Surface Albedo Research Articles

A method for constructing directional surface wave spectra from ICESat-2 altimetry

Abstract. Sea ice is important for Earth's energy budget as it influences surface albedo and air–sea fluxes in polar regions. On its margins, waves heavily impact sea ice. Routine and repeat observations of waves in sea ice are currently lacking, and therefore a comprehensive understanding of how waves interact with sea ice and are attenuated by it is elusive. In this paper, we develop methods to separate the two-dimensional (2D) surface wave spectra from sea-ice height observations made by the ICESat-2 (IS2) laser altimeter, a polar-orbiting satellite. A combination of a linear inverse method, called generalized Fourier transform (GFT), to estimate the wave spectra along each beam and a Metropolis–Hastings (MH) algorithm to estimate the dominant wave's incident angle was developed. It allows us to estimate the 2D wave signal and its uncertainty from the high-density, unstructured ATL03 ICESat-2 photon retrievals. The GFT is applied to re-binned photon retrievals on 25 km segments for all six beams and outperforms a discrete Fourier transform (DFT) in accuracy while having fewer constraints on the data structure. The MH algorithm infers wave direction from beam pairs every 25 km using coherent crests of the most energetic waves. Assuming a dominant incident angle, both methods together allow a decomposition into 2D surface wave spectra with the advantage that the residual surface heights can potentially be attributed to other sea-ice properties. The combined GFT–MH method shows promise in routinely isolating waves propagating through sea ice in ICESat-2 data. We demonstrate its ability on a set of example ICESat-2 tracks, suggesting a detailed comparison against in situ data is necessary to understand the quality of retrieved spectra.

Supercooled liquid water clouds observed over Dome C, Antarctica: temperature sensitivity and cloud radiative forcing

Abstract. Clouds affect the Earth climate with an impact that depends on the cloud nature (solid and/or liquid water). Although the Antarctic climate is changing rapidly, cloud observations are sparse over Antarctica due to few ground stations and satellite observations. The Concordia station is located on the eastern Antarctic Plateau (75∘ S, 123∘ E; 3233 m above mean sea level), one of the driest and coldest places on Earth. We used observations of clouds, temperature, liquid water, and surface irradiance performed at Concordia during four austral summers (December 2018–2021) to analyse the link between liquid water and temperature and its impact on surface irradiance in the presence of supercooled liquid water (liquid water for temperature less than 0 ∘C) clouds (SLWCs). Our analysis shows that, within SLWCs, temperature logarithmically increases from −36.0 to −16.0 ∘C when liquid water path increases from 1.0 to 14.0 g m−2. The SLWC radiative forcing is positive and logarithmically increases from 0.0 to 70.0 W m−2 when liquid water path increases from 1.2 to 3.5 g m−2. This is mainly due to the downward longwave component that logarithmically increases from 0 to 90 W m−2 when liquid water path increases from 1.0 to 3.5 g m−2. The attenuation of shortwave incoming irradiance (that can reach more than 100 W m−2) is almost compensated for by the upward shortwave irradiance because of high values of surface albedo. Based on our study, we can extrapolate that, over the Antarctic continent, SLWCs have a maximum radiative forcing that is rather weak over the eastern Antarctic Plateau (0 to 7 W m−2) but 3 to 5 times larger over West Antarctica (0 to 40 W m−2), maximizing in summer and over the Antarctic Peninsula.

Retrieving land surface reflectance anisotropy with Sentinel-3 observations and prior BRDF model constraints

