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An extreme biomass-burning event occurred in Indonesia from September through October 2015 due to severe drought conditions, partially caused by a major El Nino event, thereby allowing for significant burning of peatland that had been previously drained. This event had the highest sustained aerosol optical depths (AOD) ever monitored by the global Aerosol Robotic Network (AERONET). The newly developed AERONET Version 3 algorithms retain high AOD at the longer wavelengths when associated with high Angstrom Exponents (AEs), which thereby allowed for measurements of AOD at 675 nanometers as high as approximately 7, the upper limit of Sun photometry. Measured AEs at the highest monitored AOD levels were subsequently utilized to estimate instantaneous values of AOD at 550 nanometers in the range of 11 to 13, well beyond the upper measurement limit. Additionally, retrievals of complex refractive indices, size distributions, and single scattering albedos (SSA) were obtained at much higher AOD levels than possible from almucantar scans due to the ability to perform retrievals at smaller solar zenith angles with new hybrid sky radiance scans. For retrievals made at the highest AOD levels the fine mode volume median radii were approximately 0.25 to 0.30 microns, which are very large particles for biomass burning. Very high SSA values (approximately 0.975 from 440 to 1020 nanometers) are consistent with the domination by smoldering combustion of peat burning. Estimates of the percentage peat contribution to total biomass burning aerosol based on retrieved SSA and laboratory measured peat SSA were approximately 80-85 percent, in excellent agreement with independent estimates.

The Suomi National Polar-Orbiting Partnership (S-NPP) satellite, launched in late 2011, carries the Visible Infrared Imaging Radiometer Suite (VIIRS) and several other instruments. VIIRS has similar characteristics to prior satellite sensors used for aerosol optical depth (AOD) retrieval, allowing the continuation of space-based aerosol data records. The Deep Blue algorithm has previously been applied to retrieve AOD from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements over land. The SeaWiFS Deep Blue dataset also included a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm to cover water surfaces. As part of NASA's VIIRS data processing, Deep Blue is being applied to VIIRS data over land, and SOAR has been adapted from SeaWiFS to VIIRS for use over water surfaces. This study describes SOAR as applied in version 1 of NASA's VIIRS Deep Blue data product suite. Several advances have been made since the SeaWiFS application, as well as changes to make use of the broader spectral range of VIIRS. A preliminary validation against Maritime Aerosol Network (MAN) measurements suggests a typical uncertainty on retrieved 550 nanometers AOD of order plus or minus (0.03 plus 10 percent), comparable to existing SeaWiFS/MODIS aerosol data products. Retrieved Angstrom exponent and fine mode AOD fraction are also well-correlated with MAN data, with small biases and uncertainty similar to or better than SeaWiFS/MODIS products.

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.

It has recently been found that the ultraviolet measurements obtained with the Nimbus 7 total ozone mapping spectrometer (TOMS) instrument can be used to retrieve information on the distribution of aerosols over oceanic and continental surfaces. Here we examine the use of the derived TOMS aerosol index (AI) for the detection of absorbing aerosol in terms of mineral dust aerosol over the North Atlantic Ocean and North Africa. Specifically, we compare the TOMS AI with the time series of daily aerosol measurements made in the boundary layer at Sal Island (Cape Verde), Barbados, and Miami and in the free troposphere on Tenerife (Canary Islands); these sites are frequently impacted by African dust events. At Tenerife, over the time period 1988–1992, TOMS detected 80% of the African dust events that yielded daily average dust concentrations greater than 20 μg m−3; at Barbados and Miami, TOMS detected 65% and 44% respectively of the events over the period 1979–1992. If we exclude events during which some of the TOMS data are missing and also short (1-day) dust events, TOMS detected 99% of the events at Tenerife, 97% at Barbados, and 81% at Miami. TOMS was also successful in detecting the “low altitude” African dust events recorded at Sal during the winter season. Over Africa we compare the TOMS AI data with ground-based measurements of aerosol optical thickness (AOT) obtained during field experiments in Senegal and Niger; these yield a nearly linear relationship between the TOMS AI and the AOT. Discrepancies between ground-based measurements (in terms of dust concentrations or AOT) and TOMS AI can be attributed to a number of factors: variations in the physical properties of the aerosol; the sensitivity of the TOMS response to the altitude of the aerosol layer; or the coarse spatial resolution of the TOMS pixel. Nonetheless, our results clearly show that the TOMS AI provides a remarkably accurate picture of mineral dust distributions in the atmosphere over both continental and oceanic regions.

A 14.5 year gridded data set of tropospheric absorbing aerosol index was derived from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) reflectivity difference between 340 and 380 nm channels. Based upon radiative transfer calculations, the reflectivity anomaly between these two UV wavelength channels is very sensitive to smoke and soot aerosols from biomass burning and forest fires, volcanic ash clouds as well as desert mineral dust. We demonstrate the ability of the TOMS instrument to detect and track smoke and soot aerosols generated by biomass burning in South America. TOMS data can clearly distinguish between absorbing particles (smoke and dust) and non-absorbing aerosols (clouds and haze). For South American fires, comparisons of TOMS data are consistent with the limited amount of ground-based observations (Porto Nacional, Brazil) and show generally good agreement with other satellite imagery. TOMS data shows large-scale transport of smoke particulates generated by the burning fires in the South America, which subsequentially advects smoke aerosols as far as the Atlantic Ocean east of Uruguay.

