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DOE OSTI2023

Examining the effects of soil entrainment during nuclear cloud rise on fallout predictions using a multiscale atmospheric modeling framework

Current operational models for nuclear cloud rise over land were developed and validated using observations from shallow-buried or surface detonations, where lofted soil quickly mixed with fission products from the detonation. These models poorly predict fallout from elevated detonations near the fallout-free height of burst (FFHOB), where interactions with the ground are limited and the mixing of fission products and lofted soil is incomplete. Fallout-free is a misnomer at this HOB, as fallout was observed in these cases, but was below the levels of concern, especially off-grounds of the nuclear test site. To correctly characterize and model fallout from detonations near the FFHOB, models must be developed which can capture the stratified nature of the particle and activity-size distributions within the cloud. Previously, it was shown that the Weather Research and Forecasting (WRF) model can accurately simulate nuclear cloud rise for airbursts with little to no ground interactions (Arthur et al., 2021). That work is expanded here by (1) using a radiation-hydrodynamics code to improve the fireball initialization in WRF, (2) further developing an aerosol package from WRF-Chem to simulate lofted soil, and (3) combining the WRF cloud rise simulations with the operational models used at the National Atmospheric Release Advisory Center (NARAC) for fallout modeling. Using this combination of codes, the Upshot-Knothole Grable detonation, which was just below the FFHOB, is simulated from seconds after detonation through cloud rise and fallout, and results are compared to historical test data. Here, the results show improved prediction of dose rate and highlight the need to correctly characterize the entrainment of material into the cloud and the subsequent mixing of fission products with entrained material.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2024

Investigating Gadolinium-Lined Sodium-Iodide Neutron Detectors for Mobile Applications

For enhancing the effectiveness of nonproliferation efforts in neutron detection, most portable instruments rely on 6 Li scintillators, 10 B-based detectors, or gas-filled 3 He proportional counters. Additionally, gamma-ray detectors based on scintillators and semiconductors are often employed for search applications to find radioactive material in the field. These systems typically include dedicated detectors along with separate high voltage supplies and processing electronics for the gamma-ray and neutron detectors. Ideally, a portable radiation detection system should be lightweight, compact, and cost-effective. In the field, scintillators can serve a dual purpose: (1) detecting gamma-rays and (2) detecting neutrons. Gamma-ray detection with scintillators is based on the interaction of gamma-rays within the scintillating material, whereas neutron detection depends indirectly on neutron capture events. These capture events generate conversion electrons and gamma-rays, which can interact with the scintillator. For enhancing neutron capture, the scintillator can be surrounded by neutron absorber materials with a high neutron cross section. The resulting secondary electrons and gamma-rays from neutron interactions, depending on the absorber material used, can then be analyzed to detect the presence of neutron sources. Similarly, semiconductor-based detectors can be employed along with neutron absorbers as liners for neutron detection. 158 Gd has a significantly larger neutron cross section than 3 He, commonly used in gas-filled proportional counters, as shown in Figure 1. For thermal (0.025 eV) neutrons, the absorption cross section of 158 Gd is 10,000 times greater than that of 3 He (refer to Figure 1). This feature makes naturally occurring gadolinium, which consists of 24.8% 158 Gd, a promising neutron absorber material for use in combination with gamma-ray detectors–yielding a hybrid detector–for neutron detection.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS2007

Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments

A cloud-resolving model (CRM) is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a three-and-a-half day subperiod of the Department of Energy-Atmospheric Radiation Measurement Program s Mixed-Phase Arctic Cloud Experiment (M-PACE). The CRM is implemented with an advanced two-moment microphysics scheme, a state-of-the-art radiative transfer scheme, and a complicated third-order turbulence closure. Concurrent meteorological, aerosol, and ice nucleus measurements are used to initialize the CRM. The CRM is prescribed by time-varying large-scale advective tendencies of temperature and moisture and surface turbulent fluxes of sensible and latent heat. The CRM reproduces the occurrences of the single- and double-layer MPS clouds as revealed by the M-PACE observations. However, the simulated first cloud layer is lower and the second cloud layer thicker compared to observations. The magnitude of the simulated liquid water path agrees with that observed, but its temporal variation is more pronounced than that observed. As in an earlier study of single-layer cloud, the CRM also captures the major characteristics in the vertical distributions and temporal variations of liquid water content (LWC), total ice water content (IWC), droplet number concentration and ice crystal number concentration (nis) as suggested by the aircraft observations. However, the simulated mean values differ significantly from the observed. The magnitude of nis is especially underestimated by one order of magnitude. Sensitivity experiments suggest that the lower cloud layer is closely related to the surface fluxes of sensible and latent heat; the upper cloud layer is probably initialized by the large-scale advective cooling/moistening and maintained through the strong longwave (LW) radiative cooling near the cloud top which enhances the dynamical circulation; artificially turning off all ice-phase microphysical processes results in an increase in LWP by a factor of 3 due to interactions between the excessive LW radiative cooling and extra cloud water; heating caused by phase change of hydrometeors could affect the LWC and cloud top height by partially canceling out the LW radiative cooling. It is further shown that the resolved dynamical circulation appears to contribute more greatly to the evolution of the MPS cloud layers than the parameterized subgrid-scale circulation.

