Moderate Resolution Imaging Spectroradiometer Albedo Research Articles

Directional Applicability Analysis of Albedo Retrieval Using Prior BRDF Knowledge

Surface albedo measures the proportion of incoming solar radiation reflected by the Earth’s surface. Accurate albedo retrieval from remote sensing data usually requires sufficient multi-angular observations to account for the surface reflectance anisotropy. However, most middle and high-resolution remote sensing satellites lack the capability to acquire sufficient multi-angular observations. Existing algorithms for retrieving surface albedo from single-direction reflectance typically rely on land cover types and vegetation indices to extract the corresponding prior knowledge of surface anisotropic reflectance from coarse-resolution Bidirectional Reflectance Distribution Function (BRDF) products. This study introduces an algorithm for retrieving albedo from directional reflectance based on a 3 × 3 BRDF archetype database established using the 2015 global time-series Moderate Resolution Imaging Spectro-radiometer (MODIS) BRDF product. For different directions, BRDF archetypes are applied to the simulated MODIS directional reflectance to retrieve albedo. By comparing the retrieved albedos with the MODIS albedo, the BRDF archetype that yields the smallest Root Mean Squared Error (RMSE) is selected as the prior BRDF for the direction. A lookup table (LUT) that contains the optimal BRDF archetypes for albedo retrieval under various observational geometries is established. The impact of the number of BRDF archetypes on the accuracy of albedo is analyzed according to the 2020 MODIS BRDF. The LUT is applied to the MODIS BRDF within specific BRDF archetype classes to validate its applicability under different anisotropic reflectance characteristics. The applicability of the LUT across different data types is further evaluated using simulated reflectance or real multi-angular measurements. The results indicate that (1) for any direction, a specific BRDF archetype can retrieve a high-accuracy albedo from directional reflectance. The optimal BRDF archetype varies with the observation direction. (2) Compared to the prior BRDF knowledge obtained through averaging method, the BRDF archetype LUT based on the 3 × 3 BRDF archetype database can more accurately retrieve the surface albedo. (3) The BRDF archetype LUT effectively eliminates the influence of surface anisotropic reflectance characteristics in albedo retrieval across different scales and types of data.

Surface Albedo and Snowline Altitude Estimation Using Optical Satellite Imagery and In Situ Measurements in Muz Taw Glacier, Sawir Mountains

Glacier surface albedo strongly affects glacier mass balance by controlling the glacier surface energy budget. As an indicator of the equilibrium line altitude (ELA), the glacier snowline altitude (SLA) at the end of the melt season can reflect variations in the glacier mass balance. Therefore, it is extremely crucial to investigate the changes of glacier surface albedo and glacier SLA for calculating and evaluating glacier mass loss. In this study, from 2011 to 2021, the surface albedo of the Muz Taw Glacier was derived from Landsat images with a spatial resolution of 30 m and from the Moderate Resolution Imaging Spectroradiometer albedo products (MOD10A1) with a temporal resolution of 1 day, which was verified through the albedo measured by the Automatic Weather Station (AWS) installed in the glacier. Moreover, the glacier SLA was determined based on the variation in the surface albedo, with the altitude change along the glacier main flowline derived from the Landsat image at the end of the melt season. The correlation coefficient of >0.7, with a risk of error lower than 5%, between the surface albedo retrieved from remote sensing images and the in situ measurement data indicated that the method of deriving the glacier surface albedo by the remote sensing method was reliable. The annual average albedo showed a slight upward trend (0.24%) from 2011 to 2021. A unimodal seasonal variation in albedo was demonstrated, with the downward trend from January to August and the upward trend from August to December. The spatial distribution of the albedo was not entirely dependent on altitude due to the dramatic effects of the topography and glacier surface conditions. The average SLA was 3446 m a.s.l., with a variation of 160 m from 2011 to 2021. The correlation analysis between the glacier SLA and annual mean temperature/annual precipitation demonstrated that the variations of the average SLA on the Muz Taw Glacier was primarily affected by the air temperature. This study improved our understanding of the ablation process and mechanism of the Muz Taw Glacier.

