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The physical and chemical properties of biomass burning (BB) smoke particles vary with fuel type and burning conditions, greatly affecting their impact on climate and air quality. However, the factors affecting smoke particle properties are not well characterized on a global scale, and the factors controlling their evolution during transport are not well constrained. From observations of the Multi-Angle Imaging Spectrometer (MISR) instrument aboard NASA's Terra satellite, smoke aerosol optical depth (AOD) can be retrieved, along with constraints on near-source plume vertical extent, smoke age, and particle size, shape, light-absorption, and absorption spectral dependence. Previous work demonstrated the robust, statistical characterization of BB particles across Canada and Alaska using MISR and other remote sensing data. Here we expand upon this work, studying over 3600 wildfire plumes across Siberia. We leverage the MISR Research Aerosol (RA) algorithm to retrieve smoke particle properties and the MISR Interactive Explorer (MINX) tool to retrieve plume heights and the associated wind vectors. These results are compared statistically to available observations of fire radiative power (FRP), land cover characteristics, and meteorological information. Correlations appear between the retrieved smoke particle properties, smoke age, local ambient conditions, and fuel type, allowing us in many cases to infer the dominant aging mechanisms and the timescales over which they occur. Specifically, we find that plumes located in areas with higher peat content are subject to less oxidation and condensation/hydration compared with other plume types (e.g., forest and grassland), and are predominantly affected by dilution instead.

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.

Convective clouds are common and play a major role in Earth's water cycle and energy balance; they may even develop into storms and cause severe rainfall events. To understand the convective cloud development process, this study investigates the impact of aerosols on convective clouds by considering the influence of both topography and diurnal variation in radiation. By combining texture analysis, clustering, and thresholding methods, we identify all convective clouds in two warm seasons (May–September, 2016/17) in eastern China based on Himawari-8 Level 1 data. Having large diurnally resolved cloud data together with surface meteorological and environmental measurements, we investigate convective cloud properties and their variation, stratified by elevation and diurnal change. We then analyze the potential impact of aerosol on convective clouds under different meteorological conditions and topographies. In general, convective clouds tend to occur preferentially under polluted conditions in the morning, which reverses in the afternoon. Convective cloud fraction first increases then decreases with aerosol loading, which may contribute to this phenomenon. Topography and diurnal meteorological variations may affect the strength of aerosol microphysical and radiative effects. Updraft is always stronger along the windward slopes of mountains and plateaus, especially in northern China. The prevailing southerly wind near the foothills of mountains and plateaus is likely to contribute to this windward strengthening of updraft and to bring more pollutant into the mountains, thereby strengthening the microphysical effect, invigorating convective clouds. By comparison, over plain, aerosols decrease surface heating and suppress convection by blocking solar radiation reaching the surface.

Deep convective clouds (DCCs) are important to global climate, atmospheric chemistry, and precipitation. Dust, a dominant aerosol type over the tropical North Atlantic, has potentially large microphysical impacts on DCCs over this region. However, dust effects are difficult to identify, being confounded by covarying meteorology and other factors. Here, a method is developed to quantify DCC responses to dust and other aerosols at large spatial and temporal scales despite these uncertainties. Over 7 million tropical North Atlantic cloud, aerosol, and meteorological profiles from CloudSat satellite data and MERRA-2 reanalysis products are used to stratify cloud observations into meteorological regimes, objectively select a priori assumptions, and iteratively test uncertainty sensitivity. Dust is robustly associated with a 54% increase in DCC prevalence. However, marine aerosol proxy concentrations are 5 times more predictive of dust-associated increases in DCC prevalence than the dust itself, or any other aerosol or meteorological factor. Marine aerosols are also the most predictive factor for the even larger increases in DCC prevalence (61%–87%) associated with enhanced dimethyl sulfide and combustion and sulfate aerosols. Dust-associated increases in DCC prevalence are smaller at high dust concentrations than at low concentrations. These observations suggest that not only is dust a comparatively ineffective CCN source, but it may also act as a condensation/coagulation sink for chemical precursors to CCN, reducing total CCN availability over large spatial scales by inhibiting new particle formation from marine emissions. These observations represent the first time this process, previously predicted by models, has been supported and quantified by measurements.

We characterise the vertical distribution of biomass-burning emissions across the Amazon during the biomass-burning season (July–November) with an extensive climatology of smoke plumes derived from MISR and MODIS (2005–2012) and CALIOP (2006–2012) observations. Smoke plume heights exhibit substantial variability, spanning a few hundred metres up to 6 km above the terrain. However, the majority of the smoke is located at altitudes below 2.5 km. About 60 % of smoke plumes are observed in drought years, 40 %–50 % at the peak month of the burning season (September) and 94 % over tropical forest and savanna regions, with respect to the total number of smoke plume observations. At the time of the MISR observations (10:00–11:00 LT), the highest plumes are detected over grassland fires (with an averaged maximum plume height of ∼1100 m) and the lowest plumes occur over tropical forest fires (∼800 m). A similar pattern is found later in the day (14:00–15:00 LT) with CALIOP, although at higher altitudes (2300 m grassland vs. 2000 m tropical forest), as CALIOP typically detects smoke at higher altitudes due to its later overpass time, associated with a deeper planetary boundary layer, possibly more energetic fires, and greater sensitivity to thin aerosol layers. On average, 3 %–20 % of the fires inject smoke into the free troposphere; this percentage tends to increase toward the end of the burning season (November: 15 %–40 %). We find a well-defined seasonal cycle between MISR plume heights, MODIS fire radiative power and atmospheric stability across the main biomes of the Amazon, with higher smoke plumes, more intense fires and reduced atmospheric stability conditions toward the end of the burning season. Lower smoke plume heights are detected during drought (800 m) compared to non-drought (1100 m) conditions, in particular over tropical forest and savanna fires. Drought conditions favour understory fires over tropical forest, which tend to produce smouldering combustion and low smoke injection heights. Droughts also seem to favour deeper boundary layers and the percentage of smoke plumes that reach the free troposphere is lower during these dry conditions. Consistent with previous studies, the MISR mid-visible aerosol optical depth demonstrates that smoke makes a significant contribution to the total aerosol loading over the Amazon, which in combination with lower injection heights in drought periods has important implications for air quality. This work highlights the importance of biome type, fire properties and atmospheric and drought conditions for plume dynamics and smoke loading. In addition, our study demonstrates the value of combining observations of MISR and CALIOP constraints on the vertical distribution of smoke from biomass burning over the Amazon.

