Response to "Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET"

A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD) products, and reports much poorer agreement than that obtained by the instrument teams and others. We trace the reasons for the discrepancies primarily to differences in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account

A Study of 15-Year Aerosol Optical Thickness and Direct Shortwave Aerosol Radiative Effect Trends using MODIS, MISR, CALIOP and CERES

By combining Collection 6 Moderate Resolution and Imaging Spectroradiometer (MODIS) and Version 22 Multi-angle Imaging Spectroradiometer (MISR) aerosol products with Cloud and Earth’s Radiant Energy System (CERES) flux products, the aerosol optical thickness (AOT, at 0.55 µm) and shortwave (SW) aerosol radiative effect (SWARE) trends are studied over ocean for the near-full Terra (2000–2015) and Aqua (2002–2015) data records. Despite differences in sampling methods, regional SWARE and AOT trends are highly correlated with one another. Over global oceans, weak SWARE (cloud-free SW flux) and AOT trends of 0.5–0.6 Wm−2 (−0.5 to −0.6 Wm−2 ) and 0.002 AOT decade−1 are found using Terra data. Near-zero AOT and SWARE trends are also found for using Aqua data, regardless of the angular distribution models (ADMs) used. Regionally, positive AOT and cloud-free SW flux (negative SWARE) trends are found over the Bay of Bengal, the Arabian Sea, the Arabian/Persian Gulf and the Red Sea, while statistically significant negative trends are derived over the Mediterranean Sea and the eastern US coast. In addition, the global mean instantaneous SW aerosol direct forcing efficiencies are found to be ∼ −60 Wm−2 AOT−1 , with corresponding SWARE values of ∼ −7 Wm−2 from both Aqua and Terra data, again regardless of CERES ADMs used. Regionally, SW aerosol direct forcing efficiency values of ∼ −40 Wm−2 AOT−1 are found over the southwest coast of Africa where smoke aerosol particles dominate in summer. Larger (in magnitude) SW aerosol direct forcing efficiency values of −50 to −80 Wm−2 AOT−1 are found over several other dust- and pollutant-aerosol-dominated regions. Lastly, the AOT and SWARE trends from this study are also intercompared with aerosol trends (such as active-based ones) from several previous studies. Findings suggest that a cohesive understanding of the changing aerosol skies can be achieved through the analysis of observations from both passive- and active-based analyses, as well as from both narrowband and broadband datasets

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: Part III. Using Combined PCA to Compare Spatiotemporal Variability of MODIS, MISR and OMI Aerosol Optical Depth

Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR

An Investigation Of Particulate Matter Air Pollution Using Caliop Observations

Particulate matter with aerodynamic diameters smaller than 2.5 µm (PM2.5) contributes greatly to air pollution and poses significant threats to human health. Space-borne passive aerosol measurements, with their large spatial coverage, have been applied for estimating surface-based PM2.5 concentrations. Specifically, column-integrated aerosol optical thickness (AOT) observations, like those from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) instruments, have been leveraged for this task. In this doctoral research study, the issues and limitations with estimating PM2.5 from passively-retrieved MODIS and MISR AOT over the contiguous United States (CONUS) were first explored. Second, the potential of using active space-borne NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) near-surface aerosol extinction retrievals for PM2.5 estimation is studied. This includes exploration of various factors that affect CALIOP aerosol data processing, including the retrieval fill value (RFV) issue that results from CALIOP minimum aerosol detection limits. Next, an innovative approach for deriving PM2.5 concentrations directly from CALIOP near-surface aerosol extinction data has been explored using a bulk-mass-modeling-based method, and were validated against in situ PM2.5 from U.S. Environmental Protection Agency (EPA) ground stations. Lastly, temporal variations of CALIOP-based aerosol vertical distribution, including trends of near-surface aerosol loading, were examined globally and regionally to infer possible changes in surface air quality

Global and Regional Evaluation of Over-Land Spectral Aerosol Optical Depth Retrievals from SeaWiFS

This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (Sea WiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-year (1997-2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where Sea WiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record should be suitable for quantitative scientific use

An 11-Year Global Gridded Aerosol Optical Thickness Reanalysis (v1.0) for Atmospheric and Climate Sciences

While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003–2013 global 1 × 1 ◦ and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550 nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed

Evaluating nighttime CALIOP 0.532 μm aerosol optical depth and extinction coefficient retrievals

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 μm aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1° × 1° resolution versus corresponding/co-incident 0.550 μm AOD derived using the <i>US Navy Aerosol Analysis and Prediction System</i> (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 μm extinction coefficient are compared with 0.523/0.532 μm ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1° × 1° bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach ±20%. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties