Abstract In the Abu Dhabi Emirate, near Madinat Zayed and Liwa, studies have identified high geothermal gradients and high‐heat‐flow areas. Assessing the geothermal potential in this region requires a detailed mapping of subsurface geological formations and their thermal properties. This study employed broadband magnetotelluric (BBMT) measurements to map the geological formations, focusing on the basement rock structures linked to the high‐heat‐flow anomaly observed in the area. The three‐dimensional inversion of BBMT data revealed a high‐resistivity anomaly at 10 km depth beneath a highly conductive Quaternary sediment layer in the high‐heat‐flow area. This high‐resistivity layer is interpreted as basement rocks. To interpret the MT model, gravity, magnetic, seismic, and heat flow data were used, and a two‐dimensional gravity‐magnetic model was constructed along the BBMT profile. The high‐heat‐flow anomaly in the study area is interpreted as due to the existence of highly magnetized basement rocks.
Abstract In situ observations of thermospheric composition have long been scarce, limiting our understanding of the upper atmosphere and its response to space weather. This study focuses on the Neutral Gas Mass Spectrometer (NGMS) onboard the TM19 and TM20 satellites of China's TianMu‐1 constellation, presenting the first systematic elaboration of its core technical characteristics and novel in situ observational results of O and N 2 number densities. During the 10–12 October 2024 geomagnetic storm, the ratio of O to N 2 number densities (O/N 2 ) decreased significantly at mid‐high latitudes, owing to the stronger enhancement of N 2 compared with O. N 2 perturbations were confined to latitudes above ∼±30° in both hemispheres, whereas O perturbations exhibited a global latitudinal distribution, likely reflecting that heavy N 2 is locally enhanced by upwelling and decays equatorward via diffusion, while O is transported globally by storm‐time circulation and waves. Additionally, the O/N 2 observations from TM19 and TM20 showed high cross‐satellite response consistency with a correlation coefficient of 0.89, while the MSIS 2.0 model systematically overestimated the O/N 2 under geomagnetically quiet conditions. The NGMS onboard TianMu‐1 provides crucial data support for optimizing atmospheric models.
Abstract We describe a Geometry‐dependent surface Lambertian‐Equivalent Reflectivity (GLER) climatology developed to support operational retrievals for the Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission. This data set provides monthly and hourly surface reflectance for snow‐free land, snow‐covered land, and oceanic regions. The set is constructed by integrating MODIS MCD43C1/C2 bidirectional reflectance distribution function (BRDF) parameters, snow cover information, and radiative transfer simulations. A Factor‐Analysis spectral reconstruction method, constrained by spectral priors from the USGS spectral library and the SCIAMACHY LER data set, was applied to extend discrete MODIS four‐band reflectance over land to a near‐continuous spectral range (335–900 nm), covering most of the spectral range of TEMPO. The ocean climatology GLER was simulated using a Cox–Munk surface slope distribution model coupled with the VLIDORT model. Preliminary comparisons with the TROPOMI directionally dependent LER (DLER) empirical data set demonstrate strong seasonal consistency at a local solar time of 13:30. Summer mean differences generally remain within ±0.01, while larger winter biases (up to 0.03) are primarily attributed to extreme solar geometries, sub‐pixel residual snow, and adjacency pixel effects. This GLER climatology currently serves as a crucial input for TEMPO Level 2 operational algorithms, supporting retrievals for nitrogen dioxide, formaldehyde, and ozone, as well as cloud parameter estimations.
