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NASA NTRS2012

Evaluation of Moderate-Resolution Imaging Spectroradiometer (MODIS) Snow Albedo Product (MCD43A) over Tundra

This study assesses the MODIS standard Bidirectional Reflectance Distribution Function (BRDF)/Albedo product, and the daily Direct Broadcast BRDF/Albedo algorithm at tundra locations under large solar zenith angles and high anisotropic diffuse illumination and multiple scattering conditions. These products generally agree with ground-based albedo measurements during the snow cover period when the Solar Zenith Angle (SZA) is less than 70deg. An integrated validation strategy, including analysis of the representativeness of the surface heterogeneity, is performed to decide whether direct comparisons between field measurements and 500- m satellite products were appropriate or if the scaling of finer spatial resolution airborne or spaceborne data was necessary. Results indicate that the Root Mean Square Errors (RMSEs) are less than 0.047 during the snow covered periods for all MCD43 albedo products at several Alaskan tundra areas. The MCD43 1- day daily albedo product is particularly well suited to capture the rapidly changing surface conditions during the spring snow melt. Results also show that a full expression of the blue sky albedo is necessary at these large SZA snow covered areas because of the effects of anisotropic diffuse illumination and multiple scattering. In tundra locations with dark residue as a result of fire, the MODIS albedo values are lower than those at the unburned site from the start of snowmelt.

Wang, Zhuosen↗

NASA NTRS2017

GEO-LEO Reflective Band Inter-Comparison with BRDF and Atmospheric Scattering Corrections

The inter-comparison of the reflective solar bands (RSB) between the instruments onboard a geostationary orbit satellite and a low Earth orbit satellite is very helpful in assessing their calibration consistency. Himawari-8 was launched 7 October 2014 and GOES-R was launched on 19 November 2016. Unlike previous GOES instruments, the Advanced Himawari Imager (AHI) on Himawari-8 and the Advanced Baseline Imager (ABI) on GOES-R have onboard calibrators for the RSB. Independent assessment of calibration is nonetheless important to enhance their product quality. MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) can provide good references for sensor calibration. In this work, the inter-comparison between AHI and VIIRS is performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with accurate adjustment for band spectral difference, reduction of impact from pixel mismatching, and consistency of BRDF (Bidirectional Reflectance Distribution Function) and atmospheric correction. The site used is the Strzelecki Desert in Australia. Due to the difference in solar and view angles, two corrections must be applied in order to compare the measurements. The first is the atmospheric scattering correction applied to the top of atmosphere reflectance measurements. The second correction is applied to correct the BRDF effect. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) model and the BRDF correction is performed using a semi-empirical model. Our results show that AHI band 1 (0.47 microns) has a good agreement with VIIRS band M3 within 0.15 percent. AHI band 5 (1.61 microns) shows the largest difference (5.09 percent) with VIIRS band M10, while AHI band 5 shows the least difference (1.87 percent) in comparison with VIIRS band I3. The methods developed in this work can also be directly applied to assess GOES-16/ABI (Geostationary Operational Environment Satellite16 / Advanced Baseline Imager) calibration consistency, a topic we will address in the future.

The inter-comparison of the reflective solar bands↗

NASA NTRS2016

BRDF Characterization and Calibration Inter-Comparison between Terra MODIS, Aqua MODIS, and S-NPP VIIRS

The inter-comparison of reflective solar bands (RSB) between Terra MODIS, Aqua MODIS, and SNPP VIIRS is very important for assessment of each instrument's calibration and to identify calibration improvements. One of the limitations of using their ground observations for the assessment is a lack of the simultaneous nadir overpasses (SNOs) over selected pseudo-invariant targets. In addition, their measurements over a selected Earth view target have significant difference in solar and view angles, and these differences magnify the effects of Bidirectional Reflectance Distribution Function (BRDF). In this work, an inter-comparison technique using a semi-empirical BRDF model is developed for reflectance correction. BRDF characterization requires a broad coverage of solar and view angles in the measurements over selected pseudo-invariant targets. Reflectance measurements over Libya 1, 2, and 4 desert sites from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for the calibration difference between the two instruments. The BRDF coefficients for three desert sites for MODIS bands 1 to 9 are derived and the wavelength dependencies are presented. The analysis and inter-comparison are for MODIS bands 1 to 9 and VIIRS moderate resolution radiometric bands (M bands) M1, M2, M4, M5, M7, M8, M10 and imaging bands (I bands) I1-I3. Results show that the ratios from different sites are in good agreement. The ratios between Terra and Aqua MODIS from year 2003 to 2014 are presented. The inter-comparison between MODIS and VIIRS are analyzed for year 2014.