Sentinel-3 supports governmental policies and European programmes such as the Copernicus Global Land Service with daily monitoring of the land surface by measuring the Earth's surface with its multi-band wide-swath visible and near-infrared radiometers. To fully exploit Sentinel-3 data sets, performing a correction of directional effects caused by the land surface reflectance anisotropy properties is mandatory. This correction requires first an estimation of the bidirectional reflectance distribution function (BRDF) to be properly achieved. The quality and robustness of global estimates of key land surface variables derived from space-borne sensors depend clearly on an accurate assessment of the spectral BRDF.Here, we present an algorithm aiming at harnessing the Sentinel-3's wide imaging swath to retrieve the land surface BRDF, approximating it via a kernel-driven semi-empirical model which can then be used to normalise the observations to a common Sun-sensor geometry. Our algorithm, named ReBeLS (Regularised BRDF inversion for Land Surface), uses a temporally regularised BRDF inversion approach and, together with prior knowledge of the land surface BRDF obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, assimilates Sentinel-3 surface reflectance observations. We focus on the results derived from observations provided by the Sentinel-3 Ocean and Land Colour Instrument (OLCI) sensors; however, the algorithm can also be applied to reflectance observations acquired by the Sea and Land Surface Temperature Radiometer (SLSTR). The retrieved BRDF model parameters reproduce within uncertainties the directional signature as seen by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor. The generated Sentinel-3 normalised surface reflectance products are a significant advance compared with time series of directional surface reflectance and maximum value composite images, showing a statistically significant (p≪0.05) correlation (r>0.9) with VIIRS nadir BRDF-adjusted surface reflectance. Furthermore, the ReBeLS Sentinel-3 BRDF products offer enough flexibility to allow users to compute spectral surface albedos or to normalise surface reflectance to any Sun-sensor configuration.

A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products

Abstract. In situ measurements from sparsely distributed networks worldwide are a critical source of reference data for validating or correcting biases in satellite products. However, due to the substantial difference in spatial scales between in situ and satellite measurements, the two cannot be compared except for the fact that the underlying surface of in situ sites is absolutely homogeneous. Instead, the in situ measurements needed to be upscaled to be matched with the satellite pixels. Based on the upscaling model, we also proposed the consideration that in situ observation generally lacks spatial representativeness due to the widely distributed spatial heterogeneity, and we have developed a coarse pixel-scale ground “truth” dataset based on ground measurements of 416 in situ sites from the sparsely distributed observation networks. Furthermore, we thoroughly assessed the effectiveness of the dataset at sites with different degrees of spatial representativeness. The results demonstrate that using this dataset in validation outperforms the direct comparison between satellite and in situ site measurements over heterogeneous surfaces when in situ measurement footprints are less than satellite pixel size. The accuracy of the reference data employed for validation or bias correction can be boosted by 17.09 % over the regions with strong spatial heterogeneity. However, the degree of improvement with this dataset displays a decreasing trend with the reduction in spatial heterogeneity. At a global scale, the pixel-scale ground “truth” dataset enhances the accuracy of pixel-scale reference data in general, with the overall relative root-mean-square error (RRMSE) decreasing by 6.04 % compared to in situ single-site measurements. Our results suggest that in situ single-site measurements are limited in their ability to capture surface spatial variability information at a coarse pixel scale (i.e., the kilometer scale). The dataset we provided, which merges temporal information from ground-based observations and spatial information from high-resolution data, represents a valuable resource for validating and correcting worldwide surface albedo products over heterogeneous surfaces. To the best of our knowledge, this dataset is unique in providing a coarse pixel-scale ground “truth” with the widest spatial distribution and longest time series. The dataset is publicly available through https://doi.org/10.5281/zenodo.8008454 (Pan et al., 2023).

Photosynthetically active radiation separation model for high-latitude regions in agrivoltaic systems modeling

Photosynthetically active radiation is a key parameter for determining crop yield. Separating photosynthetically active radiation into direct and diffuse components is significant to agrivoltaic systems. The varying shading conditions caused by the solar panels produce a higher contribution of diffuse irradiance reaching the crops. This study introduces a new separation model capable of accurately estimating the diffuse component from the global photosynthetically active radiation and conveniently retrievable meteorological parameters. The model modifies one of the highest-performing separation models for broadband irradiance, namely, the Yang2 model. Four new predictors are added: atmospheric optical thickness, vapor pressure deficit, aerosol optical depth, and surface albedo. The proposed model has been calibrated, tested, and validated at three sites in Sweden with latitudes above 58 °N, outperforming four other models in all examined locations, with R2 values greater than 0.90. The applicability of the developed model is demonstrated using data retrieved from Sweden's first agrivoltaic system. A variety of data availability cases representative of current and future agrivoltaic systems is tested. If on-site measurements of diffuse photosynthetically active radiation are not available, the model calibrated based on nearby stations can be a suitable first approximation, obtaining an R2 of 0.89. Utilizing predictor values derived from satellite data is an alternative method, but the spatial resolution must be considered cautiously as the R2 dropped to 0.73.

