Two decades observing smoke above clouds in the south-eastern Atlantic Ocean: Deep Blue algorithm updates and validation with ORACLES field campaign data
-
Published:2019-07-04
Issue:7
Volume:12
Page:3595-3627
-
ISSN:1867-8548
-
Container-title:Atmospheric Measurement Techniques
-
language:en
-
Short-container-title:Atmos. Meas. Tech.
Author:
Sayer Andrew M.ORCID, Hsu N. Christina, Lee Jaehwa, Kim Woogyung V.ORCID, Burton Sharon, Fenn Marta A., Ferrare Richard A., Kacenelenbogen Meloë, LeBlanc SamuelORCID, Pistone KristinaORCID, Redemann JensORCID, Segal-Rozenhaimer Michal, Shinozuka Yohei, Tsay Si-Chee
Abstract
Abstract. This study presents and evaluates an updated algorithm for quantification of absorbing aerosols above clouds (AACs) from passive satellite measurements. The focus is biomass burning in the south-eastern Atlantic Ocean during the 2016 and 2017 ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign deployments. The algorithm retrieves the above-cloud aerosol optical depth (AOD) and underlying liquid cloud optical depth and is applied to measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) from 1997 to 2017. Airborne NASA Ames Spectrometers for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) and NASA Langley High Spectral Resolution Lidar 2 (HSRL2) data collected during ORACLES provide important validation for spectral AOD for MODIS and VIIRS; as the SeaWiFS mission ended in 2010, it cannot be evaluated directly. The 4STAR and HSRL2 comparisons are complementary and reveal performance generally in line with uncertainty estimates provided by the optimal estimation retrieval framework used. At present the two MODIS-based data records seem the most reliable, although there are differences between the deployments, which may indicate that the available data are not yet sufficient to provide a robust regional validation. Spatiotemporal patterns in the data sets are similar, and the time series are very strongly correlated with each other (correlation coefficients from 0.95 to 0.99). Offsets between the satellite data sets are thought to be chiefly due to differences in absolute calibration between the sensors. The available validation data for this type of algorithm are limited to a small number of field campaigns, and it is strongly recommended that such airborne measurements continue to be made, both over the southern Atlantic Ocean and elsewhere.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference125 articles.
1. Ahmad, Z., McClain, C. R., Herman, J. R., Franz, B. A., Kwiatkowska, E. J.,
Robinson, W. D., Bucsela, E. J., and Tzortziou, M.: Atmospheric correction
for NO2 absorption in retrieving water-leaving reflectances from the
SeaWiFS and MODIS measurements, Appl. Opt., 46, 6504–6512,
https://doi.org/10.1364/AO.46.006504, 2007. a 2. Alfaro-Contreras, R., Zhang, J., Campbell, J. R., and Reid, J. S.: Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI, Atmos. Chem. Phys., 16, 47–69, https://doi.org/10.5194/acp-16-47-2016, 2016. a 3. Banks, A. C. and Mélin, F.: An assessment of cloud masking schemes for
satellite ocean colour data of marine optical extremes, Int. J. Remote Sens.,
36, 797–821, https://doi.org/10.1080/01431161.2014.1001085, 2015. a 4. Barnes, W. L., Pagano, T. S., and Salomonson, V. V.: Prelaunch characteristics
of the Moderate Resolution Imaging Spectroradiometer (MODIS) on
EOS-AM1, IEEE T. Geosci. Remote, 36, 1088–1100,
https://doi.org/10.1109/36.700993, 1998. a 5. Ben-Ami, Y., Koren, I., and Altaratz, O.: Patterns of North African dust transport over the Atlantic: winter vs. summer, based on CALIPSO first year data, Atmos. Chem. Phys., 9, 7867–7875, https://doi.org/10.5194/acp-9-7867-2009, 2009. a, b
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|