Multiangle Imaging Spectroradiometer Retrievals Research Articles

Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin

This study evaluates the long-term accuracy of six daily aerosol optical depth (AOD) datasets derived from the Moderate Resolution Imaging Spectroradiometers (MODIS) Dark Target (DT) at 3 and 10 km resolution, Deep Blue (DB), combined DT and DB datasets (DTB) and MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms and the Multi-angle Imaging SpectroRadiometer (MISR) Version 23, by comparing them with ground-based AOD observations in 18 Aerosol Robotic Network (AERONET) sites over the Amazon basin between 2000 and 2022. The AOD retrieval accuracy was also assessed under varying seasons, aerosol loading, particle size, elevation and land cover type. Overall results showed that Terra and Aqua-MODIS DB and MISR algorithms perform better, with about 88% of AOD retrievals within the expected error range. However, MISR presented a systematic high negative bias. MODIS DT 3 km overestimated AOD values and indicated unsatisfactory retrieval accuracy in almost all scenarios. MODIS and MISR retrievals showed improved performance under low aerosol loading, whereas Aqua-MODIS MAIAC under intermediate conditions (AOD>0.2). MISR indicated a large dependence on a coarse mode-dominated environment with considerable negative bias. Terra-MODIS MAIAC retrievals exhibited a smaller dependence for aerosol particle size distribution, while Terra-MODIS DB performed better for fine mode and Aqua-MODIS DB for coarse dominance. MAIAC also performed well under polluted scenarios in the dry season in contrast to the majority of satellite-based AOD retrievals, which showed good agreement under clean background conditions in the wet season. Almost all satellite-based retrievals showed higher uncertainty under extremely high altitudes (>3000 m) followed by non-satisfactory correlation and significant biases. Additionally, almost all satellite-based AOD retrievals indicated poor performance as vegetation coverage increases. On the contrary, MISR showed higher accuracy under forest type. In general, MODIS and MISR retrieval accuracy demonstrated distinct levels of dependencies that require further improvement in the Amazon Basin.

Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign

Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.

Understanding processes that control dust spatial distributions with global climate models and satellite observations

Abstract. Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD) simulated by the Community Earth System Model version 1 (CESM1) and version 2 (CESM2), the Energy Exascale Earth System Model version 1 (E3SMv1), and the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) against satellite retrievals from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multi-angle Imaging SpectroRadiometer (MISR). We find that CESM1, CESM2, and E3SMv1 underestimate dust transport to remote regions. E3SMv1 performs better than CESM1 and CESM2 in simulating dust transport and the northern hemispheric DOD due to its higher mass fraction of fine dust. CESM2 performs the worst in the Northern Hemisphere due to its lower dust emission than in the other two models but has a better dust simulation over the Southern Ocean due to the overestimation of dust emission in the Southern Hemisphere. DOD from MERRA-2 agrees well with CALIOP DOD in remote regions due to its higher mass fraction of fine dust and the assimilation of aerosol optical depth. The large disagreements in the dust extinction profiles and DOD among CALIOP, MODIS, and MISR retrievals make the model evaluation of dust spatial distributions challenging. Our study indicates the importance of representing dust emission, dry/wet deposition, and size distribution in GCMs in correctly simulating dust spatiotemporal distributions.

