Analyzing Cloud Optical Properties Using Sky Cameras

With the spirit of reproducible research, this repository contains all the codes required to produce the results in the manuscript: S. Manandhar, S. Dev, Y. H. Lee and Y. S. Meng, Analyzing Cloud Optical Properties Using Sky Cameras, Proc. Progress In Electromagnetics Research Symposium (PIERS), 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.

Code Organization

The codes are written in python. Thanks to Joseph Lemaitre for providing the scripts to process MODIS multi bands images.

The cloud optical thickness data from MODIS satellite images are present in the folder COT, the average luminance data from sky cameras are present in the folder average_luminance, scripts to download MODIS data and various products can be found in the folder data_preparation, and the generated result is provided in the folder figs.

Dataset preparation

• modisGrabber.py Downloads the MODIS MOD- and MYD- level 5 products.
• Cloudopticalthickness.py Computes the cloud optical thickness values from the downloaded MODIS data files. It uses the function CloudProduct.py while extracting the cloud optical thickness values.

The calculated MODIS cloud optical thickness data are present in a 3X3 matrix. It is stored in .mat format, along with the corresponding date and time.

Core functionality

• calculate_luminance.py Calculates the average luminance from the sky camera images.
• normalize_array.py Normalizes a numpy array into the range [0,1]. The remaining python scripts are various helper functions used in the script calculate_luminance.py.

Reproducibility

In addition to all the related codes, we have shared the analysis figure in the folder ./figs.

Please run the notebook main.ipynb to generate the result mentioned in the paper.