Albedo Measurements Research Articles

Validation of Space-Based Albedo Products from Upscaled Tower-Based Measurements Over Heterogeneous and Homogeneous Landscapes

Surface albedo is a fundamental radiative parameter as it controls the Earth’s energy budget and directly affects the Earth’s climate. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous “ground truth” measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR).

The seasonal evolution of albedo across glaciers and the surrounding landscape of Taylor Valley, Antarctica

Abstract. The McMurdo Dry Valleys (MDVs) of Antarctica are a polar desert ecosystem consisting of alpine glaciers, ice-covered lakes, streams, and expanses of vegetation-free rocky soil. Because average summer temperatures are close to 0 ∘C, the MDV ecosystem in general, and glacier melt dynamics in particular, are both closely linked to the energy balance. A slight increase in incoming radiation or change in albedo can have large effects on the timing and volume of meltwater. However, the seasonal evolution or spatial variability of albedo in the valleys has yet to fully characterized. In this study, we aim to understand the drivers of landscape albedo change within and across seasons. To do so, a box with a camera, GPS, and shortwave radiometer was hung from a helicopter that flew transects four to five times a season along Taylor Valley. Measurements were repeated over three seasons. These data were coupled with incoming radiation measured at six meteorological stations distributed along the valley to calculate the distribution of albedo across individual glaciers, lakes, and soil surfaces. We hypothesized that albedo would decrease throughout the austral summer with ablation of snow patches and increasing sediment exposure on the glacier and lake surfaces. However, small snow events (<6 mm water equivalent) coupled with ice whitening caused spatial and temporal variability of albedo across the entire landscape. Glaciers frequently followed a pattern of increasing albedo with increasing elevation, as well as increasing albedo moving from east to west laterally across the ablation zone. We suggest that spatial patterns of albedo are a function of landscape morphology trapping snow and sediment, longitudinal gradients in snowfall magnitude, and wind-driven snow redistribution from east to west along the valley. We also compare our albedo measurements to the MODIS albedo product and found that overall the data have reasonable agreement. The mismatch in spatial scale between these two datasets results in variability, which is reduced after a snow event due to albedo following valley-scale gradients of snowfall magnitude. These findings highlight the importance of understanding the spatial and temporal variability in albedo and the close coupling of climate and landscape response. This new understanding of landscape albedo can constrain landscape energy budgets, better predict meltwater generation on from MDV glaciers, and how these ecosystems will respond to changing climate at the landscape scale.

Impact of Surface Albedo Assimilation on Snow Estimation

Surface albedo has a significant impact in determining the amount of available net radiation at the surface and the evolution of surface water and energy budget components. The snow accumulation and timing of melt, in particular, are directly impacted by the changes in land surface albedo. This study presents an evaluation of the impact of assimilating Moderate Resolution Imaging Spectroradiometer (MODIS)-based surface albedo estimates in the Noah multi-parameterization (Noah-MP) land surface model, over the continental US during the time period from 2000 to 2017. The evaluation of simulated snow depth and snow cover fields show that significant improvements from data assimilation (DA) are obtained over the High Plains and parts of the Rocky Mountains. Earlier snowmelt and reduced agreements with reference snow depth measurements, primarily over the Northeast US, are also observed due to albedo DA. Most improvements from assimilation are observed over locations with moderate vegetation and lower elevation. The aggregate impact on evapotranspiration and runoff from assimilation is found to be marginal. This study also evaluates the relative and joint utility of assimilating fractional snow cover and surface albedo measurements. Relative to surface albedo assimilation, fractional snow cover assimilation is found to provide smaller improvements in the simulated snow depth fields. The configuration that jointly assimilates surface albedo and fractional snow cover measurements is found to provide the most beneficial improvements compared to the univariate DA configurations for surface albedo or fractional snow cover. Overall, the study also points to the need for improving the albedo formulations in land surface models and the incorporation of observational uncertainties within albedo DA configurations.

