Multi-angle Imaging SpectroRadiometer Products Research Articles

Non‐Gaussian Distributions of TOA SW Flux as Observed by MISR and CERES

AbstractThe Top of Atmosphere (TOA) shortwave (SW) flux, converted from Terra Multi‐angle Imaging SpectroRadiometer (MISR) narrow band albedos, is compared with that measured from Clouds and the Earth's Radiant Energy System (CERES). We describe the probability density function (PDF) of the monthly TOA SW flux and how the statistical third moment, skewness, can impact the quantification of the flux. The PDF of the SW flux is not normally distributed but positively skewed. In both sets of observations, the near‐global (80 S–80 N) median value of the SW flux is ∼3 W/m2 less than the mean value, due to the positive skewness of the distribution. The near‐global mean TOA SW flux converted from MISR is about 7 W/m2 (∼7%) less than CERES measured flux during the last two decades. Surprisingly, a hemispheric asymmetry exists with TOA SW observations from the Terra platform. SH reflects 3.92 and 1.15 W/m2 more mean SW flux than NH, from MISR and CERES Single Scanner Footprint products, respectively. We can infer that the offsetting by morning clouds in the SH is greater than the effect of hemispheric imbalance of SW flux caused by different land masses in two hemispheres. While the characteristics of the two SW fluxes broadly agree with each other, differences in the regional PDF from two different SW fluxes are substantial over high cloud regions and high altitude regions. Our analysis shows that some parts of the different skewness from the two measurements may be attributed to the different calibration of the radiance anisotropy over high cloud scenes.

Introducing the MISR level 2 near real-time aerosol product

Abstract. Atmospheric aerosols are an important element of Earth's climate system and have significant impacts on the environment and on human health. Global aerosol modeling has been increasingly used for operational forecasting and as support for decision making. For example, aerosol analyses and forecasts are routinely used to provide air quality information and alerts in both civilian and military applications. The growing demand for operational aerosol forecasting calls for additional observational data that can be assimilated into models to improve model accuracy and predictive skill. These factors have motivated the development, testing, and release of a new near real-time (NRT) level 2 (L2) aerosol product from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra platform. The NRT product capitalizes on the unique attributes of the MISR aerosol retrieval approach and product contents, such as reliable aerosol optical depth as well as aerosol microphysical information. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition of the satellite observations. Implications for the product quality and consistency are discussed and compared to the current operational L2 MISR aerosol product. Several ways of implementing additional use-specific retrieval screenings are also highlighted.

Characterization of Aerosol Type Over East Asia by 4.4 km MISR Product: First Insight and General Performance

AbstractThe lack of aerosol type information has largely hindered satellite products from further applications such as constraining model simulations and quantifying aerosol climate effects. The recent Version (V) 23 Multi‐angle Imaging Spectroradiometer (MISR) aerosol products with an enhanced spatial resolution at 4.4 km enable an unprecedented chance to explore aerosol types and associated processes in the regional scale. Here we provide a comprehensive insight into the characterization of MISR aerosol optical and microphysical properties, as well as their performance, over East Asia. Ground validation shows a remarkable improvement in the accuracy of V23 MISR aerosol optical depth (AOD) with ~80% of its retrieval bias within ±(0.05 + 20%AODAERONET). However, an underestimation of MISR AOD is still prevalent in the high‐AOD (>0.6) conditions, due to the surface‐atmosphere separation problem and insufficient absorbing aerosol mixtures being selected. MISR AOD of different size bins agrees well with AErosol RObotic NETwork (AERONET) results, demonstrating an evident advantage in discriminating natural dust from anthropogenic particles. Although MISR nonspherical and absorbing retrievals display a consistent variation with the AERONET inversions, their component AODs have a poor reliability over East Asia due to the inappropriate aerosol component models or their mixtures as in V22. In particular, the most striking problem is the sparse and discrete MISR absorbing retrievals with spatial discontinuity. Generally, the high‐resolution V23 MISR products exhibit a great potential in characterizing the regional variations of aerosol type, which can be further refined by considering the prior aerosol knowledge over East Asia.