Sensitivity of Coarse‐Scale Snow‐Free Land Surface Shortwave Albedo to Topography

AbstractAs a widespread landscape, rugged terrain significantly distorts the land surface albedo. Simply neglecting the topographic effects in the land surface albedo modeling and retrievals can lead to large biases and uncertainties over rugged terrain. In spite of gradually increasing research about the topographic effects on the albedo, the albedo sensitivities over rugged terrain to different variables remain unclear. In this paper, the sensitivities of coarse‐scale snow‐free albedo to topography were quantitatively investigated using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface albedo data and the variance‐based global sensitivity analysis based on a well‐established mechanistically‐based land surface albedo parameterized model over rugged terrain. The results based on the MODIS data revealed that MODIS land surface albedo over the Tibetan Plateau was highly sensitive to the topographic distribution, and the differences of the spatially averaged snow‐free black‐sky albedos over grasslands induced by different terrain could reach up to 0.10 in winter. The topographic effects on MODIS albedo are tightly relevant to the land cover type, solar illumination geometries, and vegetation characteristics. The global sensitivity analysis results underscored that topography was an important driving factor of the snow‐free albedo, and it accounted for more than 30% of the total variance, respectively. These results highlight the necessities for the topographic consideration in the land surface albedo modeling and retrievals even though the terrain is gentle (10–20°) and advance our understanding of the albedo sensitivities to different variables over rugged terrain, which will facilitate the improvement of land surface albedo parameterization in the land surface models.

Response of surface air temperature to the change of leaf area index in the source region of the Yellow River by the WRF model

Leaf area index (LAI) is a crucial land-atmosphere exchange parameter. LAI change can cause a variation of other land surface parameter. In this research, three experiments were conducted to investigate the impact of LAI and albedo change on surface air temperature in the source region of the Yellow River (SRYR) using the Weather Research and Forecasting (WRF) model. Three experiments used the same settings, initial and boundary conditions except for the LAI and albedo data. The control simulation (CTL) used the WRF model climatological LAI data, the second simulation (LAI) used the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI data, and the third simulation (LAIALB) used the MODIS LAI and MODIS albedo. The results show MODIS LAI is greater by 34.5% than WRF climatological LAI, and the MODIS albedo is lower by 24.3% than WRF climatological albedo over the whole growing season of 2006 in SRYR. All the experiments can simulate the surface air temperature (Ta) spatial distribution characteristics, but underestimate the values of 1.3 °C in CTL experiment and 0.6 °C in LAIALB experiment in SRYR. The simulated Ta by LAI experiment is lower 0.1 °C than by the CTL experiment, but the simulated Ta by the LAIALB experiment is obviously higher 0.6 °C than the CTL experiment. The LAI experiment shows a cooling effect because the higher MODIS LAI decreases the canopy resistance, which induces a positive average 2.1 Wm−2 latent heat flux (LH) and a negative average − 2.1 Wm−2 sensible heat flux (Hs). The LAIALB experiment presents a warming effect because of low MODIS albedo comparing WRF albedo, which changes the radiation components and results in an obvious negative − 14.0 Wm−2 upward short wave radiation, a positive 11.7 Wm−2 net radiation, and a positive 10.9 Wm−2 heat flux. In fact, more precipitation produces more snow and high surface albedo in the WRF model, which results in a cold temperature bias in SRYR.

Quantifying the Reflectance Anisotropy Effect on Albedo Retrieval from Remotely Sensed Observations Using Archetypal BRDFs

The reflectance anisotropy effect on albedo retrieval was evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution functions (BRDFs) product, and archetypal BRDFs. Shortwave-band archetypal BRDFs were established, and validated, based on the Anisotropy Flat indeX (AFX) and time series MODIS BRDF over tile h11v03. To generate surface albedo, archetypal BRDFs were used to fit simulated reflectance, based on the least squares method. Albedo was also retrieved based on the least root-mean-square-error (RMSE) method or normalized difference vegetation index (NDVI) based prior BRDF knowledge. The difference between those albedos and the MODIS albedo was used to quantify the reflectance anisotropy effect. The albedo over tile h11v03 for day 185 in 2009 was retrieved from single directional reflectance and the third archetypal BRDF. The results show that six archetypal BRDFs are sufficient to represent the reflectance anisotropy for albedo estimation. For the data used in this study, the relative uncertainty caused by reflectance anisotropy can reach up to 7.4%, 16.2%, and 20.2% for sufficient, insufficient multi-angular and single directional observations. The intermediate archetypal BRDFs may be used to improve the albedo retrieval accuracy from insufficient or single observations with a relative uncertainty range of 8–15%.