Abstract Satellite data have been used to estimate the three‐dimensional orientation of features on Mars inferred to be bedding planes to support interpretations of deposit characteristics and depositional environments. Opportunities to ground‐truth these estimates and to understand the geologic information recorded by surfaces measured from orbit are limited to landing sites. We developed a generalized workflow for calculating surface orientations from measured apparent dip angles and look directions that may be applied to photographs. We then performed a quantitative comparison of five orbiter‐derived plane fits of scarps, light‐toned bands, and other layer‐like features exposed in outcrops in Jezero crater's western fan with both orientations and up‐close geologic interpretations of the same features using images taken by the Perseverance rover. Orbiter‐derived orientation estimates almost always fall within orientation constraints set by apparent dip angles and dip directions seen in two or more rover images. Additionally, the rover‐ and orbiter‐based orientation solutions often overlap within mutual uncertainties. However, only one of five features traced from orbit was confirmed in rover images to constitute an actual single bed, indicating that our ability to distinguish hierarchical stratigraphic elements, lithologies, and stratal structures from orbit is limited. Thus, in situ investigation at sub‐decimeter‐scale with landed spacecraft that can view strata in cross‐section will often be required to definitively distinguish stratigraphic elements that are characteristic of depositional environment. Nevertheless, certain outcrop characteristics such as distinct tonality and moderate‐to‐steep inclination are discernible from orbit and allow for the characterization of the orientation of beds or self‐similar packages of strata.
Abstract The planetary boundary layer (PBL) is the portion of the troposphere that is directly influenced by the presence of the Earth's surface. The thermodynamic structure of this layer exhibits a wide variety of characteristics across the globe. In 2018 the National Academies of Sciences, Engineering, and Medicine Space Studies Board recommended that U.S. agencies consider the advancement of technologies for the remote sensing of the PBL thermodynamic structure and height. This paper provides a quantitative assessment of the PBL thermodynamic structure across various climate regimes using the highest vertical resolution radiosonde measurements available from Department of Energy Atmospheric Radiation Measurement research sites and informs the requirements of a future PBL mission. To do this, this paper introduces a method to characterize the vertical scales of temperature and water vapor correlation. This method is used to analyze radiosonde, Atmospheric Emitted Radiance Interferometer (AERI), and Atmospheric Infrared Sounder (AIRS) data sets. The AIRS Level 2 Version 7 product is shown to achieve a vertical correlation length in temperature that is generally similar to high vertical resolution radiosonde data, but shows much larger water vapor correlation lengths (>1 km) than is reported by the radiosonde data (<500 m). Contrastingly, the ground‐based infrared TROPoe (AERI) retrieval is able to nearly recreate the vertical correlation patterns of the radiosondes in temperature below 4,000 m, and recreated the water vapor correlation lengths at two times that of the radiosonde data below 4,000 m. This is a well‐known qualitative result that is quantified by the use of this metric.
Abstract Diagnosing monthly evapotranspiration (ET) under water‐balance constraints is essential for understanding land‐atmosphere interactions and managing water resources under changing climate conditions. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow‐On (GRACE/‐FO) missions have provided precise observations of terrestrial water storage, enabling improved constraints on large‐scale water balance. Building on these advances, we develop a GRACE/‐FO‐constrained diagnostic to framework to reproduce monthly ET derived from water‐balance (ET Budget ). The framework that applies the one‐parameter Budyko formulation during dry (water‐limited) months and the two‐parameter power‐law formulation during wet (energy‐limited) months, with the aridity index distinguishing between them. The framework is evaluated across 297 major river basins using ET Budget as a reference and compared with conventional Budyko‐only approaches. Results show that, relative to the Budyko‐only approaches, the proposed framework substantially reduces deviations from ET Budget , especially in 189 humid basins, while maintaining robust performance in 15 arid and 93 semi‐arid regions. The proposed framework yields mean annual ET and P‐ET of 612.5 and 191.4 mm yr −1 over major river basins, respectively, showing no significant long‐term trends but distinct spatial patterns and contrasting responses to the El Niño‐Southern Oscillation phases. These findings highlight the value of the proposed framework as a diagnostic tool for improving the representation of monthly water‐balance ET across diverse hydroclimatic conditions.
