Validation of aerosol type classification from satellite remote sensing

Jaehwa Lee, Jhoon Kim, Jungbin Mok, Yunjae Kim

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Inter-comparison of various satellite data is performed for the purpose of validation of aerosol type classification algorithm from satellite remote sensing, so called, MODIS-OMI algorithm (MOA hereafter). Infrared Optical Depth Index (IODI), correlation coefficient between carbon monoxide (CO) column density and black carbon (BC) aerosol optical thickness (AOT), and aerosol types from 4-channel algorithm and CALIOP measurements are used to validate dust, BC, and aerosol type from MOA, respectively. The agreement of dust pixels between IODI and MOA ranges 0.1 to 0.6 with respect to AOT constraint, and it is inferred that IODI is less sensitive to optically thin dust layer. Increase of the correlation coefficient between AOT and CO column density when BC pixels are taken into account supports the performance of MOA to detect BC aerosol. The agreement of aerosol types from MOA and 4CA showed reasonable consistency, and the difference can be described by different absorptivity test and retrieval accuracy of AE. Inter-comparison of aerosol types between MOA and CALIOP measurements represented reasonable consistency when AOT greater than 0.5, and height dependence of MOA is inferred from consistency analysis with respect to aerosol layer height from CALIOP measurements. Inter-comparisons among different satellite data showed feasible future for validating aerosol type classification algorithm from satellite remote sensing.

Original languageEnglish
Pages (from-to)396-399
Number of pages4
JournalAIP Conference Proceedings
Volume1100
DOIs
Publication statusPublished - 2009 May 25
EventInternational Radiation Symposium, IRS 2008 - Foz do Iguacu, Brazil
Duration: 2008 Aug 32008 Aug 8

Fingerprint

remote sensing
aerosols
optical thickness
dust
carbon
correlation coefficients
carbon monoxide
pixels
MODIS (radiometry)
retrieval
absorptivity

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Cite this

Lee, Jaehwa ; Kim, Jhoon ; Mok, Jungbin ; Kim, Yunjae. / Validation of aerosol type classification from satellite remote sensing. In: AIP Conference Proceedings. 2009 ; Vol. 1100. pp. 396-399.
@article{381cd083b56b41539e42b37186d35984,
title = "Validation of aerosol type classification from satellite remote sensing",
abstract = "Inter-comparison of various satellite data is performed for the purpose of validation of aerosol type classification algorithm from satellite remote sensing, so called, MODIS-OMI algorithm (MOA hereafter). Infrared Optical Depth Index (IODI), correlation coefficient between carbon monoxide (CO) column density and black carbon (BC) aerosol optical thickness (AOT), and aerosol types from 4-channel algorithm and CALIOP measurements are used to validate dust, BC, and aerosol type from MOA, respectively. The agreement of dust pixels between IODI and MOA ranges 0.1 to 0.6 with respect to AOT constraint, and it is inferred that IODI is less sensitive to optically thin dust layer. Increase of the correlation coefficient between AOT and CO column density when BC pixels are taken into account supports the performance of MOA to detect BC aerosol. The agreement of aerosol types from MOA and 4CA showed reasonable consistency, and the difference can be described by different absorptivity test and retrieval accuracy of AE. Inter-comparison of aerosol types between MOA and CALIOP measurements represented reasonable consistency when AOT greater than 0.5, and height dependence of MOA is inferred from consistency analysis with respect to aerosol layer height from CALIOP measurements. Inter-comparisons among different satellite data showed feasible future for validating aerosol type classification algorithm from satellite remote sensing.",
author = "Jaehwa Lee and Jhoon Kim and Jungbin Mok and Yunjae Kim",
year = "2009",
month = "5",
day = "25",
doi = "10.1063/1.3117002",
language = "English",
volume = "1100",
pages = "396--399",
journal = "AIP Conference Proceedings",
issn = "0094-243X",
publisher = "American Institute of Physics Publising LLC",

}

Validation of aerosol type classification from satellite remote sensing. / Lee, Jaehwa; Kim, Jhoon; Mok, Jungbin; Kim, Yunjae.

In: AIP Conference Proceedings, Vol. 1100, 25.05.2009, p. 396-399.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Validation of aerosol type classification from satellite remote sensing

AU - Lee, Jaehwa

AU - Kim, Jhoon

AU - Mok, Jungbin

AU - Kim, Yunjae

PY - 2009/5/25

Y1 - 2009/5/25

N2 - Inter-comparison of various satellite data is performed for the purpose of validation of aerosol type classification algorithm from satellite remote sensing, so called, MODIS-OMI algorithm (MOA hereafter). Infrared Optical Depth Index (IODI), correlation coefficient between carbon monoxide (CO) column density and black carbon (BC) aerosol optical thickness (AOT), and aerosol types from 4-channel algorithm and CALIOP measurements are used to validate dust, BC, and aerosol type from MOA, respectively. The agreement of dust pixels between IODI and MOA ranges 0.1 to 0.6 with respect to AOT constraint, and it is inferred that IODI is less sensitive to optically thin dust layer. Increase of the correlation coefficient between AOT and CO column density when BC pixels are taken into account supports the performance of MOA to detect BC aerosol. The agreement of aerosol types from MOA and 4CA showed reasonable consistency, and the difference can be described by different absorptivity test and retrieval accuracy of AE. Inter-comparison of aerosol types between MOA and CALIOP measurements represented reasonable consistency when AOT greater than 0.5, and height dependence of MOA is inferred from consistency analysis with respect to aerosol layer height from CALIOP measurements. Inter-comparisons among different satellite data showed feasible future for validating aerosol type classification algorithm from satellite remote sensing.

AB - Inter-comparison of various satellite data is performed for the purpose of validation of aerosol type classification algorithm from satellite remote sensing, so called, MODIS-OMI algorithm (MOA hereafter). Infrared Optical Depth Index (IODI), correlation coefficient between carbon monoxide (CO) column density and black carbon (BC) aerosol optical thickness (AOT), and aerosol types from 4-channel algorithm and CALIOP measurements are used to validate dust, BC, and aerosol type from MOA, respectively. The agreement of dust pixels between IODI and MOA ranges 0.1 to 0.6 with respect to AOT constraint, and it is inferred that IODI is less sensitive to optically thin dust layer. Increase of the correlation coefficient between AOT and CO column density when BC pixels are taken into account supports the performance of MOA to detect BC aerosol. The agreement of aerosol types from MOA and 4CA showed reasonable consistency, and the difference can be described by different absorptivity test and retrieval accuracy of AE. Inter-comparison of aerosol types between MOA and CALIOP measurements represented reasonable consistency when AOT greater than 0.5, and height dependence of MOA is inferred from consistency analysis with respect to aerosol layer height from CALIOP measurements. Inter-comparisons among different satellite data showed feasible future for validating aerosol type classification algorithm from satellite remote sensing.

UR - http://www.scopus.com/inward/record.url?scp=65649114350&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=65649114350&partnerID=8YFLogxK

U2 - 10.1063/1.3117002

DO - 10.1063/1.3117002

M3 - Conference article

VL - 1100

SP - 396

EP - 399

JO - AIP Conference Proceedings

JF - AIP Conference Proceedings

SN - 0094-243X

ER -