov 2025 00:00:00 +0000

In Part 1, we created an ensemble based on spherical Fourier neural operators. As initial condition perturbations, we used bred vectors, and as model perturbations, we used multiple checkpoints trained independently from scratch. Based on diagnostics that assess the ensemble's physical fidelity, our ensemble has comparable performance to operational weather forecasting systems. However, it requires orders-of-magnitude fewer computational resources. Here in Part 2, we generate a huge ensemble (HENS), with 7424 members initialized each day of summer 2023. We enumerate the technical requirements for running huge ensembles at this scale. HENS precisely samples the tails of the forecast distribution and presents a detailed sampling of internal variability. HENS has two primary applications: (1) as a large dataset with which to study the statistics and drivers of extreme weather and (2) as a weather forecasting system. For extreme climate statistics, HENS samples events...

Huge ensembles – Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators

Mon, 17 Nov 2025 00:00:00 +0000

Simulating low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems presently use up to 100 members, larger ensembles could enrich the sampling of internal variability. They may capture the long tails associated with climate hazards better than traditional ensemble sizes. Due to computational constraints, it is infeasible to generate huge ensembles (comprised of 1000–10 000 members) with traditional, physics-based numerical models. In this two-part paper, we replace traditional numerical simulations with machine learning (ML) to generate hindcasts of huge ensembles. In Part 1, we construct an ensemble weather forecasting system based on spherical Fourier neural operators (SFNOs), and we discuss important design decisions for constructing such an ensemble. The ensemble represents model uncertainty through perturbed-parameter techniques, and it represents initial...