Abstract Thermospheric mass density is one of the largest sources of operational uncertainty for spacecraft in low Earth orbit, particularly during geomagnetic storms. The growing population of Global Navigation Satellite System‐equipped satellites presents a data set of opportunity: precise orbit determination (POD) data streams can be used to estimate thermospheric density along their paths. We present a multi‐timescale benchmark of the two main cooperative density inversion methods, the Energy Dissipation Rate method and POD‐accelerometry, against accelerometer‐derived effective densities from the CHAMP and GRACE‐FO‐A satellites over 49 geomagnetic storms. At orbit‐effective cadence, both methods achieve r2≥0.97 and a log‐normal scatter SD%≤22%, and are statistically indistinguishable in typical‐orbit scatter. However, the Energy Dissipation Rate method tracks storm‐time variations more faithfully and produces fewer large‐error orbits (r2 0.992 vs. 0.985; RMS error 12.0% vs. 13.5%), at roughly 6× lower computational cost. Increasing the fit‐span to three orbits reduces SD% to 13%–14% for both methods against matched‐interval accelerometer effective densities, but r2 against unaveraged (10 s) accelerometer data drops sharply beyond about half an orbit. Optimizing the arc length below one full orbit offers an attractive compromise, achieving r2=0.93–0.94 and SD%≈42–46% against unaveraged accelerometer data. Retrieval accuracy depends strongly on drag‐acceleration magnitude, with RMS errors below 10% where drag exceeds 4×10−7ms−2 but growing above 30% below 10−8ms−2. These results provide empirical observation‐error statistics for storm‐time POD‐derived density retrievals, directly relevant to next‐generation assimilative models.
Abstract The Spectral Irradiance Monitor (SIM), on board the Solar Radiation and Climate Experiment (SORCE) test satellite operated for 17 years: from February 2003 to February 2020, measuring the Solar Spectral Irradiance from 200 to 2,400 nm. The unavoidable instrument degradation was tracked and corrected based on a measurement equation derived from accessible telemetry, the known instrument refraction geometry, inter‐detector comparisons, and inter‐spectrometer comparisons. While the previous degradation model captures much of the long‐term trending, some of the parameters were adjusted without well‐defined physical justifications. The development of enhanced SORCE/SIM measurement equations allowed the evaluation and inclusion of degradation mechanisms not captured in the original model. We present the multiple approaches tested to better understand the degradation mechanisms and the final model that was adopted with the underlying physical implications. An updated SORCE/SIM data product, L3 Enigma Version 1 (L3E V1), covering the lifetime of the mission, starting at 210.0 nm instead of 240.0 nm, and adjusted to the TSIS/SIM absolute irradiances, has been generated and made available to the community.
Abstract Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment‐transport networks. This study investigated landscape‐scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050‐km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long‐term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long‐term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed‐use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial‐reuse programs.
Abstract A set of fresh Equatorial Plasma Bubbles (EPBs) formed during pre‐sunrise hours in the Southeast Asian sector amid the recovery phase of May 2024 geomagnetic storm. They offered new insights into their formation mechanism. This study used Total Electron Content (TEC) and Rate of TEC Index maps over Indonesia, along with ionosondes in Thailand and Vietnam, magnetometers in South American sectors, and prompt penetration electric field (PPEF) modeling, to reveal these insights. The first insight from our observations was that the pre‐sunrise EPBs were initiated by the eastward overshielding PPEF linked to the northward turn of the Interplanetary Magnetic Field Bz. Then, the disturbance dynamo electric field, expected to operate during the storm's recovery phase, might maintain the survival of the EPBs. The second, and more intriguing, insight is that these pre‐sunrise EPBs formed at specific longitudes, where TEC values had already decreased since the post‐sunset hours. Further investigation showed that these lower TEC regions consist of large plasma density gradients, serving as favorable conditions necessary for EPB formation near sunrise. Finally, this study implied that, even during a strong eastward electric field in an intense storm, preconditioning or favorable conditions, such as larger plasma density gradients, are required for pre‐sunrise EPB generation. The storm‐driven electric field then causes the pre‐sunrise EPBs to develop at distinctive longitudes where these favorable conditions are located.
