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  • 1
    Publikationsdatum: 2017-09-23
    Beschreibung: The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sensors like the Moderate Resolution Imaging Spectroradiometers (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to provide records of midvisible aerosol optical depth (AOD) and related quantities over land and ocean surfaces, respectively. Recently, DB and SOAR have also been applied to Advanced Very High Resolution Radiometer (AVHRR) observations from several platforms (NOAA11, NOAA14, and NOAA18), to demonstrate the potential for extending the DB and SOAR AOD records. This study provides an evaluation of the initial version (V001) of the resulting AVHRR-based AOD data set, including validation against Aerosol Robotic Network (AERONET) and ship-borne observations, and comparison against both other AVHRR AOD records and MODIS/SeaWiFS products at select long-term AERONET sites. Although it is difficult to distil error characteristics into a simple expression, the results suggest that one standard deviation confidence intervals on retrieved AOD of ±(0.03 + 15%) over water and ±(0.05 + 25%) over land represent the typical level of uncertainty, with a tendency toward negative biases in high-AOD conditions, caused by a combination of algorithmic assumptions and sensor calibration issues. Most of the available validation data are for NOAA18 AVHRR, although performance appears to be similar for the NOAA11 and NOAA14 sensors as well. ©2017. American Geophysical Union. All Rights Reserved.
    Print ISSN: 2169-897X
    Digitale ISSN: 2169-8996
    Thema: Geologie und Paläontologie , Physik
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2017-09-23
    Beschreibung: The spaceborne advanced very high resolution radiometer (AVHRR) sensor data record is approaching 40 years, providing a crucial asset for studying long-term trends of aerosol properties regionally and globally. However, due to limitations of its channels' information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics-based algorithm to retrieve aerosol loading over both land and ocean from AVHRR for the first time. The over-land algorithm is an extension of our Sea-viewing Wide Field-of-view Sensor and Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue algorithm, while a simplified version of our Satellite Ocean Aerosol Retrieval algorithm is used over ocean. We compare retrieved AVHRR AOD with that from MODIS on a daily and seasonal basis and find, in general, good agreement between the two. For the satellites with equatorial crossing times within 2 h of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against Aerosol Robotic Network data, preliminary results indicate that the expected error confidence interval envelope is around ±(0.03 + 15%) over ocean and ±(0.05 + 25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long-term data record for climate studies. ©2017. American Geophysical Union. All Rights Reserved.
    Print ISSN: 2169-897X
    Digitale ISSN: 2169-8996
    Thema: Geologie und Paläontologie , Physik
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 3
    Publikationsdatum: 2019-07-13
    Beschreibung: The spaceborne AVHRR sensors have provided a data record approaching 40 years, which is a crucial asset for studying the long-term trends of aerosol properties on both a global and regional basis. However, due to the limitations on its channels and information content, aerosol optical depth (AOD) data from AVHRR over land are still largely lacking. In this paper, we describe a new physics-based algorithm to retrieve global aerosol properties over both land and ocean from AVHRR for the first time. The over-land algorithm is an extension of our SeaWiFSMODIS Deep Blue algorithm, while a simplified version of the Satellite Ocean Aerosol Retrieval (SOAR) algorithm is used over ocean. We compare the retrieved AVHRR AOD values with those from MODIS collection 6 aerosol products on a daily and seasonal basis, and find in general good agreement between the two. For the satellites with equatorial crossing times within two hours of solar noon, the spatial coverage of the AVHRR aerosol product is comparable to that of MODIS, except over very bright arid regions (such as the Sahara and deserts in the Arabian Peninsula), where the underlying surface reflectance at 630 nm reaches the critical surface reflectance. Based upon comparisons of the AVHRR AOD against the AERONET data, the preliminary results indicate that the expected error is around +/-(0.03+15%) over ocean and +/-(0.05+25%) over land for this first version of the AVHRR aerosol products. Consequently, these new AVHRR aerosol products can contribute important building blocks for constructing a consistent long-term data record for climate studies.
    Schlagwort(e): Earth Resources and Remote Sensing
    Materialart: GSFC-E-DAA-TN45133 , Journal of Geophysical Research: Atmospheres (ISSN 2169-897X) (e-ISSN 2169-8996); 122; 18; 9968-9989
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    Publikationsdatum: 2019-07-13
    Beschreibung: The MODIS VIIRS 2016 Science Team Meeting was held June 6-10, 2016 at the Sheraton in Silver Spring, MD. The organizers plan to post the presentations and posters here: http:modis.gsfc.nasa.govsci_teammeetings201606.
    Schlagwort(e): Earth Resources and Remote Sensing
    Materialart: GSFC-E-DAA-TN33626 , MODIS/VIIRS 2016 Science Team Meeting; Jun 06, 2016 - Jun 10, 2016; Silver Spring, MD; United States
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 5
    Publikationsdatum: 2019-07-13
    Beschreibung: Atmospheric aerosols such as mineral dust, wildfire smoke, sea spray, and volcanic ash are of interest for a variety of reasons including public health, climate change, hazard avoidance, and more. Deep Blue is a project which uses satellite observations of the Earth from sensors such as SeaWiFS, MODIS, and VIIRS to monitor the global aerosol burden. This talk will cover some basics about aerosols and the principles of aerosol remote sensing, as well as discussing specific results and future directions for the Deep Blue project.
    Schlagwort(e): Earth Resources and Remote Sensing
    Materialart: GSFC-E-DAA-TN36911 , University of North Dakota Seminar Program; Oct 20, 2016; Grand Forks, ND; United States
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 6
    Publikationsdatum: 2019-07-13
    Beschreibung: The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sensors like the Moderate Resolution Imaging Spectroradiometers (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to provide records of mid visible aerosol optical depth (AOD) and related quantities over land and ocean surfaces respectively. Recently, DB and SOAR have also been applied to Advanced Very High Resolution Radiometer (AVHRR) observations from several platforms (NOAA11, NOAA14, and NOAA18), to demonstrate the potential for extending the DB and SOAR AOD records. This study provides an evaluation of the initial version (V001) of the resulting AVHRR-based AOD data set, including validation against Aerosol Robotic Network (AERONET)and ship-borne observations, and comparison against both other AVHRR AOD records and MODIS/SeaWiFS products at select long-term AERONET sites. Although it is difficult to distil error characteristics into a simple expression,the results suggest that one standard deviation confidence intervals on retrieved AOD of plus or minus (0.03+15 %) over water and plus or minus (0.05+25 %) over land represent the typical level of uncertainty, with a tendency towards negative biases in high-AOD conditions, caused by a combination of algorithmic assumptions and sensor calibration issues. Most of the available validation data are for NOAA18 AVHRR, although performance appear to be similar for the NOAA11 and NOAA14 sensors as well.
    Schlagwort(e): Earth Resources and Remote Sensing
    Materialart: GSFC-E-DAA-TN51760 , Journal of Geophysical Research (ISSN 2169-897X) (e-ISSN 2169-8996); 122; 18; 9945-9967
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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