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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparison of Polarized Radiative Transfer Codes Used by the EHT Collaboration

Interpretation of resolved polarized images of black holes by the Event Horizon Telescope (EHT) requires predictions of the polarized emission observable by an Earth-based instrument for a particular model of the black hole accretion system. Such predictions are generated by general relativistic radiative transfer (GRRT) codes, which integrate the equations of polarized radiative transfer in curved spacetime. A selection of ray-tracing GRRT codes used within the EHT Collaboration is evaluated for accuracy and consistency in producing a selection of test images, demonstrating that the various methods and implementations of radiative transfer calculations are highly consistent. When imaging an analytic accretion model, we find that all codes produce images similar within a pixel-wise normalized mean squared error (NMSE) of 0.012 in the worst case. When imaging a snapshot from a cell-based magnetohydrodynamic simulation, we find all test images to be similar within NMSEs of 0.02, 0.04, 0.04, and 0.12 in Stokes I , Q , U , and V , respectively. We additionally find the values of several image metrics relevant to published EHT results to be in agreement to much better precision than measurement uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Developing Partnership between San Jose State University and DOE Lawrence Livermore National Laboratory to Enhance Climate Research Equity and Inclusion

One of the key objectives of this project was to develop partnership between San Jose State University (SJSU) and the Lawrence Livermore National Laboratory (LLNL), a US Department of Energy (DOE) funded national laboratory. Both institutions are closely located within the San Francisco Bay Area in California and their researchers share overlapping research interests and expertise related to Earth system sciences. By leveraging their connections with LLNL, faculty and students from SJSU gained exposure to state-of-the-art observations and simulations related to Earth system sciences, including but not limited to the usage of the facility data provided by the DOE Atmospheric Radiation Measurement (ARM) program and data analysis techniques for interpreting and analyzing the DOE Energy Exascale Earth System Model (E3SM) simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The OSIRIS-REx Sample Return Capsule re-entry: A coordinated seismo-acoustic observational campaign for the study of meteor phenomena

Objects entering Earth’s atmosphere at hypersonic velocities may generate powerful acoustic waves. Depending on atmospheric conditions and acoustic propagation paths, they may be captured using ground or balloon-borne microbarometers and microphones. Impacts into the Earth’s atmosphere by asteroids in a meter-size range are sporadic and unannounced, and thus, well-documented scientific observations of asteroids are rare and generally happen by chance. Arriving from interplanetary space at hypervelocity, spacecraft are considered analogues for low velocity meteoroids and asteroids impacting the Earth’s atmosphere, and as such provide unprecedented and unique opportunity to carry out planned observational campaigns and perform detailed studies of meteor phenomena. However, since the end of the Apollo era, only four instances of a hypersonic re-entry of an artificial body from interplanetary space with an incident speed of 11-12 km/s have been observed and studied. These were the Sample Return Capsules (SRCs) that brought physical samples of extraterrestrial material back to Earth (Genesis, Stardust, Hayabusa 1, Hayabusa 2). These re-entries were also detected by infrasound and/or seismic sensors. The next opportunity to observe an artificial meteor will be on 24 September 2023 with the re-entry of NASA’s OSIRIS-REx SRC that will bring samples of the carbonaceous near-Earth asteroid Bennu. The re-entry consists of several flight phases, including hypersonic and supersonic, providing a unique opportunity to observe these by infrasound and seismic sensors. We will discuss observational campaign efforts aimed to capture geophysical signals generated by the OSIRIS-REx SRC re-entry. This campaign utilizes an unparalleled number of instruments, both ground and airborne, strategically positioned in the immediate and extended region around the projected re-entry trajectory to maximize the scientific output.

47 - OTHER INSTRUMENTATION↗
DOE OSTI2021

Low-energy spin dynamics in rare-earth perovskite oxides

We review recent studies of spin dynamics in rare-earth orthorhombic perovskite oxides of the type RMO 3 , where R is a rare-earth ion and M is a transition-metal ion, using single-crystal inelastic neutron scattering (INS). After a short introduction to the magnetic INS technique in general, the results of INS experiments on both transition-metal and rare-earth subsystems for four selected compounds (YbFeO 3 , TmFeO 3 , YFeO 3 , YbAlO 3 ) are presented. We show that the spectrum of magnetic excitations consists of two types of collective modes that are well separated in energy: gapped magnons with a typical bandwidth of <70 meV, associated with the antiferromagnetically (AFM) ordered transition-metal subsystem, and AFM fluctuations of <5 meV within the rare-earth subsystem, with no hybridization of those modes. We discuss the high-energy conventional magnon excitations of the 3d subsystem only briefly, and focus in more detail on the spectacular dynamics of the rare-earth sublattice in these materials. We observe that the nature of the ground state and the low-energy excitation strongly depends on the identity of the rare-earth ion. In the case of non-Kramers ions, the low-symmetry crystal field completely eliminates the degeneracy of the multiplet state, creating a rich magnetic field-temperature phase diagram. In the case of Kramers ions, the resulting ground state is at least a doublet, which can be viewed as an effective quantum spin-1/2. Equally important is the fact that in Yb-based materials the nearest-neighbor exchange interaction dominates in one direction, despite the three-dimensional nature of the orthoperovskite crystal structure. The observation of a fractional spinon continuum and quantum criticality in YbAlO3 demonstrates that Kramers rare-earth based magnets can provide realizations of various aspects of quantum low-dimensional physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Present and Future Changes in Land‐Atmosphere Coupling of Water and Energy Over Extratropical Forest Regions