Luo, Yali↗

DOE OSTI2024

Generalized rate theory for void and bubble swelling and its application to δ -plutonium

A rate theory for void and bubble swelling is derived that allows both vacancies and self-interstitial atoms to be generated by thermal activation at all sinks. In addition, they can also be produced by displacement damage from external and internal radiation. This generalized rate theory (GRT) is applied to swelling of gallium-stabilized δ-plutonium in which α-decay causes the displacement damage. Since the helium atoms produced also become trapped in vacancies, a distinction is made between empty and occupied vacancies. The growth of helium bubbles observed by transmission electron microscopy in weapons-grade and in material enriched with Pu238 is analyzed, using different values for the formation energy of self-interstitial atoms (SIA) and two different sets of relaxation volumes for the vacancy and for the SIA. One set allows preferential capture of SIA at dislocations, while the other set gives equal preference to both vacancy and SIA. It is found that the helium bubble diameters observed are in better agreement with GRT predictions if no preferential capture occurs at dislocations. Therefore, helium bubbles in δ-plutonium will not evolve into voids. Furthermore, the helium density within the bubbles remains sufficiently high to cause thermal emission of SIA. Based on a helium density between two to three helium atoms per vacant site, the sum of formation and migration energies must be around 2.0 eV for SIA in δ-plutonium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Autoregressive long-horizon prediction of plasma edge dynamics *

Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data for the KSTAR tokamak, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1–100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.

autoregressive deep learning↗

DOE OSTI2021

Gauge invariance of light-matter interactions in first-principle tight-binding models

In this work, we study the different ways of introducing light-matter interaction in first-principle tight-binding (TB) models. The standard way of describing optical properties is the velocity gauge, defined by linear coupling to the vector potential. In finite systems a transformation to represent the electromagnetic radiation by the electric field instead is possible, albeit subtleties arise in periodic systems. The resulting dipole gauge is a multi-orbital generalization of the Peierls substitution. In this work we investigate the accuracy for both pathways, with particular emphasis on gauge invariance, for TB models constructed from maximally localized Wannier functions. This approach accurately captures the light-matter interaction close to the Fermi level. Focusing on paradigmatic two-dimensional materials, we construct first-principle models and calculate the response to electromagnetic fields in linear response and for strong excitations. Benchmarks against fully converged first-principle calculations allow for ascertaining the accuracy of the TB models. We find that the dipole gauge provides a more accurate description than the velocity gauge in all cases. The main deficiency of the velocity gauge is an imperfect cancellation of paramagnetic and diamagnetic current. Formulating a corresponding sum rule however provides a way to explicitly enforce this cancellation. This procedure corrects the TB models in the velocity gauge, yielding excellent agreement with dipole gauge and thus restoring gauge invariance.

2-dimensional systems↗

DOE OSTI2021

Land–Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, in this work we assess the land–atmosphere (LA) coupling in the North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the local coupling metrics. NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local LA coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases toward mid-to-late summers, which may be an amplification through a positive LA feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

58 GEOSCIENCES↗

NASA NTRS2021

Land-Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes Between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land-atmosphere (L-A) coupling in North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the Local Coupling metrics (Santanello et al. 2018). NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local L-A coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases towards mid-to-late summers, which may be an amplification through a positive L-A feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

land-atmosphere↗

DOE OSTI2022

The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem

Gross primary productivity (GPP) is the largest flux in the global carbon cycle and satellite-based GPP estimates have long been used to study the trends and interannual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar-orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite-R series (GOES-R) to test the ability of subdaily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We compared three methods to estimate GPP: (a) a light-use efficiency model, (b) a linear relationship between the product of near-infrared reflectance of vegetation and photosynthetically active radiation (LIN-NIR v P) and EC tower GPP, and (c) a light response curve (LRC-NIR v P) between NIR v P and EC GPP. The LRC-NIR v P achieved the lowest mean absolute error for winter (2 µmol CO 2 m –2 s –1 ), spring (2.51 µmol CO 2 m –2 s –1 ), summer (1.43 µmol CO 2 m –2 s –1 ), and fall (1.35 µmol CO 2 m –2 s –1 ). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation toward the morning hours during the dry summers. The LRC-NIRvP and the light-use efficiency model were in agreement with these patterns of a shift in peak daily GPP toward the morning hours during summer. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Realism of Lagrangian Large Eddy Simulations Driven by Reanalysis Meteorology: Tracking a Pocket of Open Cells Under a Biomass Burning Aerosol Layer