Annual Glacier-Wide Mass Balance (2000–2016) of the Interior Tibetan Plateau Reconstructed from MODIS Albedo Products

Glaciers in the Tibetan Plateau (TP) play a crucial role in regulating agriculture irrigation, river discharge and the regional/global climate system. However, mass balance records of TP glaciers have remained scarce due to challenging mountainous terrain and harsh weather conditions, which limits our understanding of the influence of melting glaciers on local water resources and responses to climate change. Here, we present and assess an albedo-based method to derive annual mass balance for three glaciers in the interior TP from Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data during 2000–2016. A strong linear correlation (R2 = 0.941, P < 0.001) is found between annual minimum-averaged glacier-wide albedo (AMGA) values and annual mass balance measurements on the Xiao Dongkemadi glacier. Furthermore, the 17-year-long annual mass balance series of the Xiao Dongkemadi glacier and the Geladandong mountain region glaciers, and the Purogangri ice cap are reconstructed for the first time, with a mass loss rate of 535 ± 63 mm w.e.a−1, 243 ± 66 mm w.e.a−1 and 113 ± 68 mm w.e.a−1, respectively. The results are verified by geodetic estimates, with relative error ranging from 4.55% to 11.80%, confirming that the albedo-based method can be used to estimate specific mass budgets for interior TP glaciers. A strong correlation between the mass balance series and air temperature infers that increasing summer air temperature may be one of main reasons for glacier shrinkage of the three studied glaciers.

Assessment of NPP VIIRS Albedo Over Heterogeneous Crop Land in Northern China

AbstractIn this paper, the accuracy of Suomi National Polar‐orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) land surface albedo, which is derived from the direct estimation algorithm, was assessed using ground‐based albedo observations from a wireless sensor network over a heterogeneous cropland in the Huailai station, northern China. Data from six nodes spanning 2013–2014 over vegetation, bare soil, and mixed terrain surfaces were utilized to provide ground reference at VIIRS pixel scale. The performance of VIIRS albedo was also compared with Global LAnd Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) albedos (Collection 5 and 6). The results indicate that the current granular VIIRS albedo has a high accuracy with a root‐mean‐square error of 0.02 for typical land covers. They are significantly correlated with ground references indicated by a correlation coefficient (R) of 0.73. The VIIRS albedo shows distinct advantages to GLASS and MODIS albedos over bare soil and mixed‐cover surfaces, while it is inferior to the other two products over vegetated surfaces. Furthermore, its time continuity and the ability to capture the abrupt change of surface albedo are better than that of GLASS and MODIS albedo.

Evaluation of the VIIRS BRDF, Albedo and NBAR products suite and an assessment of continuity with the long term MODIS record

Bidirectional Reflectance Distribution Function (BRDF) model parameters, Albedo quantities, and Nadir BRDF Adjusted Reflectance (NBAR) products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS), on the Suomi-NPP (National Polar-orbiting Partnership) satellite are evaluated with spatially representative in situ tower albedometer measurements and through comparison with the MODerate Resolution Imaging Spectroradiometer (MODIS) long term record. White Sky Albedo (WSA), Black Sky Albedo (BSA), NBAR, and Quality Assurance (QA) results show that the VIIRS algorithm is performing well at the global scale and is able to provide global data products comparable with the heritage MODIS (with an absolute bias of 0.0069 for shortwave broadband WSA) despite the spectral, angular, and effective spatial resolution differences between the two sensors. Both VIIRS and MODIS albedo are shown to agree well with in situ albedo measurements at a number of spatially representative sites. This evaluation provides confidence that the high quality, daily VIIRS BRDF model parameters, Albedo, and NBAR products will be able to provide the long term continuity required by the modeling and monitoring communities.

Spatial, seasonal, and topographical patterns of surface albedo in Norwegian forests and cropland