Efficiency Evaluation of Evacuated Solar Tube Collectors in Sakha Republic (Yakutia)

Calculations of solar radiation incident on an inclined surface were performed considering the installation location, local time, azimuth angle, tilt angle, atmospheric transparency coefficient and surface albedo. The calculations were based on long-term meteorological observation archives. The accuracy of the solar radiation calculations for the inclined surface was verified. A comparative analysis was conducted between the calculation results carried out for the installation location, tilt angle, and azimuth angle of the experimental setup and pyranometer measurements. Thermal energy production by evacuated solar tube collectors was also calculated. These calculations were performed on an hourly basis, taking into account the total solar radiation falling on the inclined surface and the atmospheric air temperature. The calculated values were compared with experimental data obtained from an ultrasonic heat meter. The payback period of solar heating systems for various locations was used as an efficiency indicator for the solar collectors. The article estimated the payback period for Verkhoyansk town in the Sakha Republic (Yakutia). Economic efficiency strongly depends on the installation location of the solar collector and the thermal energy tariff at the installation site.

Assessing the accuracy of spectral indices obtained from Sentinel images using field research to estimate land degradation.

Wind erosion resulting from soil degradation is a significant problem in Iran's Baluchistan region. This study evaluated the accuracy of remote sensing models in assessing degradation severity through field studies. Sentinel-2 Multispectral Imager's (MSI) Level-1C satellite data was used to map Rutak's degradation severity in Saravan. The relationship between surface albedo and spectral indices (NDVI, SAVI, MSAVI, BSI, TGSI) was assessed. Linear regression establishes correlations between the albedo and each index, producing a degradation severity map categorized into five classes based on albedo and spectral indices. Accuracy was tested with 100 ground control points and field observations. The Mann-Whitney U-Test compares remote sensing models with field data. Results showed no significant difference (P > 0.05) between NDVI, SAVI, and MSAVI models with field data, while BSI and TGSI models exhibited significant differences (P ≤ 0.001). The best model, BSI-NDVI, achieves a regression coefficient of 0.86. This study demonstrates the advantage of remote sensing technology for mapping and monitoring degraded areas, providing valuable insights into land degradation assessment in Baluchistan. By accurately identifying severity levels, informed interventions can be implemented to mitigate wind erosion and combat soil degradation in the region.

Balanço de Radiação sobre água de Baixa Turbidez Purificada Artificialmente para Irrigação de Fumo Cultivado sob Sombreamento. II. Análise do Albedo da água e Modelagem da Radiação Líquida

Abstract The albedo of a water surface and the energy available for evaporation are strongly correlated and studying such processes is of paramount importance for water security at farm and regional levels. In this paper, water albedo (αw) and net all-wave radiation (Rn) were analyzed after being measured above the surface of an artificially cleaned and low-turbidity water used for tobacco irrigation. It was observed that αw decreased as the sun elevation (θ) increased, especially for clear and near clear skies. The results showed that αw can be reasonably predicted with a power law model either in terms of θ or Sg (incoming solar radiation) across different cloud cover conditions. From this study, a mean daily albedo of 0.05 is recommended. Three approaches were considered for estimation of daily Rn. In the first, a linear regression model strongly fitted Rn data in terms of Sg solely. The second option based on the definition of Rn was [0.95Sg - Lnet(56)], where Lnet(56) is net longwave (LW) radiation as used in the FAO56 model for reference evapotranspiration estimation, and the third was [0.95Sg - Lnet(MLR)], where MLR stands for multiple linear regression. The disadvantages of approaches (1) and (3), based on regressions, is that they are constrained to the type of water stored in the farm and the climatic conditions of the region. The performance of approach (2), where Lnet(56) is a widely used model, was comparable to the others can potentially be improved with a site-specific calibration. All three approaches for estimating daily Rn proposed in this study can possibily be extended to clear water that did not go through any filtration process.