Improving MISR AOD Retrievals With Low-Light-Level Corrections for Veiling Light

Operational retrievals of aerosol optical depth (AOD) from Multi-angle Imaging SpectroRadiometer (MISR) data have been shown to have a high bias in pristine oceanic areas. One line of evidence involves comparison with Maritime Aerosol Network (MAN) observations, including the areas of low aerosol loading close to Antarctica. In this paper, a principal reason for the AOD overestimation is identified, which is stray light measured by the MISR cameras in dark regions of high-contrast scenes. A small fraction of the light from surrounding bright areas, such as clouds or sea ice, is redistributed to dark areas, artificially increasing their brightness. Internal reflections and light scattering from optical elements in MISR’s pushbroom cameras contribute to this veiling light effect. A simple correction model is developed that relies on the average scene brightness and an empirically determined set of veiling light coefficients for each MISR camera and wavelength. Several independent methods are employed to determine these coefficients. Three sets of coefficients are further implemented and tested in prototype MISR 4.4-km AOD retrievals. The results show dramatic improvements in retrieved AODs compared against MAN observations and the currently operational V22 MISR retrievals. For the best performing set of coefficients, the bias is reduced by 51%, from 0.039 to 0.019, the RMSE is lowered by 19%, from 0.062 to 0.050, and 84% of retrievals fall within the uncertainty envelope compared with 66% of retrievals in V22. The best performing set will be implemented operationally in the next V23 MISR AOD product release.

Development and assessment of a higher-spatial-resolution (4.4 km) MISR aerosol optical depth product using AERONET-DRAGON data

Abstract. Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been acquiring data that have been used to produce aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the current operational (Version 22) MISR algorithm performs well, with about 75 % of MISR AOD retrievals globally falling within 0.05 or 20 % × AOD of paired validation data from the ground-based Aerosol Robotic Network (AERONET). This paper describes the development and assessment of a prototype version of a higher-spatial-resolution 4.4 km MISR aerosol optical depth product compared against multiple AERONET Distributed Regional Aerosol Gridded Observations Network (DRAGON) deployments around the globe. In comparisons with AERONET-DRAGON AODs, the 4.4 km resolution retrievals show improved correlation (r = 0. 9595), smaller RMSE (0.0768), reduced bias (−0.0208), and a larger fraction within the expected error envelope (80.92 %) relative to the Version 22 MISR retrievals.

Assessing the accuracy of MISR and MISR‐simulated cloud top heights using CloudSat‐ and CALIPSO‐retrieved hydrometeor profiles

AbstractSatellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR‐E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle‐ and high‐altitude topped clouds agrees well between MISR retrievals and the MISR‐simulated output, with distributions of middle‐ and high‐topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low‐topped clouds between MISR retrievals and MISR‐simulated output that are due to differences in the detection of low‐level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low‐altitude cloud cover. The MISR‐simulated and MISR‐retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

Satellite assessment of sea spray aerosol productivity: Southern Ocean case study

AbstractDespite many years of observations by multiple sensors, there is still substantial ambiguity regarding aerosol optical depths (AOD) over remote oceans, in particular, over the pristine Southern Ocean. Passive satellite retrievals (e.g., Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and global aerosol transport models show a distinct AOD maximum around the 60°S latitude band. Sun photometer measurements performed by the Maritime Aerosol Network (MAN), on the other hand, indicate no increased AODs over the Southern Ocean. In this study elevated Southern Ocean AODs are examined from the modeling perspective. The primary aerosol component over the Southern Ocean is sea spray aerosol (SSA). Multiple simulations of SSA concentrations and optical depths are carried out using a single modeling framework, the Navy Aerosol Analysis and Prediction System (NAAPS) model. Several SSA emission functions are examined, including recently proposed formulations with sea surface temperature corrections. The differences between NAAPS simulations are primarily due to different SSA emission formulations. The results are compared against satellite‐derived AODs from the MISR and MODIS instruments. MISR and MODIS AOD retrievals are further filtered to eliminate retrievals potentially affected by cloud contamination and cloud adjacency effects. The results indicate a very large impact of SSA emission parameterization on the simulated AODs. For some scenarios, the Southern Ocean AOD maximum almost completely disappears. Further MISR and MODIS AOD quality screening substantially improves model/satellite agreement. Based on these comparisons, an optimal SSA emission function for global aerosol transport models is recommended.