Abstract Gravity waves in the upper mesosphere produce diverse spatial patterns in nighttime airglow, but their global morphology has been difficult to characterize because manual identification is impractical for the massive satellite image archive. We developed a machine learning framework to detect and classify gravity wave events in imagery from the Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) on three satellites. A machine learning based object detector called YOLOv8 (You Only Look Once, version 8) was trained to identify four airglow morphological classes: concentric gravity waves, frontal waves, ripples, and other gravity wave events. On an independent test set, the model achieved a mean average precision of 0.832 at an intersection over union threshold of 0.3. At the confidence threshold adopted for catalog generation, the mean precision and recall were 0.828 and 0.778, respectively. The trained detector was applied to 12 years of moon‐free VIIRS DNB observations from Suomi National Polar‐orbiting Partnership, NOAA‐20, and NOAA‐21, resulting in an event catalog containing more than 100,000 detected wave event instances from more than 65,000 images with positive detections, which was archived in a public repository. The catalog captures physically plausible large‐scale gravity wave occurrence patterns while also showing that detectability is reduced under elevated sensor noise and strong artificial light contamination. These results demonstrate that machine learning based object detection can systematically extract diverse mesospheric gravity wave events from the long‐term VIIRS DNB nightglow record.
Abstract Radar observations from a prescribed fire experiment reveal a large‐scale, billow‐like vorticity structure associated with the plume head near the onset of plume bending. This bending limits the vertical extent of the plume and defines the characteristic plume ceiling height. This study investigates plume bending under idealized sheared‐crossflow and quasi‐steady stratified atmospheric boundary layer conditions. Large‐eddy simulations using the Cloud Model 1 are conducted under idealized boundary‐layer configurations to qualitatively reproduce the observed plume morphology and to examine plume‐head evolution under varying fire‐generated surface heat‐flux, background shear, and stratification. Building on the classic theory, this study presents a scaling framework for estimating the characteristic plume ceiling height based on a modified Byram's convective number that accounts for sheared crossflow. The proposed scaling successfully reproduces the behavior of the idealized large‐eddy simulations and highlights the roles of shear and stratification in controlling the characteristic plume ceiling height.
Abstract An audiomagnetotelluric (AMT) survey was conducted within the Alto Paranaíba Igneous Province, southeastern Brazil, to delineate shallow occurrences of kamafugite, a rare ultrapotassic volcanic rock worldwide. A dense grid of AMT stations was deployed, allowing the construction of a high‐resolution 3D electrical resistivity model. Dimensionality analyses revealed a structurally complex subsurface dominated by pronounced three‐dimensional behavior. The interpretation of the resistivity model enabled the characterization of a complex and extinct volcanic system, including the reconstruction of paleo‐volcanic conduits at depth. The model delineated probable zones of hydrothermal fluid percolation related to volatile exsolution during magma ascent, which are intensely deformed and suggest the past occurrence of hydraulic fracturing and seismic swarm activity. To validate these interpretations, the AMT results were integrated with seismic reflection data, well‐log resistivity, magnetic data, and lithological information from shallow boreholes, acquired in a noisy agricultural environment. The results demonstrate that audiomagnetotellurics is an effective tool for investigating the volcanic evolution of igneous provinces and for imaging subsurface volcanic architectures in mineral exploration settings. Moreover, the identification and characterization of kamafugite bodies highlight the potential for producing kamafugite‐based soil remineralizers, which could contribute to Brazil's future self‐sufficiency in fertilizer production.
Abstract The representation of low clouds and precipitation remains a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub‐grid variability and scale‐dependent sampling. This study evaluates the performance of preliminary simulations from the Large‐Eddy Simulation (LES) Atmospheric Radiation Measurement Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), focusing on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation rate across closed‐cell, open‐cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA‐2 reanalyses, we assess the representativeness of ground‐based point observations by analyzing their correspondence to model‐resolved temporal means. Results suggest that observational sampling of at least 6 hr is required to achieve consistency with domain‐scale averages, in particular for observations that exhibit pronounced sub‐grid heterogeneity, such as precipitation. Differences between ERA5‐ and MERRA‐2‐driven simulations are detectable but secondary relative to regime and temporal‐scale effects, and diminish with extended averaging. These findings highlight the importance of regime‐aware model evaluation strategies and potentially demonstrate how LES can inform observation‐model comparison practices and the development of cloud and precipitation parameterizations in ESMs.