Влияние метеофакторов на среднесуточную интенсивность городского острова тепла Екатеринбурга

Urban heat island (UHI) intensity in the surface air temperature field is equal to the difference between temperatures (averaged for the period under consideration) in the city and in the immediate rural surroundings. Using multi-regression analysis, We investigated the meteorological factors determining the mean daily UHI intensity based on observational data at weather stations in Yekaterinburg and the village of Verkhneye Dubrovo in 2020–2022. The average value of an UHI intensity in May-September equals to 0.94 °C with a standard deviation of daily mean values of 0.71 °C. The multiple linear regression model includes the difference in the relative humidity of the atmosphere in the city and the village, the weather factor determined by wind speed and cloudiness, and atmospheric pressure. This “summer” model describes 60 % of the observed UHI variance. In December-March, the average UHI intensity equals to 0.81 °C with a standard deviation of mean daily values of 0.82 °C. The regression model includes only the weather factor explaining 27 % of the UHI variability. It is concluded that the UHI intensity in Yekaterinburg is primarily determined by solar radiation and various properties of urban and rural surfaces (albedo, emissivity, thermal properties of soils). They determine the maximal UHI intensity that is realized only in “ideal” weather (weather factor ~1). Deviations from “ideal” conditions described by meteorological factors only reduce the maximal UHI intensity. In winter, heat leaks from buildings and heating networks weakly dependent on the meteorological factors make an additional contribution to the UHI intensity.

Comparing Atmospheric Temperature Fluctuations Across Landed Missions

AbstractWe analyze and compare atmospheric temperature data from three landed missions: Mars Science Laboratory (MSL) Curiosity rover, Phoenix lander, and Pathfinder lander. Pathfinder and Phoenix were lander missions that operated for 84 and 151 sols, respectively. MSL Curiosity is a rover that operates on the surface of Mars. It has recorded air temperature for more than five Mars Years (MY). We denoise and detrend temperature data from each mission and use those results to calculate variance in air temperature as a diagnostic for atmospheric variability at the surface. The results show a consistent seasonal pattern in MSL air temperature variance with little interannual variability outside major dust storms. The global dust storm in MY 34 was accompanied by a decrease in temperature variance and a muted response in peak MY 35 variance the following year. Phoenix (68°N, 2 m measurement height) and Pathfinder (19.7°N, 1.1 m measurement height) air temperatures have larger variance than air temperature from environmental data records at the MSL location (5.4°S, 1.6 m measurement height) at its equatorial latitude. Pathfinder variances per sol are larger than those of Phoenix, possibly due to a combination of Pathfinder's lower albedo surface and lower latitude. This occurs despite the Pathfinder location's higher thermal inertia, which would act to decrease noontime variance relative to a lower thermal inertia surface. Comparison of MSL temperature variance to pressure drops related to convective vortex activity shows consistent seasonal patterns; however, pressure drops tend to increase with increasing rover elevation, while variance remains consistent.

青藏高原色林错2000–2021年湖冰数据集

Lake ice is a sensitive indicator of climate change. Research on the response mechanism between lake ice and climate offer valuable insights into the mechanisms driving global climate change and enhance our ability to predict climate patterns. Using the Landsat surface albedo products, we delineated the boundaries of Lake Selin Co from 2000 to 2021; and by leveraging the MODIS Terra surface reflectance data with a 250 m resolution and daily revisit time, we generated a dataset of lake ice distribution in Lake Selin Co from 2000 to 2021. We selected the results of the freezing period and the complete freezing period respectively, compared them with the visual results to perform accuracy verification and calculate the confusion matrix. The overall accuracy of the user reached 94%, and the Kappa coefficient exceeded 0.89. Continuous monitoring data for lake ice phenology in Selin Co are of great significance for tracking climate change, which help fill gaps in measured data and provide valuable support for related research.