Estimating PM2.5 in Xi'an, China using aerosol optical depth: A comparison between the MODIS and MISR retrieval models

Satellite measurements have been widely used to estimate particulate matter (PM) on the ground, which can affect human health adversely. However, such estimation from space is susceptible to meteorological conditions and may result in large errors. In this study, we compared the aerosol optical depth (AOD) retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) to predict ground-level PM2.5 concentration in Xi'an, Shaanxi province of northwestern China, using an empirical nonlinear model. Meteorological parameters from ground-based measurements and NCEP/NCAR reanalysis data were used as covariates in the model. Both MODIS and MISR AOD values were highly significant predictors of ground-level PM2.5 concentration. The MODIS and MISR models had overall comparable predictability of ground-level PM2.5 concentration and explained 67% and 72% of the daily PM2.5 concentration variation, respectively. Seasonal analysis showed that the MODIS and MISR models had overall comparable predictability of ground-level PM2.5 concentration, with the MISR model having a higher correlation coefficient (R) and thus giving a better fit in all seasons. The MISR model had high prediction accuracy in all seasons, with average R2 and absolute percentage error (APE) of 0.84 and 15.3% in all four seasons, respectively. The prediction of the MODIS model was best during winter (R2=0.83) with an APE of 19%, whereas it was relatively poor in spring (R2=0.56) with an APE of 21%. Further analysis showed that there was a significant improvement in correlation coefficient when using the nonlinear multiple regression model compared to using a simple linear regression model of AOD and PM2.5. These results are useful for assessing surface PM2.5 concentration and monitoring regional air quality.

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

Assessment of OMI near‐UV aerosol optical depth over land

AbstractThis is the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the near‐UV observations by the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. The OMI‐retrieved AOD by the UV aerosol algorithm (OMAERUV version 1.4.2) was evaluated using collocated Aerosol Robotic Network (AERONET) level 2.0 direct Sun AOD measurements over 8 years (2005–2012). A time series analysis of collocated satellite and ground‐based AOD observations over 8 years shows no discernible drift in OMI's calibration. A rigorous validation analysis over 4 years (2005–2008) was carried out at 44 globally distributed AERONET land sites. The chosen locations are representative of major aerosol types such as smoke from biomass burning or wildfires, desert mineral dust, and urban/industrial pollutants. Correlation coefficient (ρ) values of 0.75 or better were obtained at 50% of the sites with about 33% of the sites in the analysis reporting regression line slope values larger than 0.70 but always less than unity. The combined AERONET‐OMAERUV analysis of the 44 sites yielded a ρ of 0.81, slope of 0.79, y intercept of 0.10, and 65% OMAERUV AOD falling within the expected uncertainty range (largest of 30% or 0.1) at 440 nm. The most accurate OMAERUV retrievals are reported over northern Africa locations where the predominant aerosol type is desert dust and cloud presence is less frequent. Reliable retrievals were documented at many sites characterized by urban‐type aerosols with low to moderate AOD values, concentrated in the boundary layer. These results confirm that the near‐UV observations are sensitive to the entire aerosol column. A simultaneous comparison of OMAERUV, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue, and Multiangle Imaging Spectroradiometer (MISR) AOD retrievals to AERONET measurements was also carried out to evaluate the OMAERUV accuracy in relation to those of the standard aerosol satellite products. The outcome of the comparison indicates that OMAERUV, MODIS Deep Blue, and MISR retrieval accuracies in arid and semiarid environments are statistically comparable.

Evaluation of ERA-Interim and MERRA Cloudiness in the Southern Ocean

Abstract The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.

Aerosol optical depths over oceans: A view from MISR retrievals and collocated MAN and AERONET in situ observations

AbstractIn this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISR/MAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root‐mean‐square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISR/AERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground‐based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.

