Validation of aerosol-type classification from satellite remote sensing

Jhoon Kim; Jaehwa Lee; Jungbin Mok; Yunjae Kim

doi:10.1117/12.806401

8 December 2008 Validation of aerosol type classification from satellite remote sensing

Jhoon Kim, Jaehwa Lee, Jungbin Mok, Yunjae Kim

Proceedings Volume 7152, Remote Sensing of the Atmosphere and Clouds II; 71520Q (2008) https://doi.org/10.1117/12.806401
Event: SPIE Asia-Pacific Remote Sensing, 2008, Noumea, New Caledonia

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. Intercomparison 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.

Citation Download Citation

Jhoon Kim, Jaehwa Lee, Jungbin Mok, and Yunjae Kim "Validation of aerosol type classification from satellite remote sensing", Proc. SPIE 7152, Remote Sensing of the Atmosphere and Clouds II, 71520Q (8 December 2008); https://doi.org/10.1117/12.806401

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