MAIAC Thermal Technique for Smoke Injection Height From MODIS

We present a new algorithm to derive smoke plume height ( $\text{H}^{\mathrm {a}}$ ) using the thermal contrast from the rising mixture of aerosol and emitted gases in the Moderate Resolution Imaging Spectroradiometer (MODIS) 11- $\mu \text{m}$ channel. Validation shows good agreement with the wind-corrected Multi-angle Imaging SpectroRadiometer (MISR)-MISR Interactive Explorer (MINX) values, with about 60% of the MODIS Terra thermal retrievals within 500 m of MISR $\text{H}^{\mathrm {a}}$ and 450 m lower on average. The bias is expected because the thermal technique represents an effective rather than a top plume height from MISR MINX. The comparison of MODIS Aqua retrievals with Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP) Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations (CALIPSO) shows similar statistics, with a standard deviation of 458 m for the mean plume height and 216 m lower on average. $\text{H}^{\mathrm {a}}$ is part of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) MODIS Collection 6 suite of products (MCD19), accessible via the Land Product Distributed Active Archive Center (LP DAAC). Aerosol injection height is reported in the daily MAIAC atmospheric product MCD19A2 along with the cloud mask (CM), column water vapor, aerosol optical depth (AOD), AOD uncertainty, and aerosol type, at 1-km resolution on a global sinusoidal grid. Despite some limitations, the vastly increased coverage from MODIS observations makes it a valuable data set complementing the established MISR and CALIOP products.

Assessment and Improvement of MISR Angstrom Exponent and Single-Scattering Albedo Products Using AERONET Data in China

Mapping the components, size, and absorbing/scattering properties of particle pollution is of great interest in the environmental and public health fields. Although the Multi-angle Imaging SpectroRadiometer (MISR) can detect a greater number of aerosol microphysical properties than most other spaceborne sensors, the Angstrom exponent (AE) and single-scattering albedo (SSA) products are not widely utilized or as robust as the aerosol optical depth (AOD) product. This study focused on validating MISR AE and SSA data using AErosol RObotic NETwork (AERONET) data for China from 2004 to 2014. The national mean value of the MISR data (1.08) was 0.095 lower than that of the AERONET data. However, the MISR SSA average (0.99) was significantly higher than that of AERONET (0.89). In this study, we developed a method to improve the AE and SSA by narrowing the selection of MISR mixtures via the introduction of the following group thresholds obtained from an 11-year AERONET dataset: minimum and maximum values (for the method of MISR_Imp_All) and the top 10% and bottom 10% of the averaged values (for MISR_Imp_10%). Overall, our improved AE values were closer to the AERONET AE values, and additional samples (MISR_Imp_All: 28.04% and 64.72%, MISR_Imp_10%: 34.11% and 73.13%) had absolute differences of less than 0.1 and 0.3 (defined by the expected error tests, e.g., EE_0.1) compared with the original MISR product (18.46% and 50.23%). For the SSA product, our method also improved the mean, EE_0.05, and EE_0.1 from 0.99, 16.13%, and 56.45% (MISR original product) to 0.96, 40.32%, and 70.97% (MISR_Imp_All), and 0.94, 54.84%, and 90.32% (MISR_Imp_10%), respectively.

Direct Estimation of Land Surface Albedo From Simultaneous MISR Data

The availability of multiangular information from the NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument provides an excellent opportunity for the characterization of surface anisotropy, which can be used for improving surface albedo estimation. However, the MISR data have been reported with large uncertainties and data gaps due to inaccurate aerosol estimation and/or cloud masking limiting its otherwise broader applications. To mitigate these issues, two approaches were proposed to estimate land surface albedo directly from surface reflectance (LSA_sfc) and Top-of-Atmosphere reflectance (LSA_toa), respectively. As a further development of the traditional albedo algorithms, this is the first attempt to simultaneously utilize multispectral and multiangular information in surface albedo estimation without any prior constraining information. Validations at AmeriFlux sites show that the proposed algorithms can achieve accuracies similar to that of the MISR product with respective bias and RMSE of 0.004 and 0.032 for LSA_sfc and 0.005 and 0.032 for LSA_toa algorithms. We found that the LSA_toa algorithm can significantly reduce data gaps and provide accurate surface albedo retrievals with two to three times more valid data than the current MISR product. In addition, these approaches can be easily applied to other optical sensors to produce accurate and gap-free clear-sky surface albedo estimations. The results of this paper also highlight the importance of having two to three simultaneous observations with sufficient angular sampling, which can improve albedo accuracy and reduce data gaps.

Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model

AbstractBy evaluating quality‐assured Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT), MODIS Deep Blue (DB), Multiangle Imaging Spectroradiometer (MISR), and Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products assimilated into the U. S. Navy Aerosol Analysis and Prediction System (NAAPS), the impact of single‐sensor and multisensor data assimilation on aerosol optical depth (AOD) analysis and forecast skill is characterized using ground‐based Level 2 Aerosol Robotic Network (AERONET) data sets during the 2007 boreal summer (June–August 2007). The single‐sensor assimilation experiment suggests that all products tested can improve NAAPS performance on a regional or a global scale. The multisensor assimilation experiment suggests that model improvement is greatest with the combined use of Terra and Aqua MODIS DT products, largely due to data density. Incremental improvements are identified, as a function of data density, over regions such as the Saharan desert when adding MISR and MODIS DB products. The inclusion of CALIOP data is mass‐neutral by definition and has an insignificant impact on the NAAPS 00 h analysis. CALIOP assimilation does improve the 48 h forecast from NAAPS due to more accurate 00 h vertical distribution and hence forecasted advection. Root‐mean‐square errors exceeding 0.1 are found over East Asia and North Africa for both the NAAPS analysis and satellite AOD data, indicating that satellite aerosol products in these two regions need improvement. Similarly, low correlation is found between NAAPS and AERONET over Australia, even with the use of all available satellite aerosol products, suggesting that more detailed examination of some critical regions is necessary.

Expanding MISR LAI Products to High Temporal Resolution With MODIS Observations

The Multi-Angle Imaging Spectroradiometer (MISR) is a powerful sensor for leaf area index (LAI) mapping with its simultaneous multi-angle observations. However, the LAI product derived from MISR observations has low temporal resolution, which is unsatisfactory for many applications. This paper presents an algorithm that expands the MISR LAI product to high temporal resolution with the aid of Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm establishes relationships between the MISR LAI and the MODIS red/near-infrared band ratio (simple ratio (SR)) pixel by pixel using coincident data of these two sensors for the past nine years. Using these pixel-based SR-LAI relationships, a new LAI product with the merits of the original MISR product and high temporal resolution is obtained from MODIS surface reflectance. The expanded LAI series was compared with the original MISR and MODIS LAI products, as well as field LAI measurements made at the Baohe and Maoershan forest sites and the Hulunbeier grassland site, to assess the algorithm's performance. The results show that the temporal coverage of the MISR LAI improved from 15.5% to 65.2% in an 8-day composite, and the mean root-mean-square error is 0.74 for the vegetated pixels. This LAI product has similar temporal consistency and seasonal dynamics to the existing MODIS LAI product generated from the main algorithm, but is more robust against the low quality of reflectance inputs. The expanded LAI product differs with field measurements by about 11.5%, with agreement to field observations at all three sites within an accuracy of 0.8 LAI.

Global-Scale Comparison of MISR and MODIS Land Surface Albedos

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky surface albedos are compared with similar products generated on the basis of the Multiangle Imaging SpectroRadiometer (MISR) surface bidirectional reflectance factor (BRF) model parameters available for the year 2005. The analysis is achieved using global-scale statistics to characterize the broad patterns of these two independent albedo datasets. The results obtained in M. Taberner et al. have shown that robust statistics can be established and that both datasets are highly correlated. As a result, the slight but consistent biases and trends identified in this paper, derived from statistics obtained on a global basis, should be considered sufficiently reliable to merit further investigation. The present paper reports on the zonal- and seasonal-mean differences retrieved from the analysis of the MODIS and MISR surface albedo broadband products. The MISR − MODIS differences exhibit a systematic positive bias or offset in the range of 0.01–0.03 depending on the spectral domain of interest. Results obtained in the visible domain exhibit a well-marked and very consistent meridional trend featuring a “smile effect” such that the MISR − MODIS differences reach maxima at the highest latitudes in both hemispheres. The analysis of seasonal variations observed in MISR and MODIS albedo products reveals that, in the visible domain, the MODIS albedos generate weaker seasonal changes than MISR and that the differences increase poleward from the equatorial regions. A detailed investigation of MODIS and MISR aerosol optical depth retrievals suggests that this large-scale meridional trend is probably not caused by differences in the aerosol load estimated by each instrument. The scale and regularity of the meridional trend suggests that this may be due to the particular sampling regime of each instrument in the viewing azimuthal planes and/or approximations in the atmospheric correction processes. If this is the case, then either MODIS is underestimating, or MISR overestimating, the surface anisotropy or both.