Algal growth and weathering crust state drive variability in western Greenland Ice Sheet ice albedo

Abstract. One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS “dark zone” but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions.

Broadband albedo of Arctic sea ice from MERIS optical data

Abstract. Arctic summer sea ice experiences rapid changes in its sea-ice concentration, surface albedo, and the melt pond fraction. This affects the energy balance of the region and demands an accurate knowledge of those surface characteristics in climate models. In this paper, the broadband albedo (300–3000 nm) of Arctic sea ice is derived from MEdium Resolution Imaging Spectrometer (MERIS) optical swath data by transforming the spectral albedo as an output from the Melt Pond Detector (MPD) algorithm with a newly developed spectral-to-broadband conversion (STBC). The new STBC replaces the previously applied spectral averaging method to provide a more accurate broadband albedo product, which approaches the accuracy of 0.02–0.05 required in climate simulations and allows a direct comparison to broadband albedo values from climate models. The STBC is derived empirically from spectral and broadband albedo measurements over landfast ice. It is validated on a variety of simultaneous spectral and broadband field measurements over Arctic sea ice, is compared to existing conversion techniques, and performs better than the currently published algorithms. The root-mean-square deviation (RMSD) between broadband albedo that was measured and converted by the STBC is 0.02. Other conversion techniques, the spectral averaging method and the linear combination of albedo values from four MERIS channels, result in higher RMSDs of 0.09 and 0.05, respectively. The improved MERIS-derived broadband albedo values are validated with airborne measurements. Results show a smaller RMSD of 0.04 for landfast ice than the RMSD of 0.07 for drifting ice. The MERIS-derived broadband albedo is compared to broadband albedo from ERA5 reanalysis to examine the albedo parameterization used in ERA5. Both albedo products agree over large scales and in temporal patterns. However, consistency in point-to-point comparison is rather poor, with differences up to 0.20, correlations between 0.69 and 0.79, and RMSDs in excess of 0.10. Differences in sea-ice concentration and cloud-masking uncertainties play a role, but most discrepancies can be attributed to climatological sea-ice albedo values used in ERA5. They are not adequate and need revising, in order to better simulate surface heat fluxes in the Arctic. The advantage of the resulting broadband albedo data set from MERIS over other published data sets is the accompanied data set of available melt pond fraction. Melt ponds are the main reason for the sea-ice albedo change in summer but are currently not represented in climate models and atmospheric reanalysis. Additional information about melt evolution, together with accurate albedo retrievals, can aid the challenging representation of sea-ice optical properties in those models in summer.

Google Earth Engine–assisted black carbon radiative forcing calculation over a heavy industrial city in China

Black carbon (BC) aerosol has a low content in the atmosphere; however, it has a strong radiative forcing effect and a significant impact on human beings and the environment. BC aerosol radiative forcing (ARF) has a major environmental influence. The main method to calculate the ARF is numerical simulation using a radiation transfer model by inputting atmospheric and surface parameters. Currently, most research studies directly apply the albedo products, which are not the real surface albedo (the blue-sky albedo). Alternatively, they use an empirical formula to calculate the sky diffuse light ratio to obtain the real surface albedo. To overcome these shortcomings, this study develops a new scheme to obtain the BC ARF in Xuzhou City from May 2014 to July 2016 by combining the BC mass concentration, albedo measurements from the Google Earth Engine (GEE) platform, aerosol optical depth (AOD), and microphysical parameters retrieved from the Aerosol Robotic Network (AERONET). Although BC AOD accounts for 3.3 to 17.9% of the total AOD, the BC ARF at the surface (SFC) and top of the atmosphere (TOA) is between − 14.06 ± 4.645 W/m2 and − 4.04 ± 0.437 W/m2 and between 2.93 ± 1.034 W/m2 and 0.74 ± 0.093 W/m2, with average values of − 9.67 ± 2.787 W/m2 and 2.02 ± 0.587 W/m2, respectively. Finally, comparing the BC ARF obtained by different albedo methods shows that the BC ARF change at the TOA is marked, and generally, the BC ARF calculated by the empirical formula method is lower than that calculated by using the blue-sky albedo method.

