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  • 1
  • 2
    Publication Date: 2019-07-19
    Description: The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.
    Keywords: Environment Pollution
    Type: GSFC.ABS.6077.2012 , 2011 American Geophysical Union (AGU) Fall Meeting; Dec 05, 2011 - Dec 09, 2011; San Francisco, CA; United States
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  • 3
    Publication Date: 2019-07-13
    Description: We compare C5 and C6 validation to compare the C6 10 km aerosol product against the well validated and trusted aerosol product on global and regional scales. Only the 10 km aerosol product is evaluated in this study, validation of the new C6 3 km aerosol product still needs to be performed. Not all of the time series has processed yet for C5 or C6, and the years processed for the 2 products is not exactly the same (this work is preliminary!). To reduce the impact of outlier observations, MODIS is spatially averaged within 27.5 km of the AERONET site, and AERONET is temporatally averaged within 30 minutes of the MODIS overpass time. Only high quality (QA = 3 over land, QA greater than 0 over ocean) pixels are included in the mean.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN15408 , 2014 MODIS Science Team Meeting; Apr 29, 2014 - May 01, 2014; Columbia, MD; United States
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  • 4
    Publication Date: 2019-07-12
    Description: The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.
    Keywords: Meteorology and Climatology
    Type: GSFC.JA.6086.2012
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  • 5
    Publication Date: 2019-07-12
    Description: The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC.JA.4727.2011
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  • 6
    Publication Date: 2019-08-13
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN15531 , 2014 MODIS Science Team Meeting; Apr 29, 2014 - May 01, 2014; Columbia, MD; United States
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  • 7
    Publication Date: 2019-07-13
    Description: High aerosol loading over the northern Indian subcontinent can result in poor air quality leading to human health consequences and climate perturbations. The international 2008 TIGERZ experiment intensive operational period (IOP) was conducted in the Indo \Gangetic Plain (IGP) around the industrial city of Kanpur (26.51degN, 80.23deg E), India, during the premonsoon (April-June). Aerosol Robotic Network (AERONET) Sun photometers performed frequent measurements of aerosol properties at temporary sites distributed within an area covering 50 sq km around Kanpur to characterize pollution and dust in a region where complex aerosol mixtures and semi \bright surface effects complicate satellite retrieval algorithms. TIGERZ IOP Sun photometers quantified aerosol optical depth (AOD) increases up to 0.10 within and downwind of the city, with urban emissions accounting for 10 C20% of the IGP aerosol loading on deployment days. TIGERZ IOP area \averaged volume size distribution and single scattering albedo retrievals indicated spatially homogeneous, uniformly sized, spectrally absorbing pollution and dust particles. Aerosol absorption and size relationships were used to categorize black carbon and dust as dominant absorbers and to identify a third category in which both black carbon and dust dominate absorption.Moderate Resolution Imaging Spectroradiometer (MODIS) AOD retrievals with the lowest quality assurance (QA 〉 or = 0) flags were biased high with respect to TIGERZ IOP area \averaged measurements. MODIS AOD retrievals with QA 0 had moderate correlation (R(sup 2) = 0.52-69) with the Kanpur AERONET site, whereas retrievals with QA 〉 0 were limited in number. Mesoscale \distributed Sun photometers quantified temporal and spatial variability of aerosol properties, and these results were used to validate satellite retrievals.
    Keywords: Geophysics
    Type: GSFC.JA.00426.2012 , Journal of Geophysical Research; 116
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  • 8
    Publication Date: 2019-07-13
    Description: Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN10940 , AeroCom Workshop; Sep 23, 2013 - Sep 26, 2013; Hamburg; Germany
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  • 9
    Publication Date: 2019-07-13
    Description: The document was presented at the 2013 AEROCENTER Annual Meeting held at the GSFC Visitors Center, May 31, 2013. The organizers of the meeting are posting the talks to the public Aerocenter website.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN10428 , 2013 Annual Aerocenter Meeting; Aug 21, 2013; Greenbelt, MD; United States
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  • 10
    Publication Date: 2019-07-13
    Description: GEO-CAPE will measure a suite of short-lived species that are relevant to both air quality and climate. The document was presented at the 2013 AEROCENTER Annual Meeting held at the GSFC Visitors Center, May 31, 2013. The Organizers of the meeting are posting the talks to the public Aerocentr website, after the meeting.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN10483 , 2013 Annual Aerocenter Meeting; May 31, 2013; Greenbelt, MD; United States
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