[1] A statistical approach is used to assess the quality of the Multiangle Imaging SpectroRadiometer (MISR) version 22 (V22) aerosol products. Aerosol optical depth (AOD) retrieval results are improved relative to the early postlaunch values reported by ], which varied with particle type category. Overall, about 70% to 75% of MISR AOD retrievals fall within 0.05 or 20% × AOD of the paired validation data from the Aerosol Robotic Network (AERONET), and about 50% to 55% are within 0.03 or 10% × AERONET AOD, except at sites where dust or mixed dust and smoke are commonly found. Retrieved particle microphysical properties amount to categorical values, such as three size groupings: "small," "medium," and "large." For particle size, ground-based AERONET sun photometer Angstrom exponents are used to assess statistically the corresponding MISR values, which are interpreted in terms of retrieved size categories. Coincident singlescattering albedo (SSA) and fraction AOD spherical data are too limited for statistical validation. V22 distinguishes two or three size bins, depending on aerosol type, and about two bins in SSA (absorbing vs. nonabsorbing), as well as spherical vs. nonspherical particles, under good retrieval conditions. Particle type sensitivity varies considerably with conditions and is diminished for midvisible AODs below about 0.15 or 0.2. On the basis of these results, specific algorithm upgrades are proposed and are being investigated by the MISR team for possible implementation in future versions of the product.

Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends for 1998–2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM2.5 concentrations using geophysical relationships between surface PM2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM2.5 estimates are highly consistent with globally distributed ground monitors (R 2 = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM2.5 estimates to predict and account for the residual bias with PM2.5 monitors, yielding even higher cross validated agreement (R 2 = 0.90–0.92; slope = 0.90–0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (−0.28 ± 0.03 μg/m3/yr), Europe (−0.15 ± 0.03 μg/m3/yr), India (1.13 ± 0.15 μg/m3/yr), and globally (0.04 ± 0.02 μg/m3/yr). The positive trend (2.44 ± 0.44 μg/m3/yr) for India over 2005–2013 and the negative trend (−3.37 ± 0.38 μg/m3/yr) for China over 2011–2018 are remarkable, with implications for the health of billions of people.

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[1] Although the current Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite passive remote sensing midvisible aerosol optical thickness (AOT) products are accurate overall to about 0.05 or 20%, they differ systematically on a global, monthly average basis, by about 0.03 to 0.05. Some key climate change and other applications require accuracies of 0.03 or better. The instruments are sufficiently stable and well characterized, and have adequate signal-tonoise, to realize such precision. However, assumptions made in the current standard aerosol retrieval algorithms produce AOT biases that must be addressed first. We identify the causes of AOT discrepancies over dark water under typical, relatively low AOT conditions and quantify their magnitudes on the basis of detailed analysis. Examples were selected to highlight key issues for which there are coincident MISR, MODIS, and Aerosol Robotic Network (AERONET) observations. Instrument calibration and sampling differences, assumptions made in the MISR and MODIS standard algorithms about ocean surface boundary conditions, missing particle property or mixture options, and the way reflectances used in the retrievals are selected each contribute significantly to the observed differences under some circumstances. Cloud screening is also identified as a factor, though not fully examined here, as are the relatively rare high-AOT cases over ocean. Specific algorithm upgrades and further studies indicated by these findings are discussed, along with recommendations for effectively using the currently available products for regional and global applications.

An international Intercomparison of 3D Radiation Codes (I3RC) underscores the vast progress of recent years, but also highlights the challenges ahead for routine implementation in remote sensing and global climate modeling applications. Modeling atmospheric and oceanic processes is one of the most important methods of the earth sciences for understanding the interactions of the various components of the surface-atmosphere system and predicting future weather and climate states. Great leaps in the availability of computing power at continuously decreasing costs have led to widespread popularity of computer models for research and operational applications. As part of routine scientific work, output from models built for AFFILIATIONS: CAHALAN-NASA

Abstract:The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0° (nadir) to 70° off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR's operational stereo product uses this capability to retrieve cloud heights and winds for every satellite orbit, yielding global coverage every nine days. The MISR INteractive eXplorer (MINX) visualization and analysis tool complements the operational stereo product by providing users the ability to retrieve heights and winds locally for detailed studies of smoke, dust and volcanic ash plumes, as well as clouds, at higher spatial resolution and with greater precision than is possible with the operational product or with other space-based, passive, remote sensing instruments. This ability to investigate plume geometry and dynamics is becoming increasingly important as climate and air quality studies require greater knowledge about the injection of aerosols and the location of clouds within the atmosphere. MINX incorporates features that allow users to customize their stereo retrievals for optimum results under varying aerosol and underlying surface conditions. This paper discusses the stereo retrieval algorithms and retrieval options in MINX, and provides appropriate examples to explain how the program can be used to achieve the best results.

The Middle Eastern Shamal is a strong north‐northwesterly wind, capable of lifting dust from the Tigris‐Euphrates basin and transporting it to the Persian Gulf and Arabian Peninsula. The present study explores the poorly understood spatial and temporal variability of summer Shamal on the diurnal, seasonal, and interannual time scales, along with its influence on dust storm activity and sensitivity to global patterns of sea surface temperature using a comprehensive set of observational data. Statistics of the summer Shamal season are quantified for the first time, including its onset, termination, duration, and the occurrence of distinct break periods. Based on a multistation criteria, the mean onset and termination of the Shamal season occur on 30 May ± 16 days (1 standard deviation) and 16 August ± 22 days, respectively. Anomalously early (late) onset and termination of the Shamal season are typically associated with La Niña (El Niño) conditions, which favor (inhibit) the development of the Iranian heat low in spring and inhibit (favor) its persistence into late summer. Dust source regions in the Tigris‐Euphrates basin and Kuwait, as well as southeastward dust transport during the summer Shamal, which cannot be detected by satellite aerosol products alone, are identified, for the first time, from the Multiangle Imaging Spectroradiometer plume motion vector products and confirmed by surface observations and lidar data. A close interrelationship has been revealed among summertime dust activity across the eastern Arabian Peninsula, frequency of Shamal days, and duration of the Shamal season on the interannual time scales.

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