Literature DB >> 30140601

Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements.

A M Sayer1,2, N C Hsu2, J Lee2,3, N Carletta2,4, S-H Chen2,4, A Smirnov2,4.   

Abstract

The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sen-sors 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 Ad-vanced 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 Research (GESTAR), Universities Space Research Association. 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 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 appears to be similar for the NOAA11 and NOAA14 sensors as well.

Entities:  

Year:  2017        PMID: 30140601      PMCID: PMC6101972          DOI: 10.1002/2017JD026934

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


  7 in total

1.  New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans.

Authors:  Ziauddin Ahmad; Bryan A Franz; Charles R McClain; Ewa J Kwiatkowska; Jeremy Werdell; Eric P Shettle; Brent N Holben
Journal:  Appl Opt       Date:  2010-10-10       Impact factor: 1.980

2.  Retrieval of aerosol properties over land surfaces: capabilities of multiple-viewing-angle intensity and polarization measurements.

Authors:  Otto P Hasekamp; Jochen Landgraf
Journal:  Appl Opt       Date:  2007-06-01       Impact factor: 1.980

3.  Aerosol retrievals over the ocean by use of channels 1 and 2 AVHRR data: sensitivity analysis and preliminary results.

Authors:  M I Mishchenko; I V Geogdzhayev; B Cairns; W B Rossow; A A Lacis
Journal:  Appl Opt       Date:  1999-12-20       Impact factor: 1.980

4.  Satellite remote sensing reveals regional tropospheric aerosol trends.

Authors:  Michael I Mishchenko; Igor V Geogdzhayev
Journal:  Opt Express       Date:  2007-06-11       Impact factor: 3.894

5.  AERONET-based nonspherical dust optical models and effects on the VIIRS Deep Blue/SOAR over-water aerosol product.

Authors:  Jaehwa Lee; N Christina Hsu; Andrew M Sayer; Corey Bettenhausen; Ping Yang
Journal:  J Geophys Res Atmos       Date:  2017-09-17       Impact factor: 4.261

6.  Indonesian fire activity and smoke pollution in 2015 show persistent nonlinear sensitivity to El Niño-induced drought.

Authors:  Robert D Field; Guido R van der Werf; Thierry Fanin; Eric J Fetzer; Ryan Fuller; Hiren Jethva; Robert Levy; Nathaniel J Livesey; Ming Luo; Omar Torres; Helen M Worden
Journal:  Proc Natl Acad Sci U S A       Date:  2016-08-01       Impact factor: 11.205

7.  El Niño and health risks from landscape fire emissions in Southeast Asia.

Authors:  Miriam E Marlier; Ruth S DeFries; Apostolos Voulgarakis; Patrick L Kinney; James T Randerson; Drew T Shindell; Yang Chen; Greg Faluvegi
Journal:  Nat Clim Chang       Date:  2013
  7 in total

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