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USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗

USGS2024

Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA

Extensional faults are key components of foreland basin systems. They form within the upper crust in response to flexure of the lithosphere and accommodate subsidence within the foredeep and forebulge depozones. Such faults are excellent proxies for orogenic system evolution and control the distribution of natural resources and hazards. However, the spatiotemporal evolution of flexural extension has not been documented previously at a regional scale, thereby limiting our understanding of underlying geodynamic controls. Here, we resolve late Paleozoic flexural extension in the northern Arkoma basin and southern Ozark dome, USA. We synthesize a large database of previous mapping, existing research, subsurface data, and geophysical data into 3D geologic and 2D kinematic models. Mesh surfaces representing several key horizons from the Carboniferous Period (ca. 335-306 Ma) were constructed. These surfaces were built from oil and gas well tops (n = ∼10,000) and surface geologic map contacts using an advanced kriging method. The mesh surfaces are offset by a complex 3D fault network, allowing detailed analysis of along-strike and down-dip variations in fault displacement. Analysis of the 3D model reveals a regular and repeated fault segmentation pattern wherein E -W striking, left- and foreland-stepping en échelon normal faults are segmented by inherited NE striking basement faults. Maximum vertical separation along the E -W normal faults is generally focused between the inherited NE-trending faults. This suggests that the inherited basement faults delocalized extensional strain during late Paleozoic normal faulting. Maximum vertical separation and fault localization may correlate to areas with high-amplitude positive magnetic anomalies interpreted as Mesoproterozoic granitic rocks. Speculative covariance of magnetic anomalies and fault displacements implies that the relatively strong basement granite concentrated stress, leading to localized faulting within the relatively thin sedimentary cover. Lastly, we show that flexural extension migrated southeast to northwest from the Chesterian-Morrowan (ca. 335-319 Ma) to the Desmoinesian (ca. 306 Ma). The migratory flexural extension may be explained by diachronous loading during Pangean assembly, or by synchronous loading but variable load compensation due to inherent factors.

Arkansas, Oklahoma↗

USGS2024

Isotopic evaluation of the National Water Model reveals missing agricultural irrigation contributions to streamflow across the western United States

The National Water Model (NWM) provides critical analyses and projections of streamflow that support water management decisions. However, the NWM performs poorly in lower-elevation rivers of the western United States (US). The accuracy of the NWM depends on the fidelity of the model inputs and the representation and calibration of model processes and water sources. To evaluate the NWM performance in the western US, we compared observations of river water isotope ratios ( 18 O / "> 16 O and 2 H / "> 1 H expressed in δ notation) to NWM-flux-estimated (model) river reach isotope ratios. The modeled estimates were calculated from long-term (2000–2019) mean summer (June, July, and August) NWM hydrologic fluxes and gridded isotope ratios using a mass balance approach. The observational dataset comprised 4503 in-stream water isotope observations in 877 reaches across 5 basins. A simple regression between observed and modeled isotope ratios explained 57.9 % ( δ 18 O) and 67.1 % ( δ 2 H) of variance, although observations were 0.5 ‰ ( δ 18 O) and 4.8 ‰ ( δ 2 H) higher, on average, than mass balance estimates. The unexplained variance suggest that the NWM does not include all relevant water fluxes to rivers. To infer possible missing water fluxes, we evaluated patterns in observation–model differences using δ 18 O diff ( δ 18 O obs − δ 18 O mod ) and d diff ( δ 2 H diff - 8 ⋅ δ 18 O diff "> ). We detected evidence of evaporation in observations but not model estimates (negative d diff and positive δ 18 O diff ) at lower-elevation, higher-stream-order, arid sites. The catchment actual-evaporation-to-precipitation ratio, the fraction of streamflow estimated to be derived from agricultural irrigation, and whether a site was reservoir-affected were all significant predictors of d diff in a linear mixed-effects model, with up to 15.2 % of variance explained by fixed effects. This finding is supported by seasonal patterns, groundwater levels, and isotope ratios, and it suggests the importance of including irrigation return flows to rivers, especially in lower-elevation, higher-stream-order, arid rivers of the western US.

