Satellite Estimated Solar Irradiance Over the Oceans

Project by Group 7

Course: Future Power Supply
Degree: Master of Engineering Physics
Institution: University of Oldenburg
Semester: Summer Semester 2024

Tutor: Arindam Roy
Authors: Juan Manuel Boullosa Novo, Sofiane Saidi

Project Structure

This project aims to estimate solar irradiance at the location of a ship using satellite data. The project involves:

1. Data Acquisition: Downloading satellite data from the OSI-SAF website and reading ship data from NetCDF files.
2. Data Processing: Preprocessing the satellite data, interpolating it to the ship's location and time, and calculating the clear sky index.
3. Data Analysis: Comparing the interpolated satellite data with the ship's measurements and analyzing the differences using the clear sky index.
4. Visualization: Creating animations and plots to visualize the ship's trajectory, the satellite data, and the comparison between the two.

Codebase Structure

The codebase is primarily written in Python and consists of several scripts and Jupyter notebooks. Here's an overview of the