Comparison of MISR and MODIS land surface albedos: Methodology

The broadband white sky surface albedo (bihemispherical reflectance) products available from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared at regional and continental scales with similar products generated from the Multiangle Imaging Spectroradiometer (MISR) land surface bidirectional reflectance factor (BRF) parameters. This paper describes the methodology applied to derive MISR white sky albedos over four spectral broadbands of interest, namely, 0.3–0.7 μm, 0.4–1.1 μm, 0.7–3.0 μm, and 0.3–3.0 μm, as well as an evaluation of the strategy adopted to compare the MODIS and MISR products. The results are very encouraging since the two data sets show very good statistical agreement over large areas and over a full year of measurements, despite the many differences that exist in the suite of algorithms applied to retrieve these surface quantities from each of these instruments separately.

Relationship of MISR RPV parameters and MODIS BRDF shape indicators to surface vegetation patterns in an Australian tropical savanna

The global coverage of bidirectional reflectance distribution function (BRDF) products from the Multi-angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) has the potential to provide quantitative information on surface vegetation structure for input to process modelling and model–data assimilation schemes for regional and biome-scale assessment of carbon dynamics. The relationship of MISR Rahman–Pinty–Verstraete (RPV) model parameters, derived from inversion of MISR 275 m fine mode data, and BRDF shape indicators calculated from the latest MODIS 500 m MCD43 BRDF product to vegetation patterns in an Australian tropical savanna was examined for a time series covering the dry season period from April to October 2005. The bidirectional reflectance products were compared with geographical information system (GIS) data coverage combining floristic polygons with Landsat thematic mapper (TM) based estimates of canopy cover and height classes. The analysis showed that both the MISR RPV asymmetry parameter Θ and several MODIS BRDF shape indicators constructed using the red band were sensitive to local-scale anisotropic scattering and thus vegetation structure. The MISR RPV asymmetry parameter Θ showed consistent variation between grasslands, forest (closed canopies), and more open tree–grass mixtures over time. The MODIS indicators such as NDHD-R and ANIF-R produced distinctly different temporal profiles for major vegetation types such as rainforest, Melaleuca woodland, and Dichanthium grassland. These indices also showed evidence of consistent discrimination between eucalypt savanna types that varied in canopy cover and tree height. A clumping index calculated from NDHD-R for a single period (day 177 in a time series) showed good correspondence with savanna vegetation canopy properties but was insensitive to dense canopy rainforest vegetation. These results indicate there is potential for both MISR and MODIS BRDF products to provide a quantitative description of vegetation types in global tree–grass systems. However, there is a pressing need for further study to calibrate the responses with fine-scale structural data derived from both field measurement and light detection and ranging (lidar).

Analysis of multi-date MISR measurements for forest and woodland communities, Queensland, Australia