Abstract Couplings between land and the near surface atmosphere are modulated by interactions between soil conditions, vegetation dynamics, turbulent fluxes, and atmospheric properties. How the land‐atmosphere coupling responds to warming and elevated CO 2 are important for understanding the land surface carbon, energy, and water cycles. In this work, we documented this coupled land‐atmosphere network based on observations and the Energy Exascale Earth System Model (E3SM) simulations over extratropical forest ecosystems. We employed a transfer entropy approach and novel network metrics to reveal patterns and strength of the land‐atmosphere coupling under historical conditions and a future high emission scenario (SSP585). We found that, in observations, the present‐day extratropical forest coupling network has high network connectivity (72%–88% of the targeted processes are coupled). E3SM reasonably captured the extratropical forest coupling network (modeled network connectivity was 81%–96%) and predicted that the coupling strength would significantly increase by 28% (±3%) under warming and elevated CO 2 conditions. Furthermore, E3SM factorial coupled experiments suggested that warming enhanced soil nitrogen mineralization favoring plant nitrogen uptake and vegetation growth were responsible for the strengthening future land‐atmosphere coupling. This work provides new metrics to analyze and document complex couplings for coupled earth system processes and highlights the important roles soil nutrient availability and biogeochemistry have on land‐atmosphere coupling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Earth as a Proxy Exoplanet: Deconstructing and Reconstructing Spectrophotometric Light Curves

Point-source spectrophotometric (single-point) light curves of Earth-like planets contain a surprising amount of information about the spatial features of those worlds. Spatially resolving these light curves is important for assessing time-varying surface features and the existence of an atmosphere, which in turn is critical to life on Earth and significant for determining habitability on exoplanets. Given that Earth is the only celestial body confirmed to harbor life, treating it as a proxy exoplanet by analyzing time-resolved spectral images provides a benchmark in the search for habitable exoplanets. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) provides such an opportunity, with observations of ∼5000 full-disk sunlit Earth images each year at 10 wavelengths with high temporal frequency. We disk-integrate these spectral images to create single-point light curves and decompose them into principal components (PCs). Using machine-learning techniques to relate the PCs to six preselected spatial features, we find that the first and fourth PCs of the single-point light curves, contributing ∼83.23% of the light-curve variability, contain information about low and high clouds, respectively. Surface information relevant to the contrast between land and ocean reflectance is contained in the second PC, while individual land subtypes are not easily distinguishable (<0.1% total light-curve variation). We build an Earth model by systematically altering the spatial features to derive causal relationships to the PCs. This model can serve as a baseline for analyzing Earth-like exoplanets and guide wavelength selection and sampling strategies for future observations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2022

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying the Occurrence of Record Hot Years Through Normalized Warming Trends

Surface air temperature trends and extreme events are of global concern and they are related. Here we show that the occurrence of record hot years over different latitudes from 1960-2019 are more strongly correlated with the observational annual mean temperature trends normalized by internal variability. Compared with the raw trends showing Arctic amplification, the normalized trends show a tropical amplification over land. Two hot spots with more frequent occurrence of record hot years are identified: northern hemisphere ocean (versus land) and southern hemisphere tropical land (versus mid- and high-latitude lands). Ensemble mean results from 32 Earth system models agree with observations better than individual models, but they do not reproduce observed large differences in correlations across latitudes between normalized trends and record-breaking events over land versus ocean. Furthermore, our results enable the quantification of record hot year occurrence through normalized warming trends and provide new metrics for model evaluation and improvement.