Comparison of GEOS‐Chem aerosol optical depth with AERONET and MISR data over the contiguous United States

Aerosol optical properties simulated by the global 3‐D tropospheric chemistry and transport model Goddard Earth Observing System (GEOS)‐Chem (GC) from 2008 to 2010 over the contiguous United States were evaluated with ground observations from Aerosol Robotic Network (AERONET) sites and aerosol products reported by the Multiangle Imaging Spectroradiometer (MISR). Overall, the correlation coefficient (r) and regression slope between AERONET and GC2° × 2.5° (2° latitude × 2.5° longitude) daily total column aerosol optical depth (AOD) were 0.6 and 0.51, respectively. After using the nested GC0.5° × 0.667° model to control for spatial variability, removing several outliers, and averaging over a monthly timescale, the agreement was significantly improved to an r of 0.84 and a slope of 0.75. Seasonal, hourly, and geographical statistics for GC0.5° × 0.667° and AERONET AODs show a similar data range and variation, with higher mean values in the summer, the evening, and in the eastern U.S. Smaller correlation coefficients are seen in the summer and winter, in the evening, and in the western U.S. To investigate the optical properties of major GC tracers, MISR level 2 aerosol products were used to calculate inorganic aerosol, dust, and absorbing non‐dust AOD. Both GC and MISR suggest that on average, inorganic aerosol has the highest AOD (GC: 0.071, MISR: 0.089) nationally, followed by absorbing non‐dust species (GC: 0.025, MISR: 0.041), and dust (GC: 0.013, MISR: 0.014). The large discrepancies in our intercomparison are due to GC underestimation of inorganic aerosol levels during all four seasons in the western U.S. and dust during summer in the eastern U.S., along with overestimation of summertime‐absorbing non‐dust species over the northwestern U.S. These uncertainties are attributed to underestimation of inorganic aerosol emissions in more polluted western regions, the transport of Sahara dust in the summer, misuse of the fire files, MISR retrieval uncertainties in the surface, and choice of aerosol models.

An assessment of cirrus heights from MISR oblique stereo using ground‐based radar and lidar at the Tropical Western Pacific ARM sites

We compare cirrus presence and heights (CTHs) using oblique stereo by the Multiangle Imaging SpectroRadiometer (MISR) with measurements from ground‐based cloud radar and lidar sensors at the Tropical Western Pacific (TWP) sites operated by the U.S. Department of Energy Atmospheric Radiation Measurement Program. Precise point‐wise comparisons, limited to only 195 coincident cases, showed that the total number of cirrus retrieved using oblique‐stereo analysis improved to 70% from 39% using the standard‐stereo technique. The stereo technique detects cloud with the highest contrast, which is often at lower altitude. The oblique‐stereo technique's efficiency depends on the thickness and number of underlying cloud layers. A histogram approach allowed similar regions to be compared statistically with many more samples and showed three distinct peaks at ≈13 km, 15 km, and 19 km related to deep convective clouds, tropical tropopause layer (TTL) cirrus, and overshooting convective clouds, respectively. Most differences between the satellite and ground‐based measurements resulted from a number of cases of invalid cloud comparisons (14%), blunders from edges and broken clouds (7%), low contrast stereo mismatches (4%), and under‐estimation of CTHs (3%). Overall, the oblique‐stereo analysis detected a cirrus‐top layer in 65% of all the valid coincident cases, mostly <1 km in thickness. The oblique‐stereo derived cirrus CTHs differed from the heights of cirrus‐top layers from ground‐based cloud radar and lidar by −0.5 ± 1.0 km, validating the MISR retrievals. This suggests global thin cirrus retrievals are possible with the oblique‐stereo technique after the screening of occasional blunders.

