Recommandation on good practices for the preprocessing, quality control of solar radiation measurements and example of validation tools

Philippe Blanc, Alexandre Boilley, Benoit Gschwind, Adam R. Jensen, Lionel Ménard, Yves-Marie Saint-Drenan

Table of Contents

Preface

This notebook presents the motivation behind writing the notebook. Installation of libraries used throughout this notebook.

Chapter 1: Description of the netcdf dataformat used for the solar radiation measurements

In this chapter we provide a description of the structure of the netcdf used to store solar data. The data are uploaded in this format on a Thredds Data SErver (TDS), whose functionalities are exploited in the later part of this notebook.

*Further work on the data format are needed to include detailed metada*

Chapter 2: Accessing solar measurements

How to access to solar measurements using a Thredds Data Server.

 * we need a solution to handle the usr/pwd or change the dataset into an open source one *

Chapter 3: Quality control

Demonstrates example of good practices for preparing the data and conducting the most important QC procedures.

Chapter 4: Validation of a single satellite product at a single station

Example of validation routine for the CAMS Rad data.

 * we should find an alternative to using Alexander's mail to access CAMSRAD *

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Installation & Usage

You have several options to explore those notebooks :

Binder

You can launch the Notebooks via mybinder. You will have access to a live version of the notebooks, being able to interact with them.

Click on this button :

NbViewer

NbViewer provides a static rendering of the notebook. You will be able to see the code and results, by not to interact with them :

https://nbviewer.org/github/oie-mines-paristech/IEA_PVPS_T16_QC_pynb/tree/master/

Local installation

Alternatively, you can install and play those notebooks locally.

1. Clone this repository :

   git clone https://github.com/oie-mines-paristech/IEA_PVPS_T16_QC_pynb.git

2. Create and activate a virtual env

   virtualenv .venv source .venv/bin/activate.bash

3. Install dependencies

   pip install -r requirements.txt

4. Launch Jupyter

   jupter notebook