The Determination of Snow Albedo from Satellite Measurements Using Fast Atmospheric Correction Technique

We present a simplified atmospheric correction algorithm for snow/ice albedo retrievals using single view satellite measurements. The validation of the technique is performed using Ocean and Land Colour Instrument (OLCI) on board Copernicus Sentinel-3 satellite and ground spectral or broadband albedo measurements from locations on the Greenland ice sheet and in the French Alps. Through comparison with independent ground observations, the technique is shown to perform accurately in a range of conditions from a 2100 m elevation mid-latitude location in the French Alps to a network of 15 locations across a 2390 m elevation range in seven regions across the Greenland ice sheet. Retrieved broadband albedo is accurate within 5% over a wide (0.5) broadband albedo range of the (N = 4155) Greenland observations and with no apparent bias.

Evaluating the performance of a double integrating sphere in measurement of reflectance, transmittance, and albedo of coniferous needles

Leaf reflectance and transmittance spectra are essential information in many applications such as developing remote sensing methods, computing shortwave energy balance (albedo) of forest canopies, and monitoring health or stress of trees. Measurement of coniferous needle spectra has usually been carried out with single integrating spheres, which has involved a lot of tedious manual work. A small double integrating sphere would make the measurements considerably faster, because of its ease of operation and small sample sizes required. Here we applied a compact double integrating sphere setup, used previously for measurement of broad leaves, for measurement of coniferous needles. Test measurements with the double integrating sphere showed relative underestimation of needle albedo by 5–39% compared to a well-established single integrating sphere setup. A small part of the bias can be explained by the bias of the single sphere. Yet the observed bias is quite significant if absolute accuracy of measurements is required. For relative measurements, e.g. for monitoring development of needle spectra over time, the double sphere system provides notable improvement. Furthermore, it might be possible to reduce the bias by building an optimized measurement setup that minimizes absorption losses in the sample port. Our study indicates that double spheres, after some technical improvement, may provide a new and fast way to collect extensive spectral libraries of tree species.

Surface albedo of alpine lichen heaths and shrub vegetation

ABSTRACT Lichen heaths are declining in abundance while shrubs are increasing their range in alpine and arctic areas due to climate change. This can have a large impact on the surface albedo of these areas. The aim of this article is to quantify the difference in albedo between lichen heaths and shrub-dominated vegetation and the variability within lichen heaths. Several environmental conditions that can influence the albedo measurements are considered. We measured the albedo of twenty lichen- and shrub-dominated plots on an alpine mountain area in southern Norway in the summer of 2018 with two radiometers using a paired plot design. With this design, we ensured similar weather conditions, aspects, and zenith angles between the paired lichen- and shrub-dominated plots. In addition, we collected patches of Cladonia stellaris and Flavocetraria nivalis to measure their albedo. The average difference in albedo between the lichen- and shrub-dominated plots is 0.124. The albedo of the lichen-dominated plots varies between 0.227 and 0.284, and that of the shrub-dominated plots varies between 0.115 and 0.148. This variation in albedo is explained by differences in aspect and vegetation composition. Further studies should focus on the consequences of this decrease in albedo for the microclimate in alpine and arctic areas.