[1] A synergy of satellite and ground-based radiometric observations, along with chemical transport modeling, was used for the assessment of the influence of drought monsoon conditions of 2002 and prolonged dry pre-monsoon period of 2003 on aerosol properties over south Asia, with emphasis over northern India. Reanalysis data are also examined for studying the dry anomalous period from the climatological mean, that show prevalence of westerlies under anticyclonic circulation and subsidence favoring the accumulation of aerosols. TRMM observations over south Asia indicate significant rainfall deficit over northwestern India in July 2002 and May–June 2003. Subsequently, the anomalous and prolonged dry conditions favored heavy aerosol buildup as indicated by strong positive anomalies (20–80%) of MODIS aerosol optical depth (AOD) as well as significant increase in TOMS aerosol index (AI) during July 2002 and May–June 2003 compared to the long-term monthly means. The largest increase in aerosol loading is observed over northern India, encompassing the Indo-Gangetic Plains (IGP) that is in the downwind region of dust outflow from the Thar Desert and long-range transport from Arabia and Middle East. Ground-based sunphotometer observations at Delhi and Kanpur also show enhanced presence of desert-dust aerosols during July 2002 and May–June 2003, characterized by large AOD and significantly low Angstrom Exponent. In addition, modifications in columnar aerosol size distribution toward larger coarse-mode fraction and higher single scattering albedo at longer wavelengths were observed, thus supporting the observation of enhanced dust influx. SPRINTARS model simulations also show the enhanced dust loading over northern India during the studied months, which is in general agreement with the satellite and ground-based observations.

Retrievals of aerosol optical depth (AOD) and related parameters from satellite measurements typically involve prescribed models of aerosol size and composition, and are therefore dependent on how well these models are able to represent the radiative behaviour of real aerosols, This study uses aerosol volume size distributions retrieved from Sun-photometer measurements at 11 Aerosol Robotic Network (AERONET) island sites, spread throughout the world's oceans, as a basis to define such a model for unpolluted maritime aerosols. Size distributions are observed to be bimodal and approximately lognormal, although the coarse mode is skewed with a long tail on the low-radius end, The relationship of AOD and size distribution parameters to meteorological conditions is also examined, As wind speed increases, so do coarse-mode volume and radius, The AOD and Angstrom exponent (alpha) show linear relationships with wind speed, although there is considerable scatter in all these relationships, limiting their predictive power. Links between aerosol properties and near-surface relative humidity, columnar water vapor, and sea surface temperature are also explored. A recommended bimodal maritime model, which is able to reconstruct the AERONET AOD with accuracy of order 0.01-0.02, is presented for use in aerosol remote sensing applications. This accuracy holds at most sites and for wavelengths between 340 nm and 1020 nm. Calculated lidar ratios are also provided, and differ significantly from those currently used in Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) processing.

[1] The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a well-calibrated 13-year (1997–2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). This paper presents and validates a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm, which retrieves the AOD at 550 nm and the partition of aerosol particle volume between fine and coarse modes. The algorithm has been applied over water to the whole SeaWiFS record. The data set includes quality flags to identify those retrievals suitable for quantitative use. SOAR has been validated against Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) data and found to compare well (correlation 0.86 at 550 nm and 0.88 at 870 nm for AERONET, and 0.87 at 550 nm and 0.85 at 870 nm for MAN, using recommended quality control settings). These comparisons are used to identify the typical level of uncertainty on the AOD, estimated as 0.03 + 15% at 550 nm and 0.03 + 10% at 870 nm. The data set also includes the Angstrom exponent, although as expected this is noisy for low aerosol loadings (correlation 0.50; 0.78 for points where the AOD at 550 nm is 0.3 or more). Retrieved AOD is compared with colocated observations from other satellite sensors; regional and seasonal patterns are found to be common between all data sets, and differences generally linked to factors such as cloud screening and retrieval assumptions.

The Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheres data product suite includes three algorithms applied to retrieve midvisible aerosol optical depth (AOD): the Enhanced Deep Blue (DB) and Dark Target (DT) algorithms over land, and a DT over-water algorithm. All three have been refined in the recent “Collection 6” (C6) MODIS reprocessing. In particular, DB has been expanded to cover vegetated land surfaces as well as brighter desert/urban areas. Additionally, a new “merged” data set which draws from all three algorithms is included in the C6 products. This study is intended to act as a point of reference for new and experienced MODIS data users with which to understand the global and regional characteristics of the C6 DB, DT, and merged data sets, based on MODIS Aqua data. This includes validation against Aerosol Robotic Network (AERONET) observations at 111 sites, focused toward regional and categorical (surface/aerosol type) analysis. Neither algorithm consistently outperforms the other, although in many cases the retrieved AOD and the level of its agreement with AERONET are very similar. In many regions the DB, DT, and merged data sets are all suitable for quantitative applications, bearing in mind that they cannot be considered independent, while in other cases one algorithm does consistently outperform the other. Usage recommendations and caveats are thus somewhat complicated and regionally dependent.