Many theoretical and applied studies have demonstrated that the anisotropic reflectance of the land surface is determined by the structural and optical properties of the land surface. The Multi-angle Imaging SpectroRadiometer (MISR) measures the anisotropic reflectance of the land surface thus has the potential to improve the operational mapping of canopy attributes in Queensland, one of the largest states in Australia. The aim of this study was to assess the relationship between foliage projective cover (FPC) and the shape of the bidirectional reflectance distribution function (BRDF) for a mixed grassland/woodland ecosystem, the Southern Brigalow Belt Biogeographic Region. A practical approach for deriving the surface bidirectional reflectance factor (BRF) from MISR “Local" mode data using existing MISR products is presented. The BRDF typology of the land surface was determined using shape parameters derived from inversion of the linear Ross–Thick Li–Sparse Reciprocal and the non-linear Rahman–Pinty–Verstraete (RPV) models against a time series of MISR “Local" mode surface BRF data. Following an evaluation of the models inversion error, the RPV model was examined for correlation with FPC, a canopy attribute routinely derived from Landsat data in Queensland. Our empirical analyses showed the MISR derived RPV model parameters were qualitatively related to spatial and temporal variations in vegetation structure in Queensland and the k parameter contained information independent of FPC. These results are consistent with published findings from other regions.

Analysis of the MISR LAI/FPAR product for spatial and temporal coverage, accuracy and consistency

The Multi-angle Imaging SpectroRadiometer (MISR) instrument provides global imagery at nine discrete viewing angles and four visible/near-infrared spectral bands. MISR standard products include green leaf area index (LAI) of vegetation and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). This paper describes the research basis for transitioning the MISR LAI/FPAR products from provisional to validation status. The efforts included not only comparisons to field data but also analyses of relationships, consistency and complementarity between various MISR products derived by independent algorithms. For example, we show how the energy absorbed by the ground below vegetation can be estimated from two independent MISR products, FPAR and BHRPAR (bi-hemispheric reflectance at PAR wavelengths). Further, we show that this information can be used to derive at least three measures of canopy structure — Beer's law extinction coefficient, mean leaf inclination and the gap fraction or vegetation ground cover. The spatial and temporal coverage of the LAI/FPAR product is mainly limited by cloud contamination. However, when a successful aerosol retrieval is performed, typically 95% of pixels have surface reflectance retrievals suitable as input to the LAI/FPAR algorithm. The algorithm provides LAI/FPAR retrievals in 50–80% of these pixels with suitable input. The early versions of the algorithm overestimated LAI values in grasses and broadleaf crops. The MISR LAI product from the recalibrated algorithm (version 3.3) is assessed by comparison with field data collected in a 3 × 3 km agricultural area (grasses and cereal crops) near Avignon, France. LAI retrievals in other biomes are compared to MODIS LAI product of known accuracy. The MISR LAI product shows structural and phenological variability in agreement with data. Our results suggest that the product is accurate to within 0.66 LAI in herbaceous vegetation and savannas and is an overestimate by about 1 LAI in broadleaf forests. LAI retrievals over needle leaf forests remain at provisional quality level.

MISR Calibration and Implications for Low-Light-Level Aerosol Retrieval over Dark Water

Abstract Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol layer is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident, AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method’s accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but are too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward-viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

Statistical comparison of MISR, ETM+ and MODIS land surface reflectance and albedo products of the BARC land validation core site, USA

The Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautics and Space Administration (NASA)'s Earth Observing System (EOS) Terra satellite are crucial for generation of other products such as the Fraction of Photosynthetically Active Radiation (FPAR) and Leaf Area Index (LAI). The analysis reported here compares the reflectance and albedo products from MODIS (MOD09 and MOD43B3), MISR and Landsat Enhanced Thematic Mapper (ETM)+ data using general statistical methods. Four MISR land surface products are examined: hemispherical–directional reflectance factors (HDRF), bidirectional reflectance factors (BRF), bi-hemispherical reflectance (BHR) and directional–hemispherical reflectance (DHR). Ground measurements were used to validate ETM+ reflectance and albedo products (30 m) which were then upscaled and compared with MISR products (1.1 km). The results from 11 May 2000, 5 December 2000 and 22 January 2001 show that: (1) under clear-sky conditions, MISR BRF and HDRF, BHR and DHR are nearly the same (R 2>99%); (2) there are strong correlations between ETM+ surface reflectance and MISR nadir-view BRF; however, the relationship is affected by the cloud, snow and shadow; (3) in clear areas, MISR BRF is similar to MOD09, but is greater for the haze and snow regions and smaller for shadows; and (4) the MISR albedo product is closely related to the ETM+ and, to a lesser extent, MODIS.