ALBERT

Description: 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.

Description: Analysis of sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (〉1.0 in mid-visible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological co-variation with atmospheric stability and convergence. The new development of Aerosol Robotic network (AERONET) Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the Spectral Deconvolution Algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of AERONET L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.

Description: No abstract available

Description: After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

Description: Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) datahas shown that major aerosol pollution events with very highfine mode AOD (〉1.0 in midvisible) in theChina/Korea/Japan region are often observed to be associated with significant cloud cover. This makesremote sensing of these events difficult even for high temporal resolution Sun photometer measurements.Possible physical mechanisms for these events that have high AOD include a combination of aerosolhumidification, cloud processing, and meteorological covariation with atmospheric stability andconvergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloudscreening algorithms now allow for unprecedented ability to monitor these extremefine mode pollutionevents. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening)provides an even more comprehensive assessment offine mode AOD than L2 in current and previous dataversions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA dailyaveragefine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remotesensing of AOD often did not retrieve and/or identify some of the highestfine mode AOD events in thisregion. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDAfinemode AOD was significantly higher in magnitude, particularly for the highest AOD events that were oftenassociated with significant cloudiness.

Description: The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

Description: Wildfires raged throughout western Russia and parts of Eastern Europe during a persistent heat wave in the summer of 2010. Anomalously high surface temperatures (35 - 41 C) and low relative humidity (9 - 25 %) from mid- June to mid-August 2010 shown by analysis of radiosonde data from multiple sites in western Russia were ideal conditions for the wildfires to thrive. Measurements of outgoing longwave radiation (OLR) from the Atmospheric Infrared Sounder (AIRS) over western Russian indicate persistent subsidence during the heat wave. Daily three-day back-trajectories initiated over Moscow reveal a persistent anticyclonic circulation for 18 days in August, coincident with the most intense period of fire activity observed by Moderate Resolution Imaging Spectroradiometer (MODIS). This unfortunate meteorological coincidence allowed transport of polluted air from the region of intense fires to Moscow and the surrounding area. We demonstrate that the 2010 Russian wildfires are unique in the record of observations obtained by remote-sensing instruments on-board NASA satellites: Aura and Aqua (part of the A-Train Constellation) and Terra. Analysis of the distribution of MODIS fire products and aerosol optical thickness (AOT), UV aerosol index (AI) and single-scattering albedo (SSA) from Aura's Ozone Monitoring Instrument (OMI), and total column carbon monoxide (CO) from Aqua s Atmospheric Infrared Sounder (AIRS) show that the region in the center of western Russia surrounding Moscow (52-58 deg N, 33 -43 deg E) is most severely impacted by wildfire emissions. Over this area, AIRS CO, OMI AI, and MODIS AOT are significantly enhanced relative to the historical satellite record during the first 18 days in August when the anti-cyclonic circulation persisted. By mid-August, the anti-cyclonic circulation was replaced with westerly transport over Moscow and vicinity. The heat wave

Description: MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R 〉 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

Description: Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

Description: Atmospheric aerosol has uncertain impacts on the global climate system, as well as on atmospheric and bio-geo-chemical processes of regional and local scales. EOS-MODIS is one example of a satellite sensor designed to improve understanding of the aerosols' type, size and distribution at all temporal and spatial scales. Ocean scientists also plan to use data from EOS-MODIS to assess the temporal and spatial coverage of in-water chlorophyll. MODIS is the first sensor planned to observe the combined ocean-atmosphere system with a wide spectral range (from 410 to 2200 nm). Dust aerosol and salt aerosol have similar spectral signals for wavelengths longer than 550 nm, but because dust selectively absorbs blue light, they have divergent signals in the blue wavelength regions (412 to 490 nm). Chlorophyll also selectively absorbs blue radiation, so that varying chlorophyll concentrations produces a highly varying signal in the blue regions, but less variability in the green, and almost no signal in the red to mid-infrared regions. Thus, theoretically, it may be difficult to differentiate dust and salt in the presence of unknown chlorophyll in the ocean. This study attempts to address the cases in which aerosol and chlorophyll signals can and cannot be separated. For the aerosol spectra, we use the aerosol lookup table from the operational MODIS aerosol-over-ocean algorithm, and for chlorophyll spectra, we use the SeaBAM data set (created for SeaWiFS). We compare the signals using Principal Component Analysis and attempt to retrieve both chlorophyll and aerosol properties using a variant of the operational MODIS aerosol-over-ocean algorithm. Results show that for small optical depths, less than 0.5, it is not possible to differentiate between dust and salt and to determine the chlorophyll concentration at the same time. For larger aerosol optical depths, the chlorophyll signals are comparatively insignificant, and we can hope to distinguish between dust and salt.