[1] Fundamental to the onset of the Indian Summer Monsoon is the land-sea thermal gradient from the Indian Ocean to the Himalayas-Tibetan Plateau (HTP). The timing of the onset is strongly controlled by the meridional tropospheric temperature gradient due to the rapid premonsoon heating of the HTP compared to the relatively cooler Indian Ocean. Analysis of tropospheric temperatures from the longest available record of microwave satellite measurements reveals widespread warming over the Himalayan-Gangetic region and consequent strengthening of the land-sea thermal gradient. This trend is most pronounced in the pre-monsoon season, resulting in a warming of 2.7C in the 29-year record (1979–2007), when this region is strongly influenced by dust aerosols at elevated altitudes. The enhanced tropospheric warming is accompanied by increased atmospheric loading of absorbing aerosols, particularly vertically extended dust aerosols, raising the possibility that aerosol solar heating has amplified the seasonal warming and in turn strengthened the land-sea gradient. Citation: Gautam, R., N. C. Hsu, K.-M. Lau, S.-C. Tsay, and M. Kafatos (2009), Enhanced pre-monsoon warming over the Himalayan-Gangetic region from 1979 to 2007, Geophys. Res. Lett., 36, L07704, doi:10.1029/2009GL037641.

[1] We integrate SeaWiFS aerosol optical thickness (AOT) over the Taklamakan and Gobi Deserts with U.S. aerosol observations to study surface aerosol variability in the Northwest U.S. in relation to Asian dust emissions. The results indicate that ∼50% of the interannual variability in springtime average PM 2.5 and PM 10 can be explained by changes in Asian dust emissions. On a seasonal timescale, variations in dust emissions appear to be more important in determining the total material crossing the Pacific than the variations in meteorology represented by the PNA or the LRT3 indices. We are able to explain ∼80% of the interannual variability using three variables: AOT, a transport index, and regional precipitation. This suggests that a strong source, favorable transport and sufficient residence time are needed for Asian dust to have a maximum seasonal impact in the Northwest. The results contextualize case studies and demonstrate the utility of the Deep Blue algorithm.

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scatteri ng, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 run Lambert Equivalent Reflectivity (LER) ofa scene exceeds the surfuce reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflecti vity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large EI Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

[1] Measurements of the column-integrated aerosol optical properties in the southern African region were made by Aerosol Robotic Network (AERONET) Sun-sky radiometers at several sites in August–September 2000 as a part of the Southern African Regional Science Initiative (SAFARI) 2000 dry season field campaign. Fine mode biomass burning aerosols dominated in the northern part of the study region (Zambia), which is an active burning region, and other aerosols including fossil fuel burning, industrial, and aeolian coarse mode types also contributed to the aerosol mixture in other regions (South Africa and Mozambique), which were not as strongly dominated by local burning. The large amount of smoke produced in the north lead to a north-south gradient in aerosol optical depth (ta ) in September, with biomass burning aerosol concentrations reduced by dispersion and deposition during transport. Large average diurnal variations of ta (typical diurnal range of 25%) were observed at all sites in Zambia as a result of large diurnal trends in fire counts in that region that peak in midafternoon. However, for all sites located downwind to the south, there was relatively little (� 5–10%) average diurnal trend observed as the aerosol transport is not strongly influenced by diurnal cycles. AERONET radiometer retrievals of aerosol single scattering albedo (w0) in Zambia showed relatively constant values as a function of tafor ta440ranging from 0.4 to � 2.5. The wavelength dependence of w0varied significantly over the region, with greater decreases for increasing wavelength at smoke-dominated sites than for sites influenced by a significant coarse mode aerosol component. Retrievals of midvisible w0 based on the fitting of Photosynthetically Active Radiation (PAR; 400–700 nm) flux measurements to modeled fluxes for smoke in Mongu, Zambia yielded an average value of 0.84. This is in close agreement with the estimated average of 0.85 derived from interpolation of the AERONET retrievals made at 440 and 675 nm for August–September 2000. The spectral dependence of w0 independently retrieved with the AERONET measurements and with diffuse fraction measurements in Mongu, Zambia was similar for both techniques, as a result of both methods retrieving the imaginary index of refraction (� 0.030–0.035 on one day) with very little wavelength dependence. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0360 Atmospheric Composition and Structure: Transmission and scattering of radiation; 0345 Atmospheric Composition and Structure: Pollution—urban and regional (0305); 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 3359 Meteorology and Atmospheric Dynamics: Radiative processes