Estimación de las variaciones espacio temporales de albedo en los glaciares Olivares, Chile Central

This study derived albedo measurements from the Olivares Alfa, Beta and Gama glaciers, placed on the central Chilean Andes, by processing Landsat-8 satellite images acquired in January 1990, 1996 and 2017. The aim was to estimate spatiotemporal variations of such a variable. Between 1990 and 2017, the average albedo of the Olivares Alfa glacier decreased by 0.17 (0.43-0.26), which translated into an annual rate of decrease of 1.78%. On the same period, the average albedo of Olivares Beta glacier decreased by 0.09 (0.48-0.39), which translated into an annual rate of decrease of 1.33%, while the average albedo of the Olivares Gama glacier decreased by 0.12 (0.45-0.33), translating into an annual rate of decrease of 1.1%. The mapping of the albedo differential of each glacier, resulting from subtracting the 1990 albedo from the 2017 albedo, enabled to appreciate the spatial variations of the variable, which evidenced its largest decreases on both, accumulation and ablation glacier zones. The remote sensing-derived albedo could be included in the mass balance of these and other glaciers of the country. This would enable to assess the impact of the decreasing of this variable on the ice loss and its relationship with the climatic variability induced by the global warming and climate change.

Impacts and Contributors of Representativeness Errors of $In~Situ$ Albedo Measurements for the Validation of Remote Sensing Products

Validation of remote sensing albedo products involves comparisons between point-scale in situ observations and footprint-scale satellite retrievals. However, the observed differences between product and in situ observations are not only attributable to intrinsic errors of satellite products but also to inadequate spatial representativeness of in situ observations. Here, representativeness errors of in situ observations and their effects on validation results were quantitatively explored. Furthermore, the contributors and their influences on representativeness errors were quantified. In the case of large representativeness errors, validation result errors are mainly controlled by representativeness errors. When representativeness errors are small, validation result errors are likely affected by other factors and can be so large that cannot be ignored. Surface heterogeneity is most positively related to representativeness errors, followed by the deviation distance of in situ site from the pixel center. The representative area surrounding in situ sites only shows a weak negative correlation with representativeness errors. The range seems to be not a good indicator of spatial representativeness of in situ sites since there is almost no relationship between them. When these factors are combined, surface heterogeneity contributes more to representativeness errors on the 500-m pixel scale, while quantitative impacts of the representative area and location deviation of in situ sites are not fully understood because magnitudes of these effects are dependent on the choice of high-resolution data set. These findings enhance our understanding about spatial representativeness of in situ observations and improve the quality of validation results based on single in situ observations.

Development of the Direct-Estimation Albedo Algorithm for Snow-Free Landsat TM Albedo Retrievals Using Field Flux Measurements

Anisotropy information from moderate-to-coarse-resolution sensors [e.g., 500-m Moderate Resolution Imaging Spectroradiometer (MODIS)] is widely applied to estimate high-resolution surface albedo. Simulated albedos using MODIS bidirectional reflectance distribution function (BRDF) parameters as prior knowledge based on the kernel-driven model are employed to build and assess the lookup table (LUT) of the direct-estimation method, which is then used to estimate high-resolution albedos directly from top-of-atmosphere (TOA) reflectance data (e.g., Landsat albedo). Previously, the errors in the simulated albedos were not considered in building and assessing the LUT. In this article, daytime time-series (30 min) of snow-free albedo measurements with sufficient solar zenith angles (SZAs) were introduced to build the LUT for snow-free Landsat TM surface shortwave broadband albedo (TM albedo) retrievals, together with TOA-simulated reflectance by concurrent daily MODIS BRDF parameters. The assessment utilizes an independent data set and shows larger discrepancies between the estimated and measured albedos [root-mean-square errors (RMSEs) of >0.03 at SZAs ≥ 60°] than those in previous articles. To reduce inconsistencies between the MODIS BRDF parameters and the observed albedos, as well as possible spatial resolution differences between the MODIS and Landsat data, we adopted a correction strategy that first linearly adjusts the MODIS BRDF parameters to match the albedo measurements by a magnitude method, and second, the TOA reflectance simulations were further corrected by concurrent TM reflectances. The developed algorithm shows a significant improvement after using such corrections as a priori (RMSE < 0.02 at SZA ≤ 75°). The validation indicates improved accuracies in the TM albedo estimation. These improvements may provide potential albedo estimations for nadir-viewing high-resolution sensors using coarse-resolution anisotropy information.