58 GEOSCIENCES↗
DOE OSTI2025

A Greening Future Elevates Flash Drought Risk in Northern Mid‐to‐High Latitudes

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Drought↗
DOE OSTI2021

The Hazards Posed by Mesoscale Lightning Megaflashes

Lightning megaflashes extending over >100-km distances have been observed by the Geostationary Lightning Mappers (GLMs) on NOAA’s R-series Geostationary Operational Environmental Satellites (GOES). The hazards posed by megaflashes are unclear, however, because of limitations in the GLM data. We address these by reprocessing GOES-16 GLM measurements from 1 January 2018 to 15 January 2020 and integrating them with Earth Networks Global Lightning Network (ENGLN) observations. ENGLN verified 194 880 GLM megaflashes as natural lightning. Of these, 127 479 flashes occurred following the October 2018 GLM software update that standardized GLM timing. Reprocessed GLM/ENGLN lightning maps from these postupdate cases provide a comprehensive view of how individual megaflashes evolve. This megaflash dataset is used to generate statistics that describe their hazards. The average megaflash produces 5–7 cloud-to-ground (CG) strokes that are spread across 40%–50% of the flash extent. As flash extent increases beyond 100 km, megaflashes become concentrated in key hot-spot regions in North and South America while the number of CG and intracloud events per flash and the overall peak current increase. CGs in the larger megaflashes occur over 80% of the flash extent measured by GLM, and the majority contain regions where the megaflash is the only lightning activity in the preceding hour. These statistics demonstrate that there is no safe location below an electrified cloud that is producing megaflashes, and current lightning safety guidance is not always sufficient to mitigate megaflash hazards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests

Earth’s forests face grave challenges in the Anthropocene, including hotter droughts increasingly associated with widespread forest die-off events. But despite the vital importance of forests to global ecosystem services, their fates in a warming world remain highly uncertain. Lacking is quantitative determination of commonality in climate anomalies associated with pulses of tree mortality—from published, field-documented mortality events—required for understanding the role of extreme climate events in overall global tree die-off patterns. Here we established a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970. Our analysis quantifies a global “hotter-drought fingerprint” from these tree-mortality sites—effectively a hotter and drier climate signal for tree mortality—across 675 locations encompassing 1,303 plots. Frequency of these observed mortality-year climate conditions strongly increases nonlinearly under projected warming. Our database also provides initial footing for further community-developed, quantitative, ground-based monitoring of global tree mortality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulations and Experiments Reveal Effect of Nanopores on Helium Diffusion in Quartz

The diffusion properties of noble gases in minerals are widely used to reconstruct the thermal histories of rocks. In this work, we combine density functional theory (DFT) calculations with laboratory experiments to investigate controls on helium diffusion in quartz. DFT calculations for perfect α-quartz predict substantially lower activation energies and frequency factors for helium diffusion than observed in laboratory experiments, especially in the [001] direction. These results imply that no helium could be retained in quartz at Earth surface temperatures, which conflicts with observations of partial cosmogenic 3 He retention over geologic time scales. Here, we implement a model of helium diffusion in α-quartz modulated by nanopore defects that disrupt energetically favorable diffusion pathways. In this model, we find that laboratory-determined diffusivities can be most closely reproduced when a helium atom encounters ~70 nanopore sites per million interstitial sites. The results of our model indicate that diffusion of helium in natural quartz, like other noble gases in other minerals, can be significantly modulated by extended defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Post‐Perovskite Transition in Fe‐ and Al‐Bearing Bridgmanite: Effects on Seismic Observables

Abstract The primary phase of the Earth’s lower mantle, (Al, Fe)‐bearing bridgmanite, transitions to the post‐perovskite (PPv) phase at Earth’s deep mantle conditions. Despite extensive experimental and ab initio investigations, there are still important aspects of this transformation that need clarification. Here, we address this transition in (Al 3+ , Fe 3+ )‐, (Al 3+ )‐, (Fe 2+ )‐, and (Fe 3+ )‐bearing bridgmanite using ab initio calculations and validate our results against experiments on similar compositions. Consistent with experiments, our results show that the onset transition pressure and the width of the two‐phase region depend distinctly on the chemical composition: (a) Fe 3+ ‐, Al 3+ ‐, or (Al 3+ , Fe 3+ )‐alloying increases the transition pressure, while Fe 2+ ‐alloying has the opposite effect; (b) in the absence of coexisting phases, the pressure‐depth range of the Pv‐PPv transition is likely too broad to cause a sharp D” discontinuity (<30 km); (c) the average Clapeyron slope of the two‐phase regions are consistent with previous measurements, calculations in MgSiO 3 , and inferences from seismic data. In addition, (d) we observe a softening of the bulk modulus in the two‐phase region. The consistency between our results and experiments gives us the confidence to proceed and examine this transition in aggregates with different compositions computationally, which will be fundamental for resolving the most likely chemical composition of the D" region by analyses of tomographic images.

Geochemistry & Geophysics↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