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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Snow ALbedo eVOlution (SALVO) Campaign Broadband Albedo from April - June, 2024 in Utqiagivk, AK level a1

A field-portable broadband (285 – 2800 nm) albedometer was used to make spatially distributed albedo measurements on tundra and sea ice surfaces. The albedometer consists of paired upward-looking and downward-looking pyranometers, which were both connected to a data logger. The instrument was mounted approximately 1 m above the surface using a tripod and was placed on a 1.4 m-long boom to minimize the impacts of shading from the operator and to observe surfaces undisturbed by footprints (see Appendix for photos of measurement setup and uncertainty assessment). Albedo measurements were taken parallel to the 200-m albedo lines at 5-m increments (41 measurements) ~1.2 m south of the line. On the operator’s end of the boom, there was a bubble level that was aligned with the bubble level on the upward-looking pyranometer. To take a measurement, the operator first relocated the tripod to the measurement location, then leveled the instrument and held it level for at least twice the pyranometers’ response time (5 or 15 seconds, see below), and finally depressed a trigger on the data logger. The data logger recorded the instantaneous voltage on both pyranometers, the measurement number, and the time. The data logger also converted the voltages to irradiances, and from these computed the ratio (outgoing/incoming) for albedo, which could be checked in the field. The operator recorded in a field notebook the measurement number that corresponded with the locations on the line and any pertinent notes (e.g., invalid measurements). With this setup, a trained operator could measure a 200-m albedo line (41 measurements) in approximately 30 minutes. Measurements were made within 3 hours of solar noon. The data logger had sufficient storage capacity to record all measurements from the campaign, but data were downloaded to a computer after each measurement day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Snow ALbedo eVOlution (SALVO) Campaign Spectral Albedo and Related Measurements from April - June, 2024 in Utqiagivk, AK

A field-portable spectroradiometer, referred to herein as an ‘ASD’, was used to make spatially-distributed spectral albedo (350 – 2500 nm) measurements on tundra and sea ice surfaces. The ASD detector is carried in a backpack and controlled via a computer mounted on the front of the operator (see Figure 1). The ASD measures the spectral irradiance from a fiber optic cable that is routed from the backpack to a custom, gooseneck cosine collector mounted on the end of a 1-m long boom (Grenfell and Perovich, 2008). The boom was held at hip height (approximately 1 m) and had an integrated bubble level for levelling. To make an albedo measurement, first the operator collect an incident (down-welling) irradiance, followed by a reflected (up-welling) measurement. The time between incident and reflected measurements was typically between 11 and 26 seconds (interquartile range). For each measurement, 10 spectra are averaged together. Albedo is calculated as the ratio of the reflected to incident measurement, which obviates the need for absolute radiometric calibration. Albedo measurements were taken parallel to the 200-m albedo lines at 5-m increments (41 measurements) ~1 m south of the line. While the ASD operator was making measurements, an assistant kept notes on the scan number associated with each measurement, the surface type (see below), and collected photos of each measurement (see companion oblique photos data archive). Measurements were made within 3 hours of solar noon.

ASD Spectroradiometer↗
DOE OSTI2021

Albedo Measurement of the Terra Pave White Albedo Product: Cooperative Research and Development Final Report

The Terra Pave team is creating an eco-friendly, cost-effective road coating that controls dust and dirt on high-traffic roads near solar field installations to reduce the dirt cover on panels, which lowers energy output. The Terra Pave White Albedo product also has the capability to increase the amount of solar radiation reflected from the ground to the backside of bifacial PV modules, thereby increasing the amount of electricity generated. This work will quantify the amount of solar radiation reflected from the Terra Pave White albedo product by measuring its albedo, which is the ratio of the reflected radiation to the incoming radiation. Albedo is measured with two horizontal pyranometers with one ground-facing and the other sky-facing.