Hydrology and Earth Systems Science↗

USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗

USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗

USGS2026

Guidelines for producing integrated 210Pb and 14C age-models

Accurate reconstructions of past environmental changes are crucial in paleoecological research and require reliable chronologies of sedimentary archives. Establishing robust age-models and obtaining the most appropriate proxies for analysis is a complex scientific endeavor, requiring extensive resources and collaboration among specialists, including radiochronologists. Radiometric dating methods, such as 210 Pb and radiocarbon ( 14 C), are frequently employed to establish chronologies in aquatic sedimentary deposits and peat bogs. In this study, we review key aspects of sampling, analysis, and the principles underlying 210 Pb and 14 C age-models, focusing on methods for developing robust joint chronologies for paleoenvironmental research. Drawing largely from the authors' experiences and group discussions during and after a scientific workshop in 2022, we discuss important considerations for site selection, sampling strategies, and radiometric dating to construct integrated 210 Pb and 14 C age-models. Using expert consensus, this group – called Paleostats – aims to provide a set of best practices for other geochronologists with this methods paper. Among our conclusions, we emphasize the importance of accounting for site-specific factors such as prior information on sedimentation rates to establish appropriate sampling and analytical strategies. The use of appropriate coring devices can minimize disturbance to sediments and ensure the core surface remains intact and preserved until sectioning. Where excess 210 Pb is expected, sectioning at intervals of ≤1 cm provides an adequate sampling resolution for 210 Pb dating. Exceptions are possible, allowing for ~2–3 cm sections in areas with confirmed high sedimentation rates (e.g., > 1 cm yr −1 ). Recovering deeper core sections for 14 C dating with sufficient overlap allows for accounting errors in depth estimates made in the field. Special attention is advised during time intervals where validation proxies, such as the human-made radionuclides 137 Cs or post-bomb 14 C, are expected, and to determine the depth of secular equilibrium between 210 Pb and 226 Ra. Radiocarbon analyses are commonly performed by accelerator mass spectrometry, and age models are constructed mainly using Bayesian statistics with Markov Chain Monte Carlo techniques (e.g., Bacon ). A Bayesian approach ( Plum ) is now available for producing 210 Pb age-models, which infers the 210 Pb ex flux, eliminates the need for selecting an equilibrium depth, and allows dating cores with incomplete 210 Pb ex inventory. Plum offers improved chronologies by integrating raw 210 Pb and 14 C data, and these age-models can be enriched with other dating methodologies, such as identifying tephras and other well-recorded historical events. Harmonized reporting would contribute to making radiometric age-models reproducible, which would benefit from an international effort. Using 210 Pb and 14 C to produce integrated age-models may yield better insights into the interplay between natural and recent anthropogenic forcings on ecosystems. This can enhance our understanding of environmental processes and their impacts on climate change, ultimately supporting science-based assessments and decisions.