Chang, Tiejun↗

NASA NTRS2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗

NASA NTRS2000

BOREAS RSS-19 1994 Seasonal Understory Reflectance Data

The BOREAS RSS-19 team collected airborne remotely sensed images and ground reflectance data for characterizing the radiometric properties of the boreal forest landscape. One objective of BOREAS is to further the understanding of the spectral bidirectional reflectance of typical boreal ecosystem stands in the visible/near-infrared regime. An essential input for any canopy BRDF model is an accurate estimate of the average understory reflectance, both for sunlit and shaded conditions. These variables can be expected to vary seasonally because of species-dependent differences in the phenological cycle of foliar display. In response to these requirements, the average understory reflectance for the flux tower sites of both the NSA (Thompson, Manitoba) and the SSA (Candle Lake, Saskatchewan) was observed throughout the year during five field campaigns. This was done by measuring the nadir reflectance (400 to 850 nm) of sunlit and shaded understory (vegetation and snow cover) along a surveyed LAI transect line (Chen, RSS-07) at each site near solar noon and documenting an average site reflectance. Comparisons between sites reveal differences in the green and infrared regions of the spectra, because of the differing species in the understory for each site. Temporal (seasonal) variation for each site was also observed (06-Feb-1994 to 16-Sep-1994), indicating the changing flora mixtures and changing spectral signatures as the understory matures during the growing season. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Miller, John R.↗

NASA NTRS2013

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

MODIS↗

NASA NTRS2016

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

Ambeau, Brittany L.↗

NASA NTRS2005

NASA's Next Generation Sunphotometer for Ground-based Remote Sensing Applications

Atmospheric aerosol concentrations and their optical properties, in terms of which cause differential warming/cooling effects in the atmosphere and on the surface, constitute one of the largest sources of uncertainty in current assessments and predictions of global climatic change. This is especially true over the regions of bright-reflecting surface, such as desert and urban areas. Under the name of AERONET since the 90's, Cimel's sunphotometers have been deployed worldwide as the standard instrument for aerosol monitoring network, developed to support NASA, CNES, and NASDA's Earth satellite systems. PREDE's skyradiometers, as deployed in SKYNET, serve the similar role. One of the key ingredients for achieving accurate aerosol retrievals from satellite observations is comprehensive understanding of surface spectral BRF's (Bidirectional Reflectance Factors), defined as a ratio of radiance measurements reflected from a targeted surface and from a spectral-angular featureless referencing plate. Although the weather-resistant, automatic, sun/sky-scanning spectroradiometers enable Frequent measurements of atmospheric aerosol optical properties and precipitable water at remote sites, they are too slow for surface BRF measurements (20-25 seconds per 360 degree scan, in addition to filter wheel rotation time). We have designed a next generation sun photometer whose sensor head has no moving parts. A dedicated detector for each channel enables 12 simultaneous measurements ranging from the UV (380 nm) to shortwave-IR (2.13 micron) regions. The scan platform will be capable of traveling 360 degrees in about 6 seconds. This is sufficient to finish a BRDF scan every 30 degrees in azimuth and 15 degrees in elevation in less than 4 minutes. More details about this instrument will be presented, together with its applications to the aerosol and trace gas studies. The current plan for this instrument is to deploy during the EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment).

Shu, Peter K.↗

NASA NTRS2016

Effect of Satellite Formations and Imaging Modes on Global Albedo Estimation

We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5deg of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly (Delta)V per satellite.

BRDF↗

NASA NTRSDate not supplied

Characterization of Modern Spacecraft Materials under Space-simulated Environment

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that will be launched as a part of the Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022. MISSE-FF flight sample collection comprises different classes of polymers, including polyimides from the Kapton family, manufactured by E.I du Pont de Nemours and Co., Polyethylene terephthalate (PET) materials, liquid crystal polymers, PI/Polyhedral Oligomeric Silsesquioxanes (POSS), and carbon and glass fiber reinforced polymers. A sequential exposure approach was undertaken to allow monitoring of degradation induced by each environmental component (electrons, AO, and VUV) separately. Surface morphology, optical, and charge transport properties of selected materials were characterized using different techniques, namely, atomic force and scanning electron microscopy, ultraviolet visible (UV/Vis) transmission, reflectance, Bidirectional Reflectance Distribution Function (BRDF), and surface potential decay measurements.