An approach to drive Lagrangian large eddy simulation (LES) of boundary layer clouds with reanalysis data is presented and evaluated using satellite (Spinning Enhanced Visible and Infrared Imager, SEVIRI) and aircraft (Cloud-Aerosol-Radiation Interactions and Forcing, CLARIFY) measurements. The simulations follow trajectories of the boundary layer flow. They track the formation and evolution of a pocket of open cells (POC) underneath a biomass burning aerosol layer in the free troposphere. The simulations reproduce the evolution of observed stratocumulus cloud morphology, cloud optical depth, and cloud drop effective radius, and capture the timing of the cloud state transition from closed to open cells seen in the satellite imagery on the three considered trajectories. They reproduce a biomass burning aerosol layer identified by the in-situ aircraft measurements above the inversion of the POC. Entrainment of aerosol from the biomass burning layer into the POC is limited to the extent of having no impact on cloud- or boundary layer properties, in agreement with the CLARIFY observations. The two-moment bin microphysics scheme used in the simulations reproduces the in-situ cloud microphysical properties reasonably well. A two-moment bulk microphysics scheme reproduces the satellite observations in the non-precipitating closed-cell state, but overestimates liquid water path and cloud optical depth in the precipitating open-cell state due to insufficient surface precipitation. A boundary layer cold and dry bias occurring in LES can be counteracted by reducing the grid aspect ratio and by tightening the large scale wind speed nudging towards the surface.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Accuracy and Resolution Evaluation of the E-Beam Profile Scanner at the Fermilab Main Injector

The objective of this work is to assess the accuracy of measurements made by the Electron Beam Profile Scanner (EBPS), which captures the trajectory of an electron beam with and without a proton beam present. The proton beam induces deflection in the electron beam, which is influenced by proton charges. For high-resolution images, the probe beam needs to be of high intensity, small diameter, and small divergence, evaluated using a phosphor screen and an optical transition radiation (OTR) screen. The capabilities of the Kimball Physics electron gun (eGun) will be considered for accuracy. Additionally, the Zemax software will be utilized to characterize the optical elements.

Mwaniki, M. W. [IIT, Chicago] (ORCID:0000000169057↗

DOE OSTI2020

Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

58 GEOSCIENCES↗

NASA NTRS2013

X-ray Reflected Spectra from Accretion Disk Models. III. A Complete Grid of Ionized Reflection Calculations

We present a new and complete library of synthetic spectra for modeling the component of emission that is reflected from an illuminated accretion disk. The spectra were computed using an updated version of our code xillver that incorporates new routines and a richer atomic data base. We offer in the form of a table model an extensive grid of reflection models that cover a wide range of parameters. Each individual model is characterized by the photon index Gamma of the illuminating radiation, the ionization parameter zeta at the surface of the disk (i.e., the ratio of the X-ray flux to the gas density), and the iron abundance A(sub Fe) relative to the solar value. The ranges of the parameters covered are: 1.2 <= Gamma <= 3.4, 1 <= zeta <= 104, and 0.5 <= A(sub Fe) <= 10. These ranges capture the physical conditions typically inferred from observations of active galactic nuclei, and also stellar-mass black holes in the hard state. This library is intended for use when the thermal disk flux is faint compared to the incident power-law flux. The models are expected to provide an accurate description of the Fe K emission line, which is the crucial spectral feature used to measure black hole spin. A total of 720 reflection spectra are provided in a single FITS file suitable for the analysis of X-ray observations via the atable model in xspec. Detailed comparisons with previous reflection models illustrate the improvements incorporated in this version of xillver.