14 SOLAR ENERGY↗
DOE OSTI2024

Conceptual Design of Passive Neutron Albedo Reactivity and Active Neutron Albedo Reactivity Instruments for Various Arrangements of Pebble Bed Reactor Pebbles

MCNP6 simulations were performed to assess the anticipated capability of the Passive Neutron Albedo Reactivity technique for nuclear safeguards measurements of irradiated pebble/pebbles. Two physical setups were examined. One with a single pebble of three different burnups and one with 27 pebbles in a cube. For all cases the sensitivity to removing all the fissile material was examined. For both of the physical setups, 4 assay cases were examined: (a) singles count rates for which the only source neutrons were the inherent neutrons in the fuel, (b) singles count rates again except this time two relatively weak AmLi sources were placed above and below the top central pebble and the combined effect of both neutron source terms were examined, (c) doubles count rates for which the only source neutrons were the inherent neutrons in the fuel, and (d) doubles count rates again except this time two relatively weak AmLi sources were placed above and below the top central pebble and the combined effect of both neutron source terms were examined. Finally, a few parameters such as Cd near the 3 He tubes were perturbed to see if the results could be improved.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Projecting Stratocumulus Transitions on the Albedo—Cloud Fraction Relationship Reveals Linearity of Albedo to Droplet Concentrations

Satellite images show solid marine stratocumulus cloud decks (Sc) that break up over the remote oceans. The Sc breakup is initiated by precipitation and is accompanied by a strong reduction in the cloud radiative effect. Aerosol has been shown to delay the Sc breakup by postponing the onset of precipitation, however its climatic effect is uncertain. Here we introduce a new approach that allows us to re-cast currently observed cloud cover and albedo to their counterfactual cleaner world, enabling the first estimate of the radiative effect due to delayed cloud breakup. Using simple radiative approximation, the radiative forcing with respect to pre-industrial times due to delayed Sc breakup is –0.39 W m –2 . The radiative effect changes nearly linearly with aerosol due to the droplet concentration control on the cloud cover, suggesting a potentially accelerated warming if the current trend of reduction in aerosol emissions continues.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Estimating Fine-Resolution Shortwave Broadband Albedo of Croplands from Harmonized Landsat and Sentinel-2 Data

Altered surface albedo due to land-cover conversions and management is a significant driver of global climate change. Albedo can be directly measured at ground stations, and remote sensing data can be used to scale-up albedo values to regional and global levels. Some previous studies have retrieved fine-resolution (10–30 m) instantaneous albedo and coarse-resolution (500–1000 m) daily mean albedo from remote sensing data, but they all required the input of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo information at 500-m resolution, and none have assembled both instantaneous and daily albedo based exclusively on fine-resolution satellite data. Here, to address this issue, we compiled 387 instantaneous and 346 daily albedo records using field net radiometer measurements from the bioenergy croplands at the W. K. Kellogg Biological Station in southwest Michigan. We then connected these albedo records with a suite of variables derived from harmonized Landsat and Sentinel-2 data through two machine learning algorithms (random forest regression and extreme gradient boosting) to retrieve clear-sky instantaneous and daily shortwave broadband albedo. The performance statistics indicate reasonable accuracy of model results [root-mean-square error (RMSE)] around or below 0.03 except for snow-covered surfaces), suggesting that the retrieval of both instantaneous and daily albedo based exclusively on fine-resolution satellite data is promising. To facilitate the use of fine-resolution albedo products at the global level, future efforts need to include more albedo records of diverse surface cover types, as well as to accurately model daily albedo for cloudy days to address the “clear-sky bias.”

Harmonized Landsat and Sentinel-2↗
DOE OSTI2022

Evaluation and Optimization of Snow Albedo Scheme in Noah-MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies

The Biosphere-Atmosphere Transfer Scheme (BATS) ground snow albedo algorithm is commonly used in land-surface models (LSM), weather forecasting and research applications. This study addresses key uncertainties in BATS simulated ground snow albedo within the Noah-MP LSM framework through evaluation and optimization of the Noah-MP BATS ground snow albedo formulation using 2-band (visible and near-infrared (NIR)) in situ albedo observations at Rocky Mountain field stations. The Noah-MP BATS ground snow albedo scheme is extremely sensitive to its input parameters. Namely, an ensemble generated by varying BATS input parameters within potentially plausible ranges provides an average daily range (maximum ensemble member minus minimum ensemble member) of ground snow albedo exceeding 0.45 in visible and NIR bands. Parameter optimization improves agreement between simulated and in situ observed ground snow albedo in visible, NIR and broadband spectrums. Importantly, optimized parameters result in reduced biases relative to observed fresh-snow albedo and better agreement with observed albedo decay. Our analysis across different sites supports that the optimized BATS ground snow albedo parameters are appropriate to transfer in space and time, at least within the region studied (the central-southern Rocky Mountains). The primary error source remaining after parameter optimization is that observed fresh-snow albedo is highly variable, particularly in the NIR spectrum, whereas BATS fresh-snow albedo is constant, an issue which requires further investigation. This study shows significant correlations between observed fresh-snow albedo and surface meteorological conditions (e.g., downward shortwave radiation and temperature) which can support future model development that attempts to include a time-varying formulation for fresh-snow albedo.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Measured and satellite-derived albedo data for estimating bifacial photovoltaic system performance

The albedo of the ground surface is an important factor in the cost-effectiveness of a bifacial photovoltaic (PV) system. To improve the availability of reliable albedo data, datasets of ground albedo and associated meteorological data were developed by using existing measurement network data and data measured by the PV industry. The measured datasets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Satellite-derived values of albedo are available from the National Solar Radiation Data Base (NSRDB). The NSRDB albedos were compared to the measured albedos for Surface Radiation budget (SURFRAD) network locations for the period 2001–2017, and the mean bias difference results were from -0.044 to +0.056. Overall, these differences are greater than the albedo measurement uncertainty of ±0.02; consequently, the NSRDB albedos should be used with caution for estimating the performance of bifacial PV systems. Differences between SURFRAD and NSRDB albedos are attributed to the NSRDB method for determining albedo and to the ground surfaces within the NSRDB 4 km spatial resolution pixel consisting of a mixture of surface types rather than just the single surface types viewed by the albedometers at the SURFRAD stations.

14 SOLAR ENERGY↗
DOE OSTI2021

Surface albedo spatial variability in North America: Gridded data vs. local measurements

Considering the current booming interest for the large-scale deployment of bifacial photovoltaic modules, the solar industry now requires accurate estimates of broadband surface albedo at high spatial resolution. In this context, the present study evaluates the adequacy and performance over North America of two Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo products (at 500-m and 1-km resolution) and the National Solar Radiation Database (NSRDB) product at 4-km resolution. Two variations of the 500-m MODIS product are also considered: black-sky albedo and all-sky albedo. Albedo observations from 36 radiometric stations during 2011–2015 are analyzed while considering the apparent homogeneity of the surface characteristics over the 4x4 km NSRDB pixel in which they are located. Even at sites where the albedo around the station has been found “homogeneous” in the literature, marked differences are found between the daily observations and the gridded estimates at any spatial resolution. Furthermore, differences in seasonal behavior and between the three different albedo types also impact the accuracy of the albedo estimates, with overtones caused by local specificities and inhomogeneities. All this precludes the desirable evaluation of the local albedo at a specific site of relatively small size compared to its corresponding 4x4-km pixel if only the mean albedo over that pixel is known. Significant discrepancies are also found at snow-impacted sites, most importantly in the case of the NSRDB albedo estimates, which are typically much too high.

14 SOLAR ENERGY↗
DOE OSTI2025

Fine-scale vegetation composition and structure shape spatiotemporal variation in surface albedo across a low Arctic tundra landscape