Estimation of surface albedo from meteorological observations across China

Surface albedo is an important parameter in agronomic, physiological, biological, and biogeochemical studies. Ground observations of surface albedo, which are available at only a limited number of stations worldwide, are not applicable for most unmonitored areas. The objective of this study was to develop an analytical model that accounts for the effects of various influencing factors in estimating snow-free surface albedo from standard meteorological observations. Daily measurements of surface albedo during 1993–2015 from 14 meteorological stations were collected to calibrate the model parameters and to examine the performance of the developed model. The comparative results indicated that the calibrated model performed well in ground albedo parameterization across China. The calibrated model was also applied to estimate the surface albedo of a hypothetical reference crop. The simulated results demonstrated that the reference surface albedo was generally less than the specified default constant value of 0.23 and that it exhibited characteristic seasonal and latitudinal variations. The use of the default constant value of albedo rather than the albedo estimated using the proposed model resulted in systematic underestimation of net radiation, especially for low-latitude regions in summer and autumn.

Stand age and species composition effects on surface albedo in a mixedwood boreal forest

Abstract. Surface albedo is one of the most important processes governing climate forcing in the boreal forest and is directly affected by management activities such as harvesting and natural disturbances such as forest fires. Empirical data on the effects of these disturbances on boreal forest albedo are sparse. We conducted ground-based measurements of surface albedo from a series of instrument towers over 4 years in a replicated chronosequence of mixedwood boreal forest sites differing in stand age (to 19 years since disturbance) in both post-harvest and post-fire stands. We investigated the effects of stand age, canopy height, tree species composition, and ground vegetation cover on surface albedo through stand development. Our results indicate that winter and spring albedo values were 63 % and 24 % higher, respectively, in post-harvest stands than in post-fire stands. Summer and fall albedo values were similar between disturbance types, with summer albedo showing a transient peak at ∼10 years stand age. The proportion of deciduous broadleaf species showed a strong positive relationship with seasonal averages of albedo in both post-harvest and post-fire stands. Given that stand composition in mixedwood boreal forests generally shows a gradual replacement of deciduous trees by conifers, our results suggest that successional changes in species composition are likely a key driver of age-related patterns in albedo. Our findings also suggest the efficacy of increasing the proportion of deciduous broadleaf species as a silvicultural option for climate-friendly management of the boreal forest.

The Ganymede laser altimeter (GALA): key objectives, instrument design, and performance

The Ganymede Laser Altimeter (GALA) is one of the ten scientific instruments selected for the Jupiter Icy Moons Explorer (JUICE) mission currently implemented under responsibility of the European Space Agency (ESA). JUICE is scheduled for launch in mid 2022; arrival at Jupiter will be by end of 2029 with the nominal science mission—including close flybys at Ganymede, Europa, and Callisto and a Ganymede orbit phase—ending by mid 2033. GALA’s main objective is to obtain topographic data of the icy satellites of Jupiter: Europa, Ganymede, and Callisto. By measuring the diurnal tidal deformation of Ganymede, which crucially depends on the decoupling of the surface ice layer from the deep interior by a liquid water ocean, GALA will obtain evidence for (or against) a subsurface ocean in a 500 km orbit around the satellite and will provide constraints on Ganymede’s ice shell thickness. In combination with other instruments, it will characterize the morphology of surface units on Ganymede, Europa, and Callisto providing not only topography but also surface roughness and albedo (at 1064 nm) measurements. GALA is a single-beam laser altimeter operating with up to 50 Hz (nominal 30 Hz) shot frequency at a wavelength of 1064 nm and pulse lengths of $$5.5\pm 2.5$$ ns using a Nd:YAG laser. The return pulse is detected by an Avalanche Photo Diode (APD) with 100 MHz bandwidth and is digitized at a sampling rate of 200 MHz providing range measurements with a subsample resolution of 0.1 m and surface roughness measurements from pulse-shape analysis on the scale of the footprint size of about 50 m at 500 km altitude. The instrument is developed in collaboration of institutes and industry from Germany, Japan, Switzerland, and Spain.

An Examination of Snow Albedo Estimates From MODIS and Their Impact on Snow Water Equivalent Reconstruction

AbstractSnow albedo is a dominant control on snowmelt in many parts of the world. An empirical albedo decay equation, developed over 60 years ago, is still used in snowmelt models. Several empirical snow albedo models developed since show wide spread in results. Remotely sensed snow albedos have been used in a few studies, but validations are scarce because of the difficulty in making accurate in situ measurements. Reconstruction of snow water equivalent (SWE), where the snowpack is built in reverse, is especially sensitive to albedo. We present two new contributions: (1) an updated albedo model where grain size and light absorbing particle content are solved for simultaneously and (2) multiyear comparisons of remotely sensed and in situ albedo measurements from three high‐altitude sites in the western United States. Our remotely sensed albedos show 4 to 6% RMSE and negligible bias. In comparison, empirical albedo decay models, which require extensive in situ measurements, show RMSE values of 7 to 17% with biases of −6 to −14%. We examine the sensitivity of SWE reconstructions to albedo error at two sites. With no simulated error in albedo, reconstructed SWE had MAE values of 7 to 13% and 5–6% bias. The accuracy actually improved with some simulated added error, likely because of a fundamental bias in the reconstruction approach. Conversely, the best age‐based decay model showed an 18–20% MAE and bias in reconstructed SWE. We conclude that remotely sensed albedos where available are superior to age‐based approaches in all aspects except simplicity.

Long-term Variations of Venus’s 365 nm Albedo Observed by Venus Express, Akatsuki, MESSENGER, and the Hubble Space Telescope

Abstract An unknown absorber near the cloud-top level of Venus generates a broad absorption feature from the ultraviolet (UV) to visible, peaking around 360 nm, and therefore plays a critical role in the solar energy absorption. We present a quantitative study of the variability of the cloud albedo at 365 nm and its impact on Venus’s solar heating rates based on an analysis of Venus Express and Akatsuki UV images and Hubble Space Telescope and MESSENGER UV spectral data; in this analysis, the calibration correction factor of the UV images of Venus Express (Venus Monitoring Camera) is updated relative to the Hubble and MESSENGER albedo measurements. Our results indicate that the 365 nm albedo varied by a factor of 2 from 2006 to 2017 over the entire planet, producing a 25%–40% change in the low-latitude solar heating rate according to our radiative transfer calculations. Thus, the cloud-top level atmosphere should have experienced considerable solar heating variations over this period. Our global circulation model calculations show that this variable solar heating rate may explain the observed variations of zonal wind from 2006 to 2017. Overlaps in the timescale of the long-term UV albedo and the solar activity variations make it plausible that solar extreme UV intensity and cosmic-ray variations influenced the observed albedo trends. The albedo variations might also be linked with temporal variations of the upper cloud SO2 gas abundance, which affects the H2SO4–H2O aerosol formation.

Post-rendezvous radar properties of comet 67P/CG from the Rosetta Mission: understanding future Earth-based radar observations and the dynamical evolution of comets