Comparison of MISR and Meteosat-9 cloud-motion vectors

[1] Stereo motion vectors (SMVs) from the Multiangle Imaging SpectroRadiometer (MISR) were evaluated against Meteosat-9 cloud-motion vectors (CMVs) over a one-year period. In general, SMVs had weaker westerlies and southerlies than CMVs at all latitudes and levels. The E-W wind comparison showed small vertical variations with a mean difference of −0.4 m s−1, −1 m s−1, −0.7 m s−1 and corresponding rmsd of 2.4 m s−1, 3.8 m s−1, 3.5 m s−1for low-, mid-, and high-level clouds, respectively. The N-S wind discrepancies were larger and steadily increased with altitude, having a mean difference of −0.8 m s−1, −2.9 m s−1, −4.4 m s−1 and rmsd of 3.5 m s−1, 6.9 m s−1, 9.5 m s−1at low, mid, and high levels. The best overall agreement was found in marine stratocumulus off Namibia, while differences were larger in the Tropics and convective clouds. The SMVs were typically assigned to higher altitudes than CMVs. Attributing each observed height difference to MISR and/or Meteosat-9 retrieval biases will require further research; nevertheless, we already identified a few regions and cloud types where CMV height assignment seemed to be the one in error. In thin mid- and high-level clouds over Africa and Arabia as well as in broken marine boundary layer clouds the 10.8-μm brightness temperature-based heights were often biased low due to radiance contributions from the warm surface. Contrarily, low-level CMVs in the South Atlantic were frequently assigned to mid levels by the CO2-slicing method in multilayer situations. We also noticed an apparent cross-swath dependence in SMVs, whereby retrievals were less accurate on the eastern side of the MISR swath than on the western side. This artifact was traced back to sub-pixel MISR co-registration errors, which introduced cross-swath biases in E-W wind, N-S wind, and height of 0.6 m s−1, 2.6 m s−1, and 210 m.

Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR

Red band bidirectional reflectance factor data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy reflectance model to provide maps of fractional crown cover (dimensionless), mean canopy height (m), and aboveground woody biomass (Mg ha − 1 ) on a 250 m grid. Model adjustment was performed after dynamic injection of a background contribution predicted via the kernel weights of a bidirectional reflectance distribution function (BRDF) model. Accuracy was assessed with respect to similar maps obtained with data from the NASA Multiangle Imaging Spectroradiometer (MISR) and to contemporaneous US Forest Service (USFS) maps based partly on Forest Inventory and Analysis (FIA) data. MODIS and MISR retrievals of forest fractional cover and mean height both showed compatibility with the USFS maps, with MODIS mean absolute errors (MAE) of 0.09 and 8.4 m respectively, compared with MISR MAE of 0.10 and 2.2 m, respectively. The respective MAE for aboveground woody biomass was ~ 10 Mg ha − 1 , the same as that from MISR, although the MODIS retrievals showed a much weaker correlation, noting that these statistics do not represent evaluation with respect to ground survey data. Good height retrieval accuracies with respect to averages from high resolution discrete return lidar data and matches between mean crown aspect ratio and mean crown radius maps and known vegetation type distributions both support the contention that the GO model results are not spurious when adjusted against MISR bidirectional reflectance factor data. These results highlight an alternative to empirical methods for the exploitation of moderate resolution remote sensing data in the mapping of woody plant canopies and assessment of woody biomass loss and recovery from disturbance in the southwestern United States and in parts of the world where similar environmental conditions prevail.

Validation of multi-angle imaging spectroradiometer aerosol products in China

Based on AErosol RObotic NETwork and Chinese Sun Hazemeter Network data, the Multi-angle Imaging SpectroRadiometer (MISR) level 2 aerosol optical depth (AOD) products are evaluated in China. The MISR retrievals depict well the temporal aerosol trend in China with correlation coefficients exceeding 0.8 except for stations located in northeast China and at the Lanzhou site. In general, the MISR AOD retrievals agree well with ground-based observations for AOD 0.5. The retrievals are systematically underestimated for AOD > 0.5 in the east, southwest and northeast regions of China. Concerning surface types, the greatest underestimations occur in farmland and forest ecosystems. The largest and smallest biases are seen in spring and in summer, respectively. The systematic underestimation seems to stem from the use of too high single scattering albedos ∼0.96 which is significantly higher than those estimated from ground-based observations. Further improvements to the MISR aerosol algorithm, especially in the aerosol model, are recommended.

