Literature DB >> 31534879

Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers.

Man-Hae Kim1,2, Ali H Omar1, Mark A Vaughan1, David M Winker1, Charles R Trepte1, Yongxiang Hu1, Zhaoyan Liu1,3, Sang-Woo Kim4.   

Abstract

The CALIOP data processing scheme only retrieves extinction profiles in those portions of the return signal where cloud or aerosol layers have been identified by the CALIOP layer detection scheme. In this study we use two years of CALIOP and MODIS data to quantify the aerosol optical depth of undetected weakly backscattering layers. Aerosol extinction and column-averaged lidar ratio is retrieved from CALIOP Level 1B (Version 4) profile using MODIS AOD as a constraint over oceans from March 2013 to February 2015. To quantify the undetected layer AOD (ULA), an unconstrained retrieval is applied globally using a lidar ratio of 28.75 sr estimated from constrained retrievals during the daytime over the ocean. We find a global mean ULA of 0.031 ± 0.052. There is no significant difference in ULA between land and ocean. However, the fraction of undetected aerosol layers rises considerably during daytime, when the large amount of solar background noise lowers the signal to noise ratio (SNR). For this reason, there is a difference in ULA between day (0.036 ± 0.066) and night (0.025 ± 0.021). ULA is larger in the northern hemisphere and relatively larger at high latitudes. Large ULA for the Polar Regions is strongly related to the cases where the CALIOP Level 2 Product reports zero AOD. This study provides an estimate of the complement of AOD that is not detected by lidar, and bounds the CALIOP AOD uncertainty to provide corrections for science studies that employ the CALIOP Level 2 AOD.

Keywords:  0305; CALIPSO; aerosol extinction; aerosol optical depth; lidar ratio; undetected layer

Year:  2017        PMID: 31534879      PMCID: PMC6749610          DOI: 10.1002/2016JD025797

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


  3 in total

1.  Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products.

Authors:  Travis D Toth; James R Campbell; Jeffrey S Reid; Jason L Tackett; Mark A Vaughan; Jianglong Zhang; Jared W Marquis
Journal:  Atmos Meas Tech       Date:  2018-01-24       Impact factor: 4.176

2.  The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm.

Authors:  Man-Hae Kim; Ali H Omar; Jason L Tackett; Mark A Vaughan; David M Winker; Charles R Trepte; Yongxiang Hu; Zhaoyan Liu; Lamont R Poole; Michael C Pitts; Jayanta Kar; Brian E Magill
Journal:  Atmos Meas Tech       Date:  2018       Impact factor: 4.176

3.  CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design.

Authors:  Jason L Tackett; David M Winker; Brian J Getzewich; Mark A Vaughan; Stuart A Young; Jayanta Kar
Journal:  Atmos Meas Tech       Date:  2018-07-17       Impact factor: 4.176

  3 in total

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