Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth
Abstract
A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (θs), and pixel zenith angle/view angle (θz). The effects of these parameters are described and the functions for radiance, Iλ
- Authors:
-
- Univ. of California, San Diego, La Jolla, CA (United States)
- Publication Date:
- Research Org.:
- Univ. of California, San Diego, La Jolla, CA (United States). Center for Renewable Resources and Integration, Department of Mechanical and Aerospace Engineering
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1375414
- Grant/Contract Number:
- DGE-1144086
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Atmospheric Measurement Techniques (Online)
- Additional Journal Information:
- Journal Name: Atmospheric Measurement Techniques (Online); Journal Volume: 9; Journal Issue: 8; Journal ID: ISSN 1867-8548
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Mejia, Felipe A., Kurtz, Ben, Murray, Keenan, Hinkelman, Laura M., Sengupta, Manajit, Xie, Yu, and Kleissl, Jan. Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth. United States: N. p., 2016.
Web. doi:10.5194/amt-9-4151-2016.
Mejia, Felipe A., Kurtz, Ben, Murray, Keenan, Hinkelman, Laura M., Sengupta, Manajit, Xie, Yu, & Kleissl, Jan. Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth. United States. https://doi.org/10.5194/amt-9-4151-2016
Mejia, Felipe A., Kurtz, Ben, Murray, Keenan, Hinkelman, Laura M., Sengupta, Manajit, Xie, Yu, and Kleissl, Jan. Tue .
"Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth". United States. https://doi.org/10.5194/amt-9-4151-2016. https://www.osti.gov/servlets/purl/1375414.
@article{osti_1375414,
title = {Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth},
author = {Mejia, Felipe A. and Kurtz, Ben and Murray, Keenan and Hinkelman, Laura M. and Sengupta, Manajit and Xie, Yu and Kleissl, Jan},
abstractNote = {A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (θs), and pixel zenith angle/view angle (θz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, θs,θz, and RBRτc,θ0, θs, θz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasθs, θz, in addition to RBRmeasθs, θz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI have an RMSE of 2.2, which is well within the uncertainty of the MWR. In conclusion, the procedure developed here provides a foundation to test and develop other cloud detection algorithms.},
doi = {10.5194/amt-9-4151-2016},
journal = {Atmospheric Measurement Techniques (Online)},
number = 8,
volume = 9,
place = {United States},
year = {Tue Aug 30 00:00:00 EDT 2016},
month = {Tue Aug 30 00:00:00 EDT 2016}
}
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