Elena Plis↗

NASA NTRSDate not supplied

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI will provide two day global coverage of TOA radiances. Unlike its predecessors, OCI will cover a spectral range from 340nm to 2260nm. Below 900nm, OCI will include two spectrometers that continuously span the ultraviolet to 600nm and 600nm to near-infrared spectral regions to provide hyperspectral radiances sampled every 2.5 nm, with a bandwidth of 5 nm for each channel. Wavelengths above 900nm are measured in seven discrete multispectral bands of varying bandwidths, six of which are at similar wavelengths to those on heritage missions to support both atmospheric and ocean color applications. Nominal spatial resolution is similar to the SeaWiFS instrument with 1050 m at nadir. As for SeaWiFS, the pixel size increases due to a ~20 degree tilt and as a function of scan angle. Variations in the radiometric sensitivity of each OCI channel over time will be monitored by solar diffuser measurements for short term instrument gain adjustments and independent lunar measurements for trend adjustments of long time periods, similar to the approach employed for the VIIRS instrument [4]. The OCI flight-unit was built at NASA’s Goddard Space Flight Center. At the time of this writing, OCI has completed on-orbit commissioning activities and normal science operations have begun. A key aspect of the OCI architecture is the capability to trend absolute and relative calibration changes over the course of mission life with solar calibration. Every 24 hours, the PACE spacecraft performs an inertial hold as the ground track nears the North Pole which orients a Quasi-Volume Diffuser (QVD) mounted on OCI towards the sun. By knowing the irradiance of the sun and the reflectivity of the target, the absolute radiance at the input to the OCI aperture can be computed as OCI scans the target. The allowable absolute uncertainty budget for each solar calibration measurement is 1.6% 1-sigma below 900nm at beginning of life (BOL) and the allowable relative uncertainty budget is ~0.26% 1-sigma. The Solar Calibration Assembly (SCA) consists of three targets selectable via a single mechanism which also opens a door. The targets consist of a Daily Bright Target (DBT), Monthly Bright Target (MBT), and Daily Dim Target (DDT). The bright targets are quartz QVDs with the monthly target being used to track the degradation of the daily target. The dim target is used to track CCD linearity using Progressive Time-Delay Integration (PTDI). A composite baffle is attached to the SCA housing aperture to block Earth shine and stray light from the spacecraft. The SCA assembly is mounted to a view port ~90° from OCI nadir. This paper provides an overview of driving solar calibration requirements, error-budgets and early trade studies which drove the solar calibration assembly (SCA) architecture and on-orbit maneuver. Measurements of the diffuser Bidirectional Reflectance Distribution Function (BRDF) at TNO, Netherlands and GSFC are briefly described. Optical modelling and test results at the sub-system and instrument level are included. Finally, preliminary measurements on-orbit are compared to pre-launch predictions.

Joseph J Knuble↗

NASA NTRSDate not supplied

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

ocean color↗

NASA NTRS2020

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗

NASA NTRS2016

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 x AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

Choi, Myungje↗

NASA NTRS2012

Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-based Estimates of Surface Albedo

The quantification of uncertainty of global surface albedo data and products is a critical part of producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A current challenge in validating satellite retrievals of surface albedo is the ability to overcome the spatial scaling errors that can contribute on the order of 20% disagreement between satellite and field-measured values. Here, we present the results from an uncertain ty analysis of MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat albedo retrievals, based on collocated comparisons with tower and airborne multi-angular measurements collected at the Atmospheric Radiation Measurement Program s (ARM) Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLAS33 IC 07). Using standard error propagation techniques, airborne measurements obtained by NASA s Cloud Absorption Radiometer (CAR) were used to quantify the uncertainties associated with MODIS and Landsat albedos across a broad range of mixed vegetation and structural types. Initial focus was on evaluating inter-sensor consistency through assessments of temporal stability, as well as examining the overall performance of satellite-derived albedos obtained at all diurnal solar zenith angles. In general, the accuracy of the MODIS and Landsat albedos remained under a 10% margin of error in the SW(0.3 - 5.0 m) domain. However, results reveal a high degree of variability in the RMSE (root mean square error) and bias of albedos in both the visible (0.3 - 0.7 m) and near-infrared (0.3 - 5.0 m) broadband channels; where, in some cases, retrieval uncertainties were found to be in excess of 20%. For the period of CLASIC 07, the primary factors that contributed to uncertainties in the satellite-derived albedo values include: (1) the assumption of temporal stability in the retrieval of 500 m MODIS BRDF values over extended periods of cloud-contaminated observations; and (2) the assumption of spatial 45 and structural uniformity at the Landsat (30 m) pixel scale.

Roman, Miguel O.↗