Enhanced Deep Blue aerosol retrieval algorithm: The second generation

Abstract

[1] The aerosol products retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semiarid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and nonvegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of precalculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semiarid regions to the entire land areas. In this paper, the changes made in the enhanced Deep Blue algorithm regarding the surface reflectance estimation, aerosol model selection, and cloud screening schemes for producing the MODIS collection 6 aerosol products are discussed. A similar approach has also been applied to the algorithm that generates the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue products. Based upon our preliminary results of comparing the enhanced Deep Blue aerosol products with the Aerosol Robotic Network (AERONET) measurements, the expected error of the Deep Blue aerosol optical thickness (AOT) is estimated to be better than 0.05 + 20%. Using 10 AERONET sites with long-term time series, 79% of the best quality Deep Blue AOT values are found to fall within this expected error.

SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm

“…The MODIS DT cloud screening algorithm without cirrus cloud test (1.38 µm test) has been used with the current retrieval together and a visual-check according to the RGB images. The surface parameterization is a MODIS DB similar approach [6] while the aerosol types are parameterized by adapting the MODIS DT algorithm [5].…”

“…In the SAHARA algorithm, we follow a similar idea to the MODIS DB aerosol retrieval algorithm [6]. Statistical relationships of surface reflectance between different wavelengths were obtained.…”

“…One year (2008) cloud-free MODIS C6 TOA reflectance and corresponding MODIS surface reflectance product (MOD09A1) were collected over the study region as shown in Figure 1. Previous studies show that certain relationships between the surface reflectance at visible channels (0.67 and 0.47 µm) and reflectance at near-infrared/ infrared channels (e.g., 0.86, 1.6, 2.1 and 3.75 µm) can be found for certain surface types depending on instruments [5,6,[38][39][40]. Figure 2 shows an Previous attempts show the possibilities of using MODIS data product for surface parameterization and atmospheric parameters retrieval for instruments like Landsat (similar to GF4) [26,37].…”

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

“…Levy et al (2013) provide a detailed explanation of basic MODIS retrieval concepts and improvements to the DT algorithm in Collection 6 for aerosol products. In addition, Hsu et al (2013) give a detailed explanation of the DB algorithm improvements in Collection 6.…”

“…This comparative analysis does not aim to be a validation study of the MODIS sensor since many works during the long history of the MODIS sensor on the Terra and Aqua platforms have sought to improve its features (these include Kaufman et al, 1997a, b;Tanré et al, 1997;Remer et al, 2002Remer et al, , 2005Remer et al, , 2006Hsu, et al, 2004Hsu, et al, , 2006Hsu, et al, , 2013Levy et al, 2007Levy et al, , 2009Levy et al, , 2010Levy et al, , 2013Levy et al, , 2015Sayer et al, 2013Sayer et al, , 2014 https://darktarget.gsfc.nasa.gov/atbd/overview, last access: 9 April 2018). However, compared to other areas of the world, no studies have been reported in the Caribbean region and in Cuba in particular (Papadimas et al, 2009;Mishchenko et al, 2010;Kahn et al, 2011;Bennouna et al, 2011Bennouna et al, , 2013Witte et al, 2011;Gkikas et al, 2013Gkikas et al, , 2016Levy et al, 2015).…”