This is a review paper rather than the report on a single line of research, updated from the 2019 Central Asia Dust Conference (CADUC) assessment. Satellites offer a broad range of constraints on dust particle amount, daily and longer-scale 3-d spatial distribution, particle properties, source locations, and transport pathways. Recent advances in dust particle optical modelling have improved the aerosol microphysical property constraints that can be derived from multi-angle remote-sensing data. Dust impacts on health are also being examined recently. Yet, the data contain spatial and temporal gaps, lack detail in some important respects, and interpretation of the remote-sensing retrieval results requires careful consideration of the information content, which can vary greatly with observing conditions. These data are applied most frequently to dust from North African sources and their journey across the Atlantic, but satellite examination of Asian sources and Pacific transports is now also receiving research attention.

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational on the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Terra satellite since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version of the MISR aerosol products. The level 2 (swath) product, which is reported on a 4.4 km spatial grid, is designated as version 23 (V23) and contains retrieved aerosol optical depth (AOD) and aerosol particle property information derived from MISR's multi-angle observations over both land and water. The changes from the previous version of the algorithm (V22) have significant impacts on the data product and its interpretation. The V23 data set is created from two separate retrieval algorithms that are applied over dark water and land surfaces, respectively. Besides increasing the horizontal resolution to 4.4 km compared with the coarser 17.6 m resolution in V22 and streamlining the format and content, the V23 product has added geolocation information, pixel-level uncertainty estimates, and improved cloud screening. MISR data can be obtained from the NASA Langley Research Center Atmospheric Science Data Center at https://eosweb.larc.nasa.gov/project/misr/misr_table (last access: 11 October 2019). The version number for the V23 level 2 aerosol product is F13_0023. The level 3 (gridded) aerosol product is still reported at 0.5∘×0.5∘ spatial resolution with results aggregated from the higher-resolution level 2 data. The format and content at level 3 have also been updated to reflect the changes made at level 2. The level 3 product associated with the V23 level 2 product version is designated as F15_0032. Both the level 2 and level 3 products are now provided in NetCDF format.

Purpose of Review Some aerosols absorb solar radiation, altering cloud properties, atmospheric stability and circulation dynamics, and the water cycle. Here we review recent progress towards global and regional constraints on aerosol absorption from observations and modeling, considering physical properties and combined approaches crucial for understanding the total (natural and anthropogenic) influences of aerosols on the climate. Recent Findings We emphasize developments in black carbon absorption alteration due to coating and ageing, brown carbon characterization, dust composition, absorbing aerosol above cloud, source modeling and size distributions, and validation of high-resolution modeling against a range of observations. Summary Both observations and modeling of total aerosol absorption, absorbing aerosol optical depths and single scattering albedo, as well as the vertical distribution of atmospheric absorption, still suffer from uncertainties and unknowns significant for climate applications. We offer a roadmap of developments needed to bring the field substantially forward.

We use a plume height climatology derived from space‐based Multiangle Imaging Spectroradiometer (MISR) observations to evaluate the performance of a widely used plume‐rise model. We initialize the model with assimilated meteorological fields from the NASA Goddard Earth Observing System and estimated fuel moisture content at the location and time of the MISR measurements. Fire properties that drive the plume‐rise model are difficult to constrain, and we test the model with four estimates each of active fire area and total heat flux, obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) thermal anomalies available for each MISR plume and other empirical data. We demonstrate the degree to which the fire dynamical heat flux (related to active fire area and sensible heat flux) and atmospheric stability structure influence plume rise, although entrainment and possibly other less well constrained factors are also likely to be significant. Using atmospheric stability conditions, MODIS FRP, and MISR plume heights, we find that smoke plumes reaching high altitudes are characterized by higher FRP and weaker atmospheric stability conditions than those at low altitude, which tend to remain confined below the boundary layer, consistent with earlier results. However, over the diversity of conditions studied, the model simulations generally underestimate the plume height dynamic range observed by MISR and do not reliably identify plumes injected into the free troposphere, key information needed for atmospheric models to simulate smoke dispersion. We conclude that embedding in large‐scale atmospheric studies an advanced plume‐rise model using currently available fire constraints remains a difficult proposition, and we propose a simplified model that crudely constrains plume injection height based on two main physical factors for which some observational constraints often exist. Field experiments aimed at directly measuring fire and smoke plume properties in detail are likely to produce the next major advances in plume‐rise modeling. Key Points A plume‐rise model is evaluated with empirical and satellite observations Plume model does not reproduce the heights with available fire constraints We propose two simplified methods to develop an injection height parameterization

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0deg (nadir) to 70deg 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.