A novel methodology for calculating the aerosol direct radiative effect using a non-uniform five-dimensional lookup table

ABSTRACT The quantification of aerosol direct radiative effects (ADREs) under clear sky conditions is essential for understanding the influence of aerosols on climate. This paper introduces a novel approach, the non-uniform five-dimensional lookup table (NU-5D-LUT) method, for calculating the ADREs under clear sky conditions. The NU-5D-LUT method considers key parameters such as aerosol optical thickness, single scattering albedo, asymmetry factor, surface albedo, and solar zenith angle. Validation against the SBDART model shows strong agreement, with correlation coefficients of 0.97 and 0.99 for TOA and BOA ADREs, respectively. Global comparisons demonstrate consistent ADRE distributions, with relative errors below 5.8% for TOA ADRE and 4.4% for BOA ADRE. The NU-5D-LUT method significantly reduces computation time, offering a practical solution for large-scale simulations and climate model evaluations in aerosol research.

Validation of Two Newly Developed Albedo Schemes Based on the Observations Over the Region With Evergreen Broadleaved Forest in Southern China

AbstractExisting land surface models still have large error in the simulation of surface albedo. At present, introducing the influence of meteorological factors into the albedo parameterization scheme is an effective way to improve the albedo simulation. However, the improvement of the vegetation canopy surface albedo parameterization scheme is still insufficient. Therefore, based on the radiation and meteorological observation data during 1 November 2015–30 April 2018 from a land‐atmosphere interaction observation tower in a typical secondary evergreen broadleaved forest in Southern China, this study firstly analyzed the influencing factors of canopy surface albedo. It was found that the solar elevation angle and air relative humidity are two key factors influencing the canopy surface albedo, and the impact of the solar elevation angle on canopy surface albedo is not exactly the same on diurnal and seasonal scales. Then, two new canopy surface albedo parameterization schemes of additive form and multiplicative form were proposed and introduced into CLM5 model for single point simulation. Results show that the adoption of newly developed canopy surface albedo parameterization schemes can improve the simulation of diurnal and seasonal variations of albedo and reduce the overestimation of the simulation of near‐infrared radiation albedo and visible radiation albedo in the CLM5 model, then significantly reduce the root mean square errors of reflected solar radiation and net radiation simulation.

MPPT Strategy of Waterborne Bifacial Photovoltaic Power Generation System Based on Economic Model Predictive Control

At present, the new energy industry represented by photovoltaics has become the main force to realize the optimization of China’s energy structure and the goal of “double carbon”; with the absence of land resources, the waterborne bifacial photovoltaic has ushered in a new opportunity. Therefore, in order to address the problem that the maximum power point tracking (MPPT) of photovoltaics (PV) could not take into account, the dynamic economic performance in the control process, an economic model predictive control (EMPC), is proposed in this work to realize the MPPT of the waterborne bifacial PV power generation system. Firstly, the model of the bifacial PV module is constructed by combining the ray-tracing irradiance model and considering the effect of water surface albedo on the irradiance absorbed by the module. Secondly, the EMPC controller is designed based on the state-space model of the system to maximize the power generation as the economic performance index, and to solve the optimal input variables time by time to achieve a rolling optimization with the operational requirements of the system itself as the constraints. Thirdly, the MATLAB/Simulink (R2022a) simulation experimental results verify that the EMPC strategy could be utilized to achieve MPPT of the waterborne bifacial PV power generation system, according to the changes of environment. Finally, it is also demonstrated that the bifacial PV power generation system that employed the EMPC strategy outperformed the traditional MPPT algorithm, with respect to both output power tracking velocity and accuracy, and the power generation could be improved by about 6% to 14.5%, which significantly enhances the system’s dynamic process economics.

Spatial Estimation of Snow Water Equivalent for Glaciers and Seasonal Snow in Iceland Using Remote Sensing Snow Cover and Albedo