ABSTRACTLand surface albedo is a key parameter of the Earth’s climate system. It has high variability in space, time, and land cover and it is among the most important variables in climate models. Extensive large-scale estimates can help model calibration and improvement to reduce uncertainties in quantifying the influence of surface albedo changes on the planetary radiation balance. Here, we use satellite retrievals of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo (MCD43A3), high-resolution land-cover maps, and meteorological records to characterize climatological albedo variations in Norway across latitude, seasons, land-cover type (deciduous forests, coniferous forests, and cropland), and topography. We also investigate the net changes in surface albedo and surface air temperature through site pair analysis to mimic the effects of land-use transitions between forests and cropland and among different tree species. We find that surface albedo increases at increasing latitude in the snow season, and cropland and deciduous forests generally have higher albedo values than coniferous forests, but for few days in spring. Topography has a large influence on MODIS albedo retrievals, with values that can change up to 100% for the same land-cover class (e.g. spruce in winter) under varying slopes and aspect of the terrain. Cropland sites have surface air temperature higher than adjacent forested sites, and deciduous forests are slightly colder than adjacent coniferous forests. By integrating satellite measurements and high-resolution vegetation maps, our results provide a large semi-empirical basis that can assist future studies to better predict changes in a fundamental climate-regulating service such as surface albedo.

Upscaling in situ albedo for validation of coarse scale albedo product over heterogeneous surfaces

ABSTRACTOne of the essential steps for satellite albedo validation is upscaling in situ measurements to corresponding pixel scale over relatively heterogeneous land surfaces. Although the multi-scale validation strategy is applicable for heterogeneous surfaces, the calibration of the high-resolution imagery during upscaling process is never perfect, and thus the upscaling results suffer from errors. The regression-kriging (RK) technique can compensate the calibration part by applying kriging to upscale residuals and produce more accurate upscaling results. In this paper, in situ measurements and high spatial resolution albedo imagery combined with RK technique was proposed. This method is illustrated by upscaling surface albedo from in situ measurements scale to the coarse pixel scale in the core experimental area of HiWATER, where 17 WSN nodes were deployed at heterogeneous area. The upscaling results of this method were compared with the upscaling results from multi-scale strategy. The results show that the upscaling method based on in situ measurements and high-resolution imagery combined with RK technique can capture the spatial characteristics of surface albedo better. Further, an attempt was made to expand this method in time series. Finally, a preliminary validation of the Moderate Resolution Imaging Spectroradiometer albedo product was performed as the tentative application.

Fire disturbance effects on land surface albedo in Alaskan tundra

AbstractThe study uses satellite Moderate Resolution Imaging Spectroradiometer albedo products (MCD43A3) to assess changes in albedo at two sites in the treeless tundra region of Alaska, both within the foothills region of the Brooks Range, the 2007 Anaktuvuk River Fire (ARF) and 2012 Kucher Creek Fire (KCF). Results are compared to each other and other studies to assess the magnitude of albedo change and the longevity of impact of fire on land surface albedo. In both sites there was a marked decrease of albedo in the year following the fire. In the ARF, albedo slowly increased until 4 years after the fire, when it returned to albedo values prior to the fire. For the year immediately after the fire, a threefold difference in the shortwave albedo decrease was found between the two sites. ARF showed a 45.3% decrease, while the KCF showed a 14.1% decrease in shortwave albedo, and albedo is more variable in the KCF site than ARF site 1 year after the fire. These differences are possibly the result of differences in burn severity of the two fires, wherein the ARF burned more completely with more contiguous patches of complete burn than KCF. The impact of fire on average growing season (April–September) surface shortwave forcing in the year following fire is estimated to be 13.24 ± 6.52 W m−2 at the ARF site, a forcing comparable to studies in other treeless ecosystems. Comparison to boreal studies and the implications to energy flux are discussed in the context of future increases in fire occurrence and severity in a warming climate.

Sensitivity of the Weather Research and Forecast/Community Multiscale Air Quality modeling system to MODIS LAI, FPAR, and albedo

AbstractThis study aims to improve land surface processes in a retrospective meteorology and air quality modeling system through the use of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation and albedo products for more realistic vegetation and surface representation. MODIS leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and albedo are incorporated into the Pleim‐Xiu land surface model (PX LSM) used in a combined meteorology and air quality modeling system. The current PX LSM intentionally exaggerates vegetation coverage and LAI in western dry lands so that its soil moisture nudging scheme is more effective in simulating surface temperature and mixing ratio. Reduced vegetation coverage from the PX LSM with MODIS input results in hotter and dryer daytime conditions with reduced ozone dry deposition velocities in much of western North America. Evaluations of the new system indicate greater error and bias in temperature, but reduced error and bias in moisture with the MODIS vegetation input. Hotter daytime temperatures and reduced dry deposition result in greater ozone concentrations in the western arid regions even with deeper boundary layer depths. MODIS albedo has much less impact on the meteorology simulations than MODIS LAI and FPAR. The MODIS vegetation and albedo input does not have much influence in the east where differences in vegetation and albedo parameters are less extreme. Evaluation results showing increased temperature errors with more accurate representation of vegetation suggests that improvements are needed in the model surface physics, particularly the soil processes in the PX LSM.

Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000–2013)

Abstract. Accurate measurements and simulations of Greenland Ice Sheet (GrIS) surface albedo are essential, given the role of surface albedo in modulating the amount of absorbed solar radiation and meltwater production. In this study, we assess the spatio-temporal variability of GrIS albedo during June, July, and August (JJA) for the period 2000–2013. We use two remote sensing products derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as outputs from the Modèle Atmosphérique Régionale (MAR) regional climate model (RCM) and data from in situ automatic weather stations. Our results point to an overall consistency in spatio-temporal variability between remote sensing and RCM albedo, but reveal a difference in mean albedo of up to ~0.08 between the two remote sensing products north of 70° N. At low elevations, albedo values simulated by the RCM are positively biased with respect to remote sensing products by up to ~0.1 and exhibit low variability compared with observations. We infer that these differences are the result of a positive bias in simulated bare ice albedo. MODIS albedo, RCM outputs, and in situ observations consistently indicate a decrease in albedo of −0.03 to −0.06 per decade over the period 2003–2013 for the GrIS ablation area. Nevertheless, satellite products show a decline in JJA albedo of −0.03 to −0.04 per decade for regions within the accumulation area that is not confirmed by either the model or in situ observations. These findings appear to contradict a previous study that found an agreement between in situ and MODIS trends for individual months. The results indicate a need for further evaluation of high elevation albedo trends, a reconciliation of MODIS mean albedo at high latitudes, and the importance of accurately simulating bare ice albedo in RCMs.

Variability of Albedo and Utility of the MODIS Albedo Product in Forested Wetlands

Albedo was monitored over a two-year period (beginning April 2008) at three forested wetland sites in Florida, USA using up- and down-ward facing pyranometers. Water level, above and below land surface, is the primary control on the temporal variability of daily albedo. Relatively low reflectivity of water accounts for the observed reductions in albedo with increased inundation of the forest floor. Enhanced canopy shading of the forest floor was responsible for lower sensitivity of albedo to water level at the most dense forest site. At one site, the most dramatic reduction in daily albedo was observed during the inundation of a highly-reflective, calcareous periphyton-covered land surface. Satellite-based Moderate-Resolution Imaging Spectroradiometer (MODIS) estimates of albedo compare favorably with measured albedo. Use of MODIS albedo values in net radiation computations introduced a root mean squared error of less than 4.7 W/m2 and a mean, annual bias of less than 2.3 W/m2 (1.7%). These results suggest that MODIS-estimated albedo values can reliably be used to capture areal and temporal variations in albedo that are important to the surface energy balance.

Retrieval of land surface albedo and temperature using data from the Indian geostationary satellite: a case study for the winter months

The shortwave and longwave radiation budget at land surfaces is largely dependent on two fundamental quantities, the albedo and the land surface temperature (LST). A time series (November 2005 to March 2006) of daily data from the Indian geostationary satellite Kalpana‐1 Very High Resolution Radiometer (K1VHRR) sensor in the visible (VIS), water vapour (WV) and thermal infrared (TIR) bands from noontime (0900 GMT) observations were processed to retrieve these quantities in clear skies for five winter months. Cloud detection was carried out using bispectral threshold tests (in both VIS and TIR bands) in a dekadal time series. Surface albedo was retrieved using a simple atmospheric transmission model. K1VHRR albedo was compared with Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA noontime albedo over different land targets (agriculture, forest, desert, scrub and snow) that showed minimum differences over agriculture and forest. The comparison of spatial albedo over different landscapes yielded a root mean square deviation (RMSD) of 0.021 in VHRR albedo (9% of MODIS albedo). A mono‐window algorithm was implemented with a single TIR band to retrieve the LST. Its accuracy was also verified over different land targets by comparison with aggregated MODIS AQUA LST. The maximum RMSD was obtained over agriculture. Spatial comparison of VHRR and AQUA LSTs over homogeneous and heterogeneous landscape cutouts revealed an overall RMSD of 2.3 K. An improvement in the retrieval accuracy is expected to be achieved with atmospheric products from the sounder and split thermal bands in the imager of future INSAT 3D missions.