X-ray↗

NASA NTRSDate not supplied

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

A new Exploration Extravehicular Activity Suit (xEVAS) is being designed to replace the current Extravehicular Mobility Unit (EMU) for the National Aeronautics and Space Administration’s (NASA’s) Artemis program to return astronauts to the lunar surface. This new suit will allow for increased range of motion compared the current EMU and Apollo era suits and will have additional features that will enhance the health and safety of exploration. With the design of lunar missions and the xEVAS progressing, it is important to consider possible injuries and injury mechanisms that could occur in the suit. To address these concerns, the suited Injury Modes and Effects Analysis (IMEA) was developed to outline suited injury scenarios and rank them based on risk score. The IMEA documents possible scenarios and underlying mechanisms of injury while wearing an extravehicular activity (EVA) suit. Tasks during lunar surface EVA as well as training events to prepare for lunar missions were considered as history has shown that more suit injuries occur during training than in flight. Each scenario is ranked with a consequence and likelihood scoring based on our current understanding of the suit and Artemis design reference missions to identify high-risk cases that will drive further work in suited injury. Injuries, mechanisms of injury, and mitigation strategies are evaluated within each scenario. The Suited Injury Summit was held on January 5, 2022, to vet the IMEA with external experts. This was an all-day virtual meeting with the suited injury team, ergonomists, suit engineers, safety engineers, the flight operations directorate, flight doctors, astronauts, astronaut strength, conditioning, and rehabilitation specialists (ASCRS), and external subject matter experts (SMEs). External SMEs consisted of surgeons with varying specialties. The intent of this meeting was to walk through the top injury risks identified in the analysis, identify any gaps that were not captured, and discuss mitigations. With participation from all groups, countless lessons-learned came from the Summit meeting. Using the lessons-learned and discussion from the Summit, the top 10 risks have been identified: neutral buoyancy laboratory training, hand/glove injuries, poor suit fit, field training, specific EVA tasks/design of task, boots/ankle injuries, falls from heights, background radiation, repetitive contact, and ambulation/long-distance ambulation. Mitigation steps have also been determined for each of the top risks. The IMEA and documentation of top risks is a living document. Yearly meetings are planned to update the analysis and reevaluate top risks and mitigations. The IMEA is being used to drive work in suited injury, and this work will continue to evolve with IMEA and lunar mission updates.

Teresa Reiber↗

NASA NTRSDate not supplied

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

Tessa Reiber↗

DOE OSTI2025

Size-resolved process understanding of stratospheric sulfate aerosol following the Pinatubo eruption

Stratospheric sulfate aerosol produced by volcanic eruptions plays important roles in atmospheric chemistry and the global radiative balance of the atmosphere. The simulation of stratospheric sulfate concentrations and optical properties is highly dependent on the chemistry scheme and microphysical treatment. In this work, we implemented a sophisticated gas-phase chemistry scheme (full chemistry, FC) and a 5-mode version of the Modal Aerosol Module with Prognostic Stratospheric Aerosol (MAM5-PSA) for the interactive treatment of stratospheric sulfate aerosol in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2) model to better simulate the chemistry-aerosol feedback following the Pinatubo eruption, and to compare it against a simulation using simplified chemistry (SC) and the default 4-mode version of the Modal Aerosol Module (MAM4). MAM5-PSA experiments were found to better capture the stratospheric sulfate burden from the eruption of the volcano to the end of 1992 as compared to the High-resolution Infrared Sounder (HIRS) observations, and the formation of sulfate in MAM5-PSA with FC (with an additional OH replenishment reaction) was significantly faster than in MAM4 with FC. Analyses of microphysical processes indicate that more sulfate aerosol mass was generated in total in FC experiments than in SC experiments. MAM5-PSA performs better than MAM4 in simulation of aerosol optical depth (AOD); AOD anomalies from the MAM5-PSA experiment have better agreement with observations. The simulated largest changes in global mean net radiative flux at the top of the atmosphere following the eruption were about −3 W m −2 in MAM5-PSA experiments and roughly −1.5 W m −2 in MAM4 experiments.

AEROSOL↗

NASA NTRSDate not supplied

Illuminating Albedo: Using MOSAiC Data to Assess the CERES Cloud Radiative Swath (CRS) Albedo Quantification Process

Increasing surface and lower tropospheric air temperatures as a result of rising greenhouse gases are expected to be most pronounced over the Arctic. Such rapid changes alter the surface climate of the region, and impacts can be observed atmospherically, oceanographically, and biogeophysically. Accurately quantifying the impact of decreasing surface albedo on the surface energy budget with satellite observations alone is complicated by a lack of shortwave radiation during winter and seasonal/spatial heterogeneity of surface type and associated spectral albedo. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project features the Cloud Radiative Swath (CRS) product, which builds upon the Single Scanner Footprint (SSF) product by using the NASA Langley Fu-Liou radiative transfer model to calculate a robust and high-quality array of surface and atmospheric radiative fluxes on an instantaneous, footprint-level scale. This study aims to use MOSAiC and CRS data to illuminate potential uncertainties in the CERES albedo production process, with goals of determining 1) spectral albedo under clear sky conditions when stratified by ice concentration, 2) the uncertainty associated with CERES surface albedo “history maps” when compared against observations captured during MOSAiC, and 3) the magnitude of variation between meteorological inputs compared to those from MOSAiC.

Emily Monroe↗