Efficient water resource management in glacier- and snow-dominated basins requires accurate estimates of the snow water equivalent (SWE) in late winter and spring and melt onset timing and intensity. To understand the high spatio-temporal variability of snow and glacier ablation, a spatially distributed energy balance model combining satellite-based retrievals of albedo and snow cover was applied. Incoming short-wave energy, contributing to daily estimates of melt energy, was constrained by remotely sensed surface albedo for snow-covered surfaces. Fractional snow cover was used for non-glaciated areas, as it provides estimates of snow cover for each pixel to better constrain snow melt. Thus, available daily estimates of melt energy in a given area were the product of the possible melt energy and the fractional snow cover of the area or pixel for non-glaciated areas. This provided daily estimates of melt water to determine seasonal snow and glacier ablation in Iceland for the period 2000–2019. Observations from snow pits on land and glacier summer mass balance were used for evaluation, and observations from land and glacier-based automatic weather stations were used to evaluate model inputs for the energy balance model. The results show that the interannual SWE variability was generally high both for seasonal snow and glaciers. For seasonal snow, the largest SWE (>1000 mm) was found in mountainous and alpine areas close to the coast, notably in the East- and Westfjords, Tröllaskaga, and in the vicinity of glacier margins. Lower SWE values were observed in the central highlands, flatter inland areas, and at lower elevations. For glaciers, more SWE (glacier ablation) was associated with lower glacier elevations while less melt was observed at higher elevations. For the impurity-rich bare-ice areas that are exposed annually, observed SWE was more than 3000 mm.

Remote sensing of ice albedo using harmonized Landsat and Sentinel 2 datasets: validation

ABSTRACT Albedo plays a key role in regulating the absorption of solar radiation within ice surfaces and hence strongly regulates the production of meltwater. A combination of Landsat and Sentinel 2 data provides the longest continuous medium resolution (10–30 m) earth surface observatory records. An albedo product (harmonized satellite albedo, hereafter HSA) has already been developed and validated for the Greenland Ice Sheet (GrIS), using harmonized Landsat 4–8 and Sentinel 2 datasets. In this paper, the HSA was validated for various Arctic and alpine glaciers and ice caps using in situ measurements. We determine the optimal spatial window size in point-to-pixel analysis, the best practices in evaluating remote sensing algorithms with groundtruth data, and cross sensor comparison of the Landsat 9 (L9) and Landsat 8 (L8) data. The impact of the spatial window size on measured ice surface homogeneity and albedo validation was analysed at both local and regional scales. Homogeneity statistics calculated from the grey-level co-occurrence matrix (GLCM) suggest that the ice surface becomes more homogeneous as the image resolution becomes coarser. The optimal spatial window size was found to be 90 m, based on maximizing the statistical and graphical measures while minimizing the root mean square error and bias. HSAs generally agree closely with in situ albedo measurements (e.g. Pearson’s R ranges from 0.68 to 0.92) across various Arctic and alpine glaciers and ice caps. Cross sensor differences between L9 and L8 are minor, and we suggest that no harmonization is necessary to add L9 to our HSA product.

Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0

Abstract. Air quality measurements from geostationary orbit by the instrument TEMPO (Tropospheric Emissions: Monitoring of Pollution) will offer an unprecedented view of atmospheric composition over North America. Measurements over Canadian latitudes, however, offer unique challenges: TEMPO's lines of sight are shallower, the sun is lower, and snow cover is more common. All of these factors increase the impact of the sphericity and the horizontal inhomogeneity of the atmosphere on the accuracy of the air quality measurements. Air mass factors encapsulate the complex paths of the measured sunlight, but traditionally they ignore horizontal variability. For the high spatial resolution of modern instruments such as TEMPO, the error due to neglecting horizontal variability is magnified and needs to be characterized. Here we present developments to SASKTRAN, the radiative transfer framework developed at the University of Saskatchewan, to calculate air mass factors in a spherical atmosphere, with and without consideration of horizontal inhomogeneity. Recent upgrades to SASKTRAN include first-order spherical corrections for the discrete ordinates method and the capacity to compute air mass factors with the Monte Carlo method. Together with finite-difference air mass factors via the successive orders method, this creates a robust framework for computing air mass factors. One-dimensional air mass factors from all three methods are compared in detail and are found to be in good agreement. Two-dimensional air mass factors are computed with the deterministic successive orders method, demonstrating an alternative for a calculation which would typically be done only with a nondeterministic Monte Carlo method. The two-dimensional air mass factors are used to analyze a simulated TEMPO-like measurement over Canadian latitudes. The effect of a sharp horizontal feature in surface albedo and NO2 was quantified while varying the distance of the feature from the intended measurement location. Such a feature in the surface albedo or NO2 could induce errors on the order of 5 % to 10 % at a distance of 50 km, and their combination could induce errors on the order of 10 % as far as 100 km away.