Earth-Science Reviews↗

USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗

USGS2025

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗

USGS2025

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗

USGS2025

Refining the earthquake history of south-central Alaska through lake records

The Alaska–Aleutian subduction zone (AASZ) is one of the world's most seismically active plate boundaries and the source of the 1964 M w 9.2 Great Alaska earthquake–the second largest instrumentally recorded earthquake in the world. Understanding the nature and frequency of such earthquakes is necessary for seismic and tsunami hazard assessment, but instrumental and historical records that span less than 150 years are too short to allow a statistically reliable analysis of earthquake recurrence times. This calls for studies of evidence of past earthquakes, extending the earthquake catalog further back in time. Subduction-zone paleoseismology in south-central Alaska is predominantly based on coastal evidence of land-level changes and tsunamis generated by megathrust earthquakes and preserved in the geological record. A complementary approach is lacustrine paleoseismology, which is still a relatively young discipline in Alaska. However, globally, lake basins are well-established high-resolution and continuous recorders of paleoseismic activity along subduction zones, relying on the identification of underwater landslide deposits and turbidites generated by seismic shaking. As a result, lake basins not only register ground shaking from megathrust earthquakes, but also from intraslab and crustal earthquakes, which are typically not accompanied by significant land-level changes. In this review paper, we combine coastal and lacustrine paleoseismology approaches to refine the south-central Alaskan earthquake history by comparing the paleoseismic records from two lakes (i.e., Eklutna Lake, located in the Chugach Mountain Range, and Skilak Lake, situated on the Kenai Peninsula) with the coastal and crustal earthquake catalog in Alaska. The resulting age ranges of all known megathrust earthquakes involving the Alaskan megathrust between the Kodiak and Prince William Sound (PWS) sections are more precise and accurate for the last 1.3 kyrs BP than the previously published age ranges from coastal records. As a result, this study supports the following key conclusions: (1) The 1964 CE earthquake was an exceptionally strong and unique event in the last 2000 years, rupturing the PWS, Kenai, Barren Islands, and Kodiak sections simultaneously. (2) The high-resolution and seasonal markings of the varved lake records now disentangle for the first time closely timed earthquakes, which was not possible based on the coastal evidence alone. (3) No persistent megathrust rupture boundaries exist. So, the possibility of a full rupture of the entire eastern AASZ, from PWS to Semidi cannot be excluded. (4) The rupture pattern in the eastern AASZ reveals superimposed cycles of multi-asperity ruptures (1964 earthquake) and clustered complementary partial ruptures, or rupture cascades. (5) The PWS section hosts the largest asperity in the eastern AASZ. (6) The shaking record of megathrust earthquakes indicates a time-dependent (quasiperiodic) behavior for the study area, but the observation of complementary clusters means that the hazards will not drop to zero but instead may even increase for a neighboring section. (7) The time-independent behavior of intraplate earthquakes implies that the intraslab hazard did not decrease following the 2016 and 2018 earthquakes. This study utilizes an integrated approach for subduction zone paleoseismology as a solution for unraveling recurrence and rupture patterns in Alaska, which can be applied worldwide.

Alaska↗

USGS2025

Foundational uncertainties in terminal Ediacaran chronostratigraphy revealed by high-precision zircon U-Pb geochronology of the Nama Group, Namibia

The Nama Group of southern Namibia and northwestern South Africa hosts the best-dated mixed carbonate-siliciclastic foreland basin succession of the terminal Ediacaran [ca. 551 million years (Ma) ago to <538 Ma] and is key for resolving the chronology of early metazoan evolution. Numerous silicified volcanic tuff interbeds are present, but differing interpretations regarding the fidelity of their ages lead to different regional stratigraphic correlations, especially for the Urusis Formation of the Schwarzrand Subgroup. An expanded record of the Urusis Formation is found in the Swartpunt area of southern Namibia, which has yielded an important metazoan biota. But the succession in this area is preserved as a series of thrusts at the leading edge of the Gariep orogenic belt and zircon U-Pb data show systematic age repetition. We use regional stratigraphic and structural mapping, integrated with carbonate carbon isotope (δ 13 C carb ) chemostratigraphy and high-precision radioisotope U-Pb zircon geochronology from outcrop and recently acquired drill core to develop a temporally calibrated basin-wide depositional model. This integrated dataset either reflects complex zircon reworking, inheritance, or potential analytical biases (Scenario 1) or the presence of a Gariep-related cryptic décollement within the Spitskop Member that has resulted in stratigraphic repetition (Scenario 2). We investigate the evidence for and against both scenarios and consider their implications for stratigraphic and δ 13 C carb correlations between the Swartpunt area and coeval exposures along the Orange River border with South Africa. Given that these issues are in an area that hosts numerous silicified ash beds and extensive exposure, an inability to confidently discount either scenario highlights a level of compounding uncertainty in zircon U-Pb geochronology that must be considered when attempting to build global chronostratigraphic frameworks. Scenario 1 implies that some of the weighted mean ages and Bayesian eruption ages from the Swartpunt area may be >1 Myr older than the depositional age of their respective ash beds when assuming existing stratigraphic correlations. If this scenario is preferred, then a cautious approach would be to consider all weighted mean zircon U-Pb ages from ash beds to reflect maximum depositional ages. Both scenarios support deposition of the Huns Member >540 Ma in the Swartpunt area if the oldest weighted mean age reported here represents a near-depositional age, which has significant implications for the temporal calibration of important terminal Ediacaran ichnofossil assemblages and future cyclostratigraphic studies. Stratigraphic correlations common to both scenarios allow us to temporally calibrate a basin evolution model for the Nama Group. Temporal trends in initial hafnium isotope (εHf) compositions of zircon grains from ash beds throughout the succession may support progressive crustal thickening associated with underplating of the Damara orogenic belt along the northern periphery of the Kalahari craton from ca. 547 Ma to ca. 538 Ma. The compilation of new and published zircon U-Pb ages may also imply that the locus of carbonate platform development migrated from north to south (present co-ordinates), tracking the migration of foredeep subsidence.