Validation of MODIS Albedo Products of Paddy Fields in Japan

A study was conducted in Chiba, Japan, to validate Moderate Resolution Imaging Spectroradiometer (MODIS) albedo products by taking the field measurements of shortwave band albedos in paddy fields. A large difference in spatial scale, from field-measured point data to 1-km resolution, complicates the validation process. To assess such effect of different spatial scales, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+) data were used. Spatial scale effects on the albedo were examined from three viewpoints: 1) comparison between point-based albedo and mean of albedo in homogeneous area; 2) comparison between point-based albedo and 1-km aggregated albedo; and 3) assessment of semivariogram of albedo in homogeneous area. In implementation of viewpoint 2), Liang's regression model was applied to convert ASTER reflectance into shortwave band albedo. The 1-km ASTER albedo was estimated using the point spread function, and in the same manner, 1-km ETM+ albedo was estimated. All results represent that an area around the measurement site can be assumed to be homogeneous, indicating negligible effects of spatial resolution difference during most of the periods. Comparison of ground-point-based albedos with MODIS actual albedo, estimated from MODIS black-sky albedo, white-sky albedo, and a fraction of diffuse skylight, showed that the accuracy of MODIS albedo products for paddy fields in Japan is within approximately 0.026 by absolute value (root-mean-square error) and 15.1% by relative value

A normalized description of the direct effect of key aerosol types on solar radiation as estimated from Aerosol Robotic Network aerosols and Moderate Resolution Imaging Spectroradiometer albedos

The interactions between aerosols and solar radiation are determined by a combination of aerosol properties (i.e., types), surface properties (i.e., albedo) and clouds. These determining factors vary for different regions. We examine how these differences contribute to the impact of aerosols on the top‐of‐atmosphere (TOA) and surface radiation. In this study, the AERONET (Aerosol Robotic Network) aerosol climatology is used, in conjunction with surface albedo and cloud products from Moderate Resolution Imaging Spectroradiometer (MODIS), to calculate the aerosol direct radiative effect (ADRE) and its normalized form (NADRE). The NADRE is defined as the ADRE normalized by optical depth at 550 nm and is mainly determined by internal aerosol optical properties and geographical parameters. These terms are evaluated for cloud‐free and cloudy conditions and for all‐mode and fine‐mode aerosols. Single‐scattering albedo is an important variable determining ADRE of biomass burning. Because of stronger absorption by the smoke over South Africa the average NADRE over South America is ∼35% larger at the TOA but ∼38% smaller at the surface than that over South Africa. The surface albedo is another important factor in determining ADRE, especially for mineral dust. As the surface albedo varies from ∼0.1 to ∼0.35, it is observed that the dust NADRE ranges from −44 to −17 Wm−2 τ−1 at the TOA and from −80 to −48 Wm−2 τ−1 at the surface over the Saharan deserts, Arabian Peninsula, and their surrounding oceans. We also find that the NADRE of fine‐mode aerosol is larger at the TOA but smaller at the surface in comparison to that of all‐mode aerosol because of its larger single‐scattering albedo and smaller asymmetry factor. Cloudy‐sky ADRE is usually not negligible for the observed cloud optical thickness, but the TOA ADRE with clouds is sensitive to the relative location of aerosols and cloud layer.

Characterizing the Spatial Variability of Broadband Albedo in a Semidesert Environment for MODIS Validation

Global data sets on land surface albedo will be one of the core products to be derived from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), part of NASA's Earth Observing System. Widespread acceptance of this product by the user communities is dependent, in part, on a comprehensive and rigorous programme of calibration and validation. Since the MODIS albedo product will be produced at a spatial resolution of 1 km, while measurements obtained from field instruments typically relate to areas of only a few tens of meters, this requires an understanding of the spatial variability of land surface albedo and a robust means of scaling up from field to satellite measurements. In this article, we examine these issues for a semidesert environment (the PROVE'97 field site at Jornada, New Mexico, USA). Spatial variations in field measurements of broadband albedo are related to the fractional ground cover of different scene elements (live and senescent vegetation, soil and shadow) via a simple linear mixture model. Information on the fractional ground cover of the scene elements is derived from ground-based hemispherical photography. It is shown that the albedo values predicted by the mixture model are accurate to within 2% of the corresponding measured values. This approach offers considerable potential for the validation of MODIS-derived albedo values through the use of spectral mixture modelling applied to fine spatial resolution satellite sensor images.