Cloud Radiative Effect Study Using Sky Camera

With the spirit of reproducible research, this repository contains all the codes required to produce the results in the manuscript: S. Dev, S. Manandhar, F. Yuan, Y. H. Lee and S. Winkler, Cloud Radiative Effect Study Using Sky Camera, Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, 2017.

Please cite the above paper if you intend to use whole/part of the code. This code is only for academic and research purposes.

Manuscript

The author version of this manuscript is manuscript.PDF.

Code Organization

All codes are written in python. Thanks to Florian Savoy for contributing the camera calibration code used in undistorting a sky/cloud image.

Dataset

All input dataset can be found in the folder ./input.

Core functionality

• color16mask.py Generates the red and blue ratio channel.
• import_WS_CI.py Imports the weather station data and also calculates the clearness index.
• internal_calibration.py Provides the internal calibration model of our sky camera.
• make_cluster_mask.py Generates the output binary sky/cloud image and computes the cloud coverage.
• nearest.py Finds the nearest datapoint according to a criterion.
• normalize_array.py Normalizes an input array.
• SG_solarmodel.py Computes the total solar irradiance for Singapore clear sky model.
• showasImage.py Normalizes an array/matrix in the range [0,255].
• undistortImg.py Undistorts a sky/cloud image based on the camera calibration model.

Reproducibility

In addition to all the related codes, we have also shared the generated results. These files are contained in the folder ./results.

The program ./Cloud Radiative Effect Study Using Sky Camera.ipynb is the main script, that reproduces all the results. It uses different helper scripts stored in the folder ./helperFunctions. It also reproduces the figures in this associated paper.