Earth-Science Reviews↗

USGS2025

VIPER site analysis

We needed to evaluate available orbital data of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission area in order to derive a variety of maps to help the science team identify scientifically interesting places for the rover to visit and to provide scientific context for our mission. Some of these maps also fulfilled engineering and mission design needs to enable safe and efficient landing and roving. We incorporated data from the Lunar Reconnaissance Orbiter Camera, the Lunar Orbital Laser Altimeter, the Mini-RF instrument, the Chandrayaan-2 Orbital High Resolution Camera, the Korean Pathfinder Lunar Orbiter’s Shadowcam, the Kaguya Spectral Profiler and Multiband Imager, and the Chandrayaan-1 Moon Mineralogy Mapper. We used a variety of techniques to build these maps, including stereogrammetry, shape-from-shading, ice stability depth and surface temperature calculations, and the horizon method for solar illumination and direct-to-Earth communications maps. Altogether, these maps allowed us to survey for boulders, evaluate features in permanently shadowed regions that VIPER might explore, provide mineralogic context for what VIPER’s instruments may learn, estimate the ages and radar properties of craters in the VIPER mission area, and evaluate the potential for gravity traverses with the rover. These data and techniques provided a rich set of information from which both the VIPER science team and engineering teams were able to draw in order to plan a safe landing and to plan a VIPER surface mission that will be both scientifically valuable and robust from an operational perspective.

The Planetary Science Journal↗

USGS2026

Ten new insights in climate science 2025

Interdisciplinary understanding is vital for delivering sound climate policy advice. However, navigating the ever-growing and increasingly diverse scholarly literature on climate change is challenging for any individual researcher. This annual synthesis highlights and explains recent advances across a variety of fields of climate change research. This year, the 10 insights focus on: (1) the record-warmth of 2023/2024 and the elevated Earth energy imbalance; (2) acceleration of ocean warming and intensifying marine heatwaves; (3) northern land carbon sinks under strain; (4) reinforcing feedback between biodiversity loss and climate change; (5) accelerated depletion of groundwater; (6) global dengue incidence; (7) global income losses and labour productivity declines; (8) strategic scaling of CDR; (9) integrity challenges in carbon credit markets and emerging responses; and (10) effective policy mixes for emissions reductions. The insights have been written to be accessible to researchers from different fields, serving as entry-points to specific topics, as well as providing an overview of the evolving landscape of climate change research. In the final section, the insights are used to develop overarching policy-relevant messages. This paper provides the basis for a science-policy report that was shared with all Party delegations ahead of COP30 in Belém, Brazil.

Global Sustainability↗

USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗

USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

General Information Product↗

USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗

USGS2024

Seismic tomography 2023

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

Bulletin of the Seismological Society of America↗

USGS2024

ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2024

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 1 (January–March), 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov . This quarterly report is the third to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data . Additional information about Landsat 9 prelaunch, commissioning, and early on-orbit imaging performance is available at https://www.mdpi.com/journal/remotesensing/special_issues/15B4V2K92K . This quarterly report is the first to not include analysis results for Landsat 7 because Enhanced Thematic Mapper Plus imaging was suspended on January 19, 2024, after the satellite transitioned into full sunlight. The satellite has been drifting since early 2022 after being lowered from the nominal orbit altitude, and the transition into full sunlight is a result of the satellite operating in its extended science mission. Additional information about the imaging suspension is available at https://www.usgs.gov/landsat-missions/news/landsat-7-imaging-suspended . Additional information about the Landsat 7 extended science mission is available at https://www.usgs.gov/landsat-missions/landsat-7-extended-science-mission .

Open-File Report↗