The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

Wu, Y.; de Graaf, M.; Menenti, M.

doi:10.1002/2016JD026355

The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data

Title

The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

Author

Wu, Y. (TU Delft Optical and Laser Remote Sensing)
de Graaf, M. (TU Delft Atmospheric Remote Sensing; Royal Netherlands Meteorological Institute (KNMI))
Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences)

Date

2017-08-27

Abstract

Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3–5%.

Subject

aerosol optical depth
aerosol vertical distribution
CALIPSO data
MODIS data
retrieval
simulation

To reference this document use:

http://resolver.tudelft.nl/uuid:963fc10a-2db1-41c2-a572-1d053a063433

DOI

https://doi.org/10.1002/2016JD026355

Embargo date

2018-05-01

ISSN

2169-897X

Source

Journal Of Geophysical Research-Atmospheres, 122 (16), 8801-8815