Mineral dust plume evolution over the Atlantic from MISR and MODIS aerosol retrievals

We demonstrate how Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) space‐based aerosol products provide complementary information, characterizing (1) transported desert dust plume extent over water, (2) aerosol optical thickness (AOT) evolution, and (3) particle size sensitivity and fraction spherical evolution for the thicker parts of these plumes. MODIS provides more extensive coverage, whereas MISR's multiangle retrievals include dust properties and fill in areas where glint precludes MODIS optical depth retrievals, increasing by up to 50% dust plume surface area coverage compared to MODIS‐only observations. These results can be used to improve dust aerosol representations in climate, forecast, and transport models. Extensive comparison of MISR and MODIS AOT retrievals with Aerosol Robotic Network (AERONET) observations in dusty regions show accuracies of about 20%; MISR Angstrom exponent is predominantly less than 1, in reasonably good agreement with AERONET. For four selected North African dust transport events, combined MISR and MODIS observations map systematic changes in retrieved plume surface area, on the basis of AOT contours; these reflect differences in aerosol dispersion and removal rates that must be reproduced by models. Within MISR retrieval uncertainties, Angstrom exponent and AOT fraction spherical are lower in the optically thicker parts of the plume by up to 30% and increase as the plume is transported across the ocean, as would be expected; retrieved single‐scattering albedo values are ∼0.98 for all stages of plume evolution. For the cases studied, AERONET shows similar property patterns at points on either side of the Atlantic and indicates ∼15% decrease in aerosol coarse mode effective radius during transoceanic transport.

Comparison of marine stratocumulus cloud top heights in the southeastern Pacific retrieved from satellites with coincident ship‐based observations

In order to better understand the general problem of satellite cloud top height retrievals for low clouds, observations made by NOAA research vessels in the stratocumulus region in the southeastern Pacific during cruises in 2001 and 2003 to 2006 were matched with near‐coincident retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging SpectroRadiometer (MISR) instruments on the Terra satellite, along with a limited set of ISCCP 30‐km (DX) retrievals. The ISCCP cloud top heights, determined from the cloud top pressures, were found to be biased high by between 1400 and 2000 m within the limited comparison data set. Like the International Satellite Cloud Climatology Project (ISCCP) results, the MODIS retrievals were biased high by more than 2000 m, while the MISR retrievals had errors on the order of 230 to 420 m, with the wind corrected heights having almost no bias. The extremely large bias in the ISCCP and MODIS retrievals was traced to their reliance on low‐resolution observations or models of the atmospheric temperature structure. Cloud top height retrievals based on satellite cloud top temperatures and a constant atmospheric lapse rate agreed substantially better with the ship‐based measurements.

Toward unified satellite climatology of aerosol properties: Direct comparisons of advanced level 2 aerosol products

The development of a unified satellite climatology of aerosol properties requires accurate quantification and deep understanding of the underlying factors contributing to discrepancies between individual satellite products. In this paper we compare the most recent level 2 results obtained for coincident pixels viewed at essentially the same time by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) instruments flown on the EOS Terra platform. This strategy eliminates potential sampling effects and provides a virtually direct comparison of spatially and temporally collocated MODIS and MISR retrievals. We show that the MODIS and MISR Ångström exponent datasets reveal essentially no correlation. Although the corresponding aerosol optical thickness (AOT) datasets can agree worse than expected over the oceans, still the agreement is often satisfactory. However, the agreement over the land is often poor or even unacceptable. Of the collocated pixels for which there is a MODIS aerosol retrieval, only ∼40% or fewer pixels have a MISR aerosol retrieval, and vice versa. These findings further illustrate the complexity of the problem of aerosol retrievals from satellite observations and indicate that the creation of a meaningful unified MODIS–MISR aerosol climatology will be a nontrivial task.