Disclaimer: This material is being kept online for historical purposes. Though accurate at the time of publication, it is no longer being updated. The page may contain broken links or outdated information, and parts may not function in current web browsers. Visit https://espo.nasa.gov for information about our current projects.


Automated cloud screening algorithm for MFRSR data

Alexandrov, M. D., A. Marshak, A. Lacis, and B. E. Carlson (2004), Automated cloud screening algorithm for MFRSR data, Geophys. Res. Lett., 31, L04118, doi:10.1029/2003GL019105.

A new automated cloud screening algorithm for ground-based sun-photometric measurements is described and illustrated on examples of real (MFRSR) and simulated data. The algorithm uses single channel direct beam measurements and is based on variability analysis of retrieved optical thickness. To quantify this variability the inhomogeneity parameter e is used. This parameter is commonly used for cloud remote sensing and modeling, but not for cloud screening. In addition to this an adjustable enveloping technique is applied to control strictness of the selection method. The key advantages of this technique are its objectivity, computational efficiency and the ability to detect short clear-sky intervals under broken cloud cover conditions. Moreover, it does not require any knowledge of the instrument calibration. The performance of the method has been compared with that of AERONET cloud screening algorithm.

PDF of Publication: 
Download from publisher's website.
Research Program: 
Radiation Science Program (RSP)