A New Methodology for Estimating Surface Albedo in Heterogeneous Areas from Satellite Imagery

Precise mapping and continuous monitoring of fine-scale surface albedo are indispensable for assessing and optimizing renewable energy sources. Understanding the variations in surface reflectivity is crucial in capturing the full potential of renewable technologies, as it directly impacts the efficiency of harnessing solar energy for sustainable power generation. Satellite remote sensing stands out as the sole practical approach for estimating surface albedo at both regional and global scales. Although there are different methods to calculate albedo from satellite data, most satellite products result in low spatial resolution for large heterogeneous areas, such as urban and peri-urban areas. This paper evaluates and compares several methodologies to calculate surface albedo from Landsat 8 imagery. As a result, a new methodology for estimating surface albedo for heterogeneous areas has been proposed. The new methodology has been compared with direct and indirect albedo measurements, improving the original methodologies of Baldinelli and Silva with respect to the Arctic-Boreal Vulnerability Experiment (ABOVE) albedo images by reducing the RMSE by 85% and 52%, respectively.

Global Observations of Tropospheric Bromine Monoxide (BrO) Columns From TROPOMI

AbstractBromine monoxide (BrO) plays an important role in tropospheric chemistry. The state‐of‐the‐science TROPOspheric Monitoring Instrument (TROPOMI) offers the potential to monitor atmospheric composition with a fine spatial resolution of up to 5.5 × 3.5 km2. We present here the retrieval of tropospheric BrO columns from TROPOMI. We implement a stratospheric correction scheme using a climatological approach based on the latest GEOS‐Chem High Performance chemical transport model, and improve the tropospheric air mass factor calculation with TROPOMI surface albedo data accounting for the geometrical dependency. Our product presents a good level of consistency in comparison with measurements from ground‐based zenith‐sky differential optical absorption spectroscopy (r = 0.67), aircrafts (r = 0.46), and satellites (similar spatial distributions of BrO columns). Furthermore, our retrieval captures BrO enhancements in the polar springtime with values up to 7.8 × 1013 molecules cm−2 and identifies small‐scale emission sources such as volcanoes and salt marshes. Based on TROPOMI data, we probe a blowing snow aerosol bromine mechanism in which the snow salinity is reduced to better match simulation and observation. Our TROPOMI tropospheric BrO product contributes high‐resolution global information to studies investigating atmospheric bromine chemistry.

Measurement of D/H and 13C/12C ratios in methane ice on Eris and Makemake: Evidence for internal activity

James Webb Space Telescope's NIRSpec infrared imaging spectrometer observed the outer solar system dwarf planets Eris and Makemake in reflected sunlight at wavelengths spanning 1 through 5 μm. Both objects have high albedo surfaces that are rich in methane ice, with a texture that permits long optical path lengths through the ice for solar photons. There is evidence for N2 ice absorption around 4.2 μm on Eris, though not on Makemake. No CO ice absorption is seen at 4.67 μm on either body. For the first time, absorption bands of two heavy isotopologues of methane are observed at 2.615 μm (13CH4), 4.33 μm (12CH3D), and 4.57 μm (12CH3D). These bands enable us to measure D/H ratios of (2.5 ± 0.5) × 10−4 and (2.9 ± 0.6) × 10−4, along with 13C/12C ratios of 0.012 ± 0.002 and 0.010 ± 0.003 in the surface methane ices of Eris and Makemake, respectively. The measured D/H ratios are much lower than that of presumably primordial methane in comet 67P/Churyumov-Gerasimenko, but they are similar to D/H ratios in water in many comets and larger outer solar system objects. This similarity suggests that the hydrogen atoms in methane on Eris and Makemake originated from water, indicative of geochemical processes in past or even ongoing hot environments in their deep interiors. The 13C/12C ratios are consistent with commonly observed solar system values, suggesting no substantial enrichment in 13C as could happen if the methane currently on their surfaces was the residue of a much larger inventory that had mostly been lost to space. Possible explanations include geologically recent outgassing from the interiors as well as processes that cycle the surface methane inventory to keep the uppermost surfaces refreshed.