ABSTRACTRadar observations provide crucial insights into the formation and dynamical evolution of comets. This ability is constrained by our knowledge of the dielectric and textural properties of these small-bodies. Using several observations by Rosetta as well as results from the Earth-based Arecibo radio telescope, we provide an updated and comprehensive dielectric and roughness description of Comet 67P/CG, which can provide new constraints on the radar properties of other nuclei. Furthermore, contrary to previous assumptions of cometary surfaces being dielectrically homogeneous and smooth, we find that cometary surfaces are dielectrically heterogeneous ( εr′≈1.6–3.2), and are rough at X- and S-band frequencies, which are widely used in characterization of small-bodies. We also investigate the lack of signal broadening in CONSERT observations through the comet head. Our results suggest that primordial building blocks in the subsurface are either absent, smaller than the radar wavelength, or have a weak dielectric contrast (Δ εr′). To constrain this ambiguity, we use optical albedo measurements by the OSIRIS camera of the freshly exposed subsurface after the Aswan cliff collapse. We find that the hypothetical subsurface blocks should have |Δ εr′|≳0.15, setting an upper limit of ∼ 1 m on the size of 67P/CG's primordial building blocks if they exist. Our analysis is consistent with a purely thermal origin for the ∼ 3 m surface bumps on pit walls and cliff-faces, hypothesized to be high-centred polygons formed from fracturing of the sintered shallow ice-bearing subsurface due to seasonal thermal expansion and contraction. Potential changes in 67P/CG's radar reflectivity at these at X- and S-bands can be associated with large-scale structural changes of the nucleus rather than small-scale textural ones. Monitoring changes in 67P/CG's radar properties during repeated close-approaches via Earth-based observations can constrain the dynamical evolution of its cometary nucleus.

Black and White-Sky Albedo Values of Snow: In Situ Relationships for AVHRR-Based Estimation Using CLARA-A2 SAL

The relationship of black-sky and white-sky albedo values of snow-covered terrain is studied using empirical measurements of six BSRN sites and the Finnish Meteorological Institute Sodankylä site, where albedo measurements are carried out both in an open area and above coniferous forest. In addition, a forest model was used to provide simulated albedo values to cover a wider leaf area index range. Linear regression formulas for estimating the monthly mean white-sky albedo value on the basis of the monthly statistics of the black-sky albedo were derived separately for open and forested areas. The statistical parameters used were the mean, median, standard deviation, skewness and kurtosis. In addition, the monthly mean solar zenith angle value was used as well. The mean absolute difference between the estimated monthly mean white-sky albedo and the empirical value was 0.027 for open areas and 0.015 for forested areas. The derived formulas were applied to the satellite black-sky albedo product CLARA-A2 SAL to generate white-sky albedo maps. Using the open snow area regression for the sea ice area produced values comparable to measured values both around the Antarctic and in the Arctic sea ice area.

Validation of the sea ice surface albedo scheme of the regional climate model HIRHAM–NAOSIM using aircraft measurements during the ACLOUD/PASCAL campaigns

Abstract. For large-scale and long-term Arctic climate simulations appropriate parameterization of the surface albedo is required. Therefore, the sea ice surface (SIS) albedo parameterization of the coupled regional climate model HIRHAM–NAOSIM was examined against broadband surface albedo measurements performed during the joint ACLOUD (Arctic CLoud Observations Using airborne measurements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) campaigns, which were performed in May–June 2017 north of Svalbard. The SIS albedo parameterization was tested using measured quantities of the prognostic variables surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes (snow-covered ice, bare ice, and melt ponds) derived from digital camera images taken on board the Polar 5 and 6 aircraft. The selected low-altitude (less than 100 m) flight sections of overall 12 flights were performed over surfaces dominated by snow-covered ice. It was found that the range of parameterized SIS albedo for individual days is smaller than that of the measurements. This was attributed to the biased functional dependence of the SIS albedo parameterization on temperature. Furthermore, a time-variable bias was observed with higher values compared to the modeled SIS albedo (0.88 compared to 0.84 for 29 May 2017) in the beginning of the campaign, and an opposite trend towards the end of the campaign (0.67 versus 0.83 for 25 June 2017). Furthermore, the surface type fraction parameterization was tested against the camera image product, which revealed an agreement within 1 %. An adjustment of the variables, defining the parameterized SIS albedo, and additionally accounting for the cloud cover could reduce the root-mean-squared error from 0.14 to 0.04 for cloud free/broken cloud situations and from 0.06 to 0.05 for overcast conditions.