The unprecedented rate of warming in the Arctic is driving changes in the structure and composition of tundra vegetation. Increases in deciduous tall shrub cover, height, and density are of particular concern, as these changes alter local surface albedo in ways that could amplify effects on the regional surface energy budget (SEB). Despite this importance, significant uncertainties remain in understanding the interplay between fine-scale vegetation patterns and emergent albedo dynamics across space and time. Here, we address these uncertainties by (1) quantifying spatiotemporal variation in surface shortwave albedo and (2) determining the relative influence of fine-scale vegetation composition, structure, and environmental conditions on albedo across a representative low-Arctic tundra landscape on Alaska’s Seward Peninsula. To do this, we synthesized multi-scale, multi-platform remote sensing observations, including a novel Landsat-derived albedo time series, a fine-scale map of Arctic plant functional type (PFT) fractional cover, and airborne LiDAR estimates of canopy height and topography. We show that there are substantial reductions in winter albedo for pixels dominated by tall, woody PFTs (28.13%) relative to pixels dominated by non-woody vegetation, but almost no change in summer albedo (3% increase). Further, we identified a unimodal trend in the relationship between canopy height and the timing of the springtime transition from high (snowy) to low (leafy) albedo (peak at 5.5 m), possibly because of competing ‘snow-fence’ and ‘protrusion’ snow-shrub interactions. To explore the primary drivers of albedo, we constructed a random forest model and found that canopy height and the fractional cover of woody PFTs were as- or more important predictors of winter albedo than topographic features. These findings provide strong evidence for the impacts of local vegetation characteristics on regional surface albedo, highlighting the need for better quantification of snow-shrub interactions to accurately predict the Arctic’s SEB under future environmental change.

Arctic↗
DOE OSTI2022

Arctic sea ice albedo: Spectral composition, spatial heterogeneity, and temporal evolution observed during the MOSAiC drift

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Presenting a Model to Predict Changing Snow Albedo for Improving Photovoltaic Performance Simulation

As photovoltaic (PV) deployment increases worldwide, PV systems are being installed more frequently in locations that experience snow cover. The higher albedo of snow, relative to the ground, increases the performance of PV systems in northern and high-altitude locations by reflecting more light onto the PV modules. Accurate modeling of the snow’s albedo can improve estimates of PV system production. Typical modeling of snow albedo uses a simple two-value model that sets the albedo high when snow is present, and low when snow is not present. However, snow albedo changes over time as snow settles and melts and a binary model does not account for transitional changes, which can be significant. Here, we present and validate a model for estimating snow albedo as it changes over time. The model is simple enough to only require daily snow depth and hourly average temperature data, but can be improved through the addition of site-specific factors, when available. We validate this model to quantify its ability to more accurately predict snow albedo and compare the model’s performance against satellite imagery-based methods for obtaining historical albedo data. In addition, we perform modeling using the System Advisor Model (SAM) to show the impact of changes in albedo on energy modeling for PV systems. Overall, our albedo model has a significantly improved ability to predict the solar insolation on PV modules in real time, especially on bifacial PV modules where reflected irradiance plays a larger role in energy production.

Pike, Christopher (ORCID:0000000155888033)↗
DOE OSTI2022

SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice

Abstract. Accurate modeling of cryospheric surface albedo is essential for our understanding of climate change as snow and ice surfaces regulate the global radiative budget and sea-level through their albedo and mass balance. Although significant progress has been made using physical principles to represent the dynamic albedo of snow, models of glacier ice albedo tend to be heavily parameterized and not explicitly connected with physical properties that govern albedo, such as the number and size of air bubbles, specific surface area (SSA), presence of abiotic and biotic light absorbing constituents (LACs), and characteristics of any overlying snow. Here, we introduce SNICAR-ADv4, an extension of the multi-layer two-stream delta-Eddington radiative transfer model with the adding–doubling solver that has been previously applied to represent snow and sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnel reflectance and transmittance between overlying snow and higher-density glacier ice, scattering by air bubbles of varying sizes, and numerous types of LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadband albedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03 for bare and bubble-free ice under direct light. Our results indicate that representing ice with a density of 650 kg m−3 as snow with no refractive Fresnel layer, as done previously, generally overestimates the BBA by an average of 0.058. However, because most naturally occurring ice surfaces are roughened “white ice”, we recommend modeling a thin snow layer over bare ice simulations. We find optimal agreement with measurements by representing cryospheric media with densities less than 650 kg m−3 as snow and larger-density media as bubbly ice with a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedo impacts from LACs with changing ice SSA, with peak impact per unit mass of LACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACs actually increase the albedo. SNICAR-ADv4 represents smooth transitions between snow, firn, and ice surfaces and accurately reproduces measured spectral albedos of a variety of glacier surfaces. This work paves the way for adapting SNICAR-ADv4 to be used in land ice model components of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Toward a more realistic representation of surface albedo in NASA CERES-derived surface radiative fluxes