Abstract Unexpectedly following launch, the Lunar Trailblazer mission experienced software anomalies that led it to orient solar panels away from the sun and lose communication with Earth. This paper describes efforts to determine the spacecraft state and attempt recovery of the mission's science at the Moon. First, ground observatories at optical and radar wavelengths were engaged to maintain custody of the spacecraft and knowledge of its trajectory. Second, viability of recovery of the mission science objectives was established via testbed work to understand system behavior in fault conditions and determination of trajectories and maneuvers that would enable lunar orbit insertion. Third, optical photometry and radar doppler broadening were employed to determine Lunar Trailblazer's spin and orientation, using approaches similar to those in asteroid studies, to establish when solar panels might again receive sufficient power to boot the spacecraft and initialize its radio. Fourth, X‐band‐capable groundstations in addition to the NASA Deep Space Network were engaged to monitor for the spacecraft's radio carrier signal nearly continually, including crowd‐sourced monitoring and tip‐and‐cue style commanding. Lunar Trailblazer left the Earth‐Moon system and is in a 14‐year Earth return, heliocentric orbit. As it moved further away from Earth prospects for recovery became formidable; ultimately, the ability of the telecom system to return telemetry to Earth would have been insufficient to enable actions to recover the spacecraft, and the recovery attempt ended 6 July 2025. Lunar Trailblazer's mission recovery efforts illuminate capabilities in characterizing a 1–3.5 m 3 size non‐cooperative object in cis‐lunar space.
Abstract National Aeronautics and Space Administration's Deep Blue (DB) aerosol project aims to produce consistent, long‐term climate data records of atmospheric aerosol properties using satellite observations. The DB algorithm has been extensively applied to low Earth orbit (LEO) sensors, including the Moderate Resolution Imaging Spectroradiometer and the Visible Infrared Imaging Radiometer Suite (VIIRS), among others. Building on this foundation, this study extends the application of DB to geostationary Earth orbit (GEO) imagers to create consistent aerosol data records with vastly superior temporal coverage. The latest VIIRS Version 2 DB algorithm is adapted for use with the GOES‐16/17 Advanced Baseline Imagers and the Himawari‐8 Advanced Himawari Imager. Comparisons of retrieved aerosol optical depth (AOD) from May 2019 to April 2020 against the Aerosol Robotic Network (AERONET) show that GEO sensors provide nearly 10 times the matchup points of VIIRS, with comparable validation statistics. In addition, the GEO products effectively reproduced both the magnitude and shape of diurnal AOD variations observed by AERONET for haze events in central and eastern North America, and East Asia, as well as for biomass burning events in South America and Southeast Asia. Analyses of the diurnal cycle of AOD confirm that GEO products can serve as a useful tool to monitor continuous aerosol transport and daytime variations, providing more representative daily mean AOD than LEO sensors. Overall, the GEO DB algorithm offers a robust framework for time‐resolved monitoring of aerosol properties, complementing existing LEO observations.
Abstract The Chilean subduction zone is a highly active seismic region, producing megathrust earthquakes approximately every decade. We apply a stochastic approach to assess spatial variations in seismic wave characteristics along the Chilean trench using weak motion data. We analyze >10,000 weak motion records from 1,984 aftershocks (Ml 2.5–6.3, with maximum depth and distance of 40 and 500 km, respectively) of the 2010 Mw 8.8 Maule earthquake in central Chile (CCH) and the 2014 Mw 8.2 Iquique earthquake in northern Chile (NCH). Source‐attenuation models for the Iquique, Valparaíso, and Maule sub‐regions were developed using Random Vibration Theory and regressions on filtered ground velocities and Fourier spectral amplitudes (0.25–20 Hz). The results reveal that geometrical spreading and frequency‐dependent attenuation vary spatially. The source spectra differ mostly at intermediate frequencies using a two‐corner‐frequency source model. Differences in distance scaling and attenuation of seismic amplitude indicate faster energy loss along CCH paths, providing independent validation for the existing Chilean non‐ergodic ground motion model. Seismic energy propagates efficiently through the colder, drier crust of NCH, while the weaker and warmer crust of CCH attenuates it faster. The frequency dependence of attenuation (η) ranges from 0.30 to 0.35, but high–frequency decay κo does not show significant spatial dependence. Separating contributions from different seismic phases becomes critical for stochastic modeling at higher frequencies and distances >250 km. The properties of the crustal medium, such as anelastic attenuation and geometrical spreading, can be reliably constrained using moderate earthquakes and scaled to larger events for regional ground motion simulations.
