The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

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 [Kahn et al. (2005)], 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 single‐scattering 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.

The frequent occurrence of severe air pollution episodes in China has been a great concern and thus the focus of intensive studies. Planetary boundary layer height (PBLH) is a key factor in the vertical mixing and dilution of near-surface pollutants. However, the relationship between PBLH and surface pollutants, especially particulate matter (PM) concentration across China, is not yet well understood. We investigate this issue at ∼1600 surface stations using PBLH derived from space-borne and ground-based lidar, and discuss the influence of topography and meteorological variables on the PBLH–PM relationship. Albeit the PBLH–PM correlations are roughly negative for most cases, their magnitude, significance, and even sign vary considerably with location, season, and meteorological conditions. Weak or even uncorrelated PBLH–PM relationships are found over clean regions (e.g., Pearl River Delta), whereas nonlinearly negative responses of PM to PBLH evolution are found over polluted regions (e.g., North China Plain). Relatively strong PBLH–PM interactions are found when the PBLH is shallow and PM concentration is high, which typically corresponds to wintertime cases. Correlations are much weaker over the highlands than the plains regions, which may be associated with lighter pollution loading at higher elevations and contributions from mountain breezes. The influence of horizontal transport on surface PM is considered as well, manifested as a negative correlation between surface PM and wind speed over the whole nation. Strong wind with clean upwind air plays a dominant role in removing pollutants, and leads to obscure PBLH–PM relationships. A ventilation rate is used to jointly consider horizontal and vertical dispersion, which has the largest impact on surface pollutant accumulation over the North China Plain. As such, this study contributes to improved understanding of aerosol–planetary boundary layer (PBL) interactions and thus our ability to forecast surface air pollution.

Aerosol variations and trends over different land and ocean regions from 1980 to 2009 are analyzed with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and observations from multiple satellite sensors and available ground-based networks. Excluding time periods with large volcanic influence, aerosol optical depth (AOD) and surface concentration over polluted land regions generally vary with anthropogenic emissions, but the magnitude of this association can be dampened by the presence of natural aerosols, especially dust. Over the 30-year period in this study, the largest reduction in aerosol levels occurs over Europe, where AOD has decreased by 40–60% on average and surface sulfate concentrations have declined by a factor of up to 3–4. In contrast, East Asia and South Asia show AOD increases, but the relatively high level of dust aerosols in Asia reduces the correlation between AOD and pollutant emission trends. Over major dust source regions, model analysis indicates that the change of dust emissions over the Sahara and Sahel has been predominantly driven by the change of near-surface wind speed, but over Central Asia it has been largely influenced by the change of the surface wetness. The decreasing dust trend in the North African dust outflow region of the tropical North Atlantic and the receptor sites of Barbados and Miami is closely associated with an increase of the sea surface temperature in the North Atlantic. This temperature increase may drive the decrease of the wind velocity over North Africa, which reduces the dust emission, and the increase of precipitation over the tropical North Atlantic, which enhances dust removal during transport. Despite significant trends over some major continental source regions, the model-calculated global annual average AOD shows little change over land and ocean in the past three decades, because opposite trends in different land regions cancel each other out in the global average, and changes over large open oceans are negligible. This highlights the necessity for regional-scale assessment of aerosols and their climate impacts, as global-scale average values can obscure important regional changes.

In addition to aerosol optical depth (AOD), aerosol type is required globally for climate forcing calculations, constraining aerosol transport models and other applications. However, validating satellite aerosol‐type retrievals is more challenging than testing AOD results, because aerosol type is a more complex quantity, and ground truth data are far less numerous and generally not as robust. We evaluate the Multiangle Imaging Spectroradiometer (MISR) Version 22 aerosol‐type retrievals by assessing product self‐consistency on a regional basis and by making comparisons with general expectation and with the Aerosol Robotic Network aerosol‐type climatology, as available. The results confirm and add detail to the observation that aerosol‐type discrimination improves dramatically where midvisible AOD exceeds about 0.15 or 0.2. When the aerosol‐type information content of the observations is relatively low, increased scattering‐angle range improves particle‐type sensitivity. The MISR standard, operational product discriminates among small, medium, and large particles and exhibits qualitative sensitivity to single‐scattering albedo (SSA) under good aerosol‐type retrieval conditions, providing a categorical aerosol‐type classification. MISR Ångström exponent deviates systematically from ground truth where particle types missing from the algorithm climatology are present, or where cloud contamination is likely to occur, and SSA tends to be overestimated where absorbing particles are found. We determined that the number of mixtures passing the algorithm acceptance criteria (#SuccMix) represents aerosol‐type retrieval quality effectively, providing a useful aerosol‐type quality flag.

Satellite instruments provide a vantage point for studying aerosol loading consistently over different regions of the world. However, the typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies, the use of multiple satellite sensors should be considered. Discrepancies exist between aerosol optical depth (AOD) products due to differences in their information content, spatial and temporal sampling, calibration, cloud masking, and algorithmic assumptions. Users of satellite-based AOD time-series are confronted with the challenge of choosing an appropriate dataset for the intended application. In this study, 16 monthly AOD products obtained from different satellite sensors and with different algorithms were inter-compared and evaluated against Aerosol Robotic Network (AERONET) monthly AOD. Global and regional analyses indicate that products tend to agree qualitatively on the annual, seasonal and monthly timescales but may be offset in magnitude. Several approaches were then investigated to merge the AOD records from different satellites and create an optimised AOD dataset. With few exceptions, all merging approaches lead to similar results, indicating the robustness and stability of the merged AOD products. We introduce a gridded monthly AOD merged product for the period 1995–2017. We show that the quality of the merged product is as least as good as that of individual products. Optimal agreement of the AOD merged product with AERONET further demonstrates the advantage of merging multiple products. This merged dataset provides a long-term perspective on AOD changes over different regions of the world, and users are encouraged to use this dataset.