Accurate multidecadal radiative flux records are vital to understand Arctic amplification and constrain climate model uncertainties. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. The year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes was conducted using in situ measurements from MOSAiC flux stations. The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by +11.40 Wm –2 and underestimates the upwelling shortwave flux by –15.70 Wm –2 and downwelling longwave fluxes by –12.58 Wm –2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0°C). The biases in downwelling shortwave and longwave fluxes suggest that the atmosphere represented in CERES is too optically thin. The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. Additionally, the results show that the spectral surface albedo used in SYN1deg overestimates albedo in visible and mid-infrared bands. A series of radiative transfer model perturbation experiments are performed to quantify the factors contributing to the differences. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm –2 ) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm –2 ). In addition, the differences between perturbation experiments using hourly and monthly MOSAiC surface albedo suggest that approximately 25% of the sea ice surface albedo variability is explained by factors not correlated with daily sea ice concentration variability. Biases in net shortwave and longwave flux can be reduced to less than half by adjusting both albedo and cloud inputs toward observed values. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influences of cloud vertical overlapping on the calculated cloud albedo and their validation with satellite observations

Cloud albedo is expected to influence cloud radiative forcing in addition to cloud fraction, and inadequate description of the cloud overlapping effects on the cloud fraction may influence the simulated cloud fraction, and thus the relative cloud radiative forcing (RCRF) and cloud albedo. In this study, we first present a new formula by extending that presented previously in Liu et al. (2011) to consider multilayer clouds directly in the relationship between cloud albedo, cloud fraction and RCRF, and then quantitatively evaluate the effects of different cloud vertical overlapping structures, represented by the decorrelation length scales (L cf ), on the simulated cloud albedos. We use the BCC_AGCM2.0_CUACE/Aero model with simultaneous validation by observations from the Clouds and the Earth's Radiation Energy System (CERES) satellite. When L cf < 4 km (i.e., the cloud overlap is closer to the random overlap), the simulated cloud albedos are generally in good agreement with the satellite-based albedos for December– February and June–August; when L cf ≥ 4 km (i.e., the cloud vertical overlap is closer to the maximum overlap), the difference between simulated and observed cloud albedos became larger, due mainly to significant differences in cloud fractions and RCRF. Further quantitative analysis shows that the relative Euclidean distance, which represents the degree of overall model–observation disagreement, increases with the L cf for all three variables (cloud albedo, cloud fraction and RCRF), indicating the importance of cloud vertical overlapping in determining the accuracy of the calculated cloud albedo for multilayer clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Surface and Atmospheric Heating Responses to Spectrally Resolved Albedo of Frozen and Liquid Water Surfaces

Abstract Multiple Earth system models (ESMs) discretize surface albedo into two semi‐broadbands comprising the UV/visible and near‐infrared (NIR) wavelengths. Here, we use an offline single‐column radiative transfer model to investigate the radiative effects of spectrally resolving the surface albedo. We use the Snow, Ice, and Aerosol Radiative model, extended to simulate liquid water, to calculate snow, ice, and liquid water albedo. We flux‐weight the hyperspectral albedo into the coarser spectral bands used by the atmospheric shortwave radiative transfer model. We establish representative atmospheric profiles for the three surface types and compare their shortwave fluxes and atmospheric warming rates with the spectrally resolved albedo to those calculated with the semi‐broadband approximation. Spectrally resolved surface albedo over snow and ice reduces atmospheric warming by darkening the albedo of NIR bands, correcting the too‐strong surface absorption in visible bands, and too‐weak surface absorption in shortwave infrared bands caused by the semi‐broadband approximation. We explore the effects on surface and atmospheric warming rates of varying solar zenith angle, cloud cover, relative humidity, and snow grain/air bubble radii. The semi‐broadband albedo biases can exceed 10% and 2% for the surface and atmospheric net flux respectively, being particularly strong under conditions which alter the distributions of surface insolation (i.e., cloud cover or increased atmospheric water vapor). These results show that transmitting a higher resolution spectral radiation field between the atmosphere and surface reduces biases in surface absorption and atmospheric heating present in ESMs that currently use the semi‐broadband approximation.

54 ENVIRONMENTAL SCIENCES↗