Abstract This study examines the impact of assimilating all‐sky microwave radiances from the Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission within the NASA Global Earth Observing System (GEOS) data assimilation and forecasting framework based on the Gridpoint Statistical Interpolation (GSI) system. Observing system experiments and Forecast Sensitivity to Observation Impact (FSOI) diagnostics were conducted, covering July through September 2023 for the experiments and August 2023 for the FSOI analysis. Results show that TROPICS radiances improve the representation of tropical moisture, temperature, and wind structures and reduce forecast error across multiple atmospheric fields. The strongest improvements occur in the lower and middle troposphere and persist through forecast day five. The constellation architecture plays a key role, with the four‐satellite configuration producing larger and more spatially coherent benefits than any individual platform in idealized experiments, with smaller but consistent positive impacts in the full GEOS‐FP system. Even within a radiance‐rich observing system, TROPICS provides complementary information on moist convective processes. Consistency between deterministic forecast verification and FSOI diagnostics supports the robustness of these findings. Overall, small‐satellite constellations with high revisit rates can add value to global numerical weather prediction by improving the depiction of tropical convection in modern data assimilation systems.
Abstract Precipitable water vapor (PWV) is an essential parameter for the study of weather and climate behavior. This work presents a novel regional classification of PWV regimes based on clustering techniques applied to Global Navigation Satellite System radio occultation‐derived and ERA5 reanalysis data with and without seasonal removal. Spatially and temporally averaged data sets were constructed using 15° × 15° latitude, longitude bins and monthly temporal intervals over the period June 2006 to September 2024. Multiple clustering approaches with Euclidean and dissimilarity metrics, including hierarchical (Linkage) and non‐hierarchical (k‐means, k‐medoids) algorithms were applied. Features such as mean and standard deviation of every full time series as well as wavelet‐derived characteristics of deseasonalized anomalies were used in Euclidean methods whereas the dynamic time warping procedure was applied to quantify dissimilarity. Results across data sets and methods are compared and they reveal similar regional structures which provide insights into global atmospheric moisture behavior. PWV across all algorithms and data shows strong and consistent latitudinal clustering patterns but with some differences over large land and ocean areas. In anomalies, the amount of groupings that the clustering methods are able to determine are much less and dissimilarity metrics shows more coherent meridional structure than Euclidean options. We also check the previous outcomes against ERA5 high resolution data results.
Abstract Snow on Antarctic sea ice modulates albedo, thermodynamic growth, and snow–ice formation, yet remains a leading uncertainty in altimetry‐derived sea‐ice thickness. Here we use the post‐2022 CRYO2ICE configuration to derive along‐track winter snow thickness from ICESat‐2 laser and CryoSat‐2 Ku‐band radar freeboards over the Weddell and Ross sectors. We analyze 82,341 winter matchups (August 2022–September 2025) using a 5 km, 4 hr collocation criterion and propagate freeboard and snow‐density uncertainties. Retrieved snow thickness is consistently larger in the Weddell Sea (mean 0.255 m, median 0.188 m) than the Ross Sea (0.217 m, 0.156 m), consistent with the older, thicker western Weddell ice. The contrast persists across sampled months and years and under common snow‐density and penetration‐factor assumptions. Formal per‐matchup precision (0.039–0.040 m) is dominated by CryoSat‐2 radar‐freeboard uncertainty, whereas the absolute magnitude is set by the unresolved Ku‐band scattering horizon. Comparison with AMSR2 passive‐microwave snow depth shows weak point‐to‐point agreement (r2=0.062 and <0.001 in the Weddell and Ross sectors), reflecting differing measurement physics and spatial support. Nevertheless, both independently reproduce thicker Weddell than Ross snow. Under a common penetration factor, absolute sector‐mean snow thickness varies by approximately a factor of two across the tested range, whereas the sector ordering is preserved under any uniform choice of penetration factor. CRYO2ICE therefore resolves a repeatable regional freeboard‐difference signal, but conversion of that signal to absolute snow thickness remains conditional on the poorly constrained, ice‐regime‐dependent Ku‐band scattering horizon.
