Literature DB >> 29796366

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET.

Stephen D Superczynski1, Shobha Kondragunta2, Alexei I Lyapustin3.   

Abstract

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere.

Entities:  

Keywords:  Aerosol Optical Thickness; Aerosols and particles; Evaluation; Intercomparison; MAIAC; Remote sensing; Suomi-NPP VIIRS

Year:  2017        PMID: 29796366      PMCID: PMC5963281          DOI: 10.1002/2016JD025720

Source DB:  PubMed          Journal:  J Geophys Res Atmos        ISSN: 2169-897X            Impact factor:   4.261


  1 in total

1.  Aerosols, climate, and the hydrological cycle.

Authors:  V Ramanathan; P J Crutzen; J T Kiehl; D Rosenfeld
Journal:  Science       Date:  2001-12-07       Impact factor: 47.728

  1 in total
  4 in total

1.  Observations of the Interaction and Transport of Fine Mode Aerosols with Cloud and/or Fog in Northeast Asia from Aerosol Robotic Network (AERONET) and Satellite Remote Sensing.

Authors:  T F Eck; B N Holben; J S Reid; P Xian; D M Giles; A Sinyuk; A Smirnov; J S Schafer; I Slutsker; J Kim; J-H Koo; M Choi; K C Kim; I Sano; A Arola; A M Sayer; R C Levy; L A Munchak; N T O'Neill; A Lyapustin; N C Hsu; C A Randles; A M Da Silva; V Buchard; R C Govindaraju; E Hyer; J H Crawford; P Wang; X Xia
Journal:  J Geophys Res Atmos       Date:  2018-05-04       Impact factor: 4.261

2.  A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers.

Authors:  John A Gamon; K Fred Huemmrich; Christopher Y S Wong; Ingo Ensminger; Steven Garrity; David Y Hollinger; Asko Noormets; Josep Peñuelas
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-01       Impact factor: 11.205

3.  Population exposure across central India to PM2.5 derived using remotely sensed products in a three-stage statistical model.

Authors:  Prem Maheshwarkar; Ramya Sunder Raman
Journal:  Sci Rep       Date:  2021-01-12       Impact factor: 4.379

4.  Exposure to Particulate Matter Air Pollution and Anosmia.

Authors:  Zhenyu Zhang; Nicholas R Rowan; Jayant M Pinto; Nyall R London; Andrew P Lane; Shyam Biswal; Murugappan Ramanathan
Journal:  JAMA Netw Open       Date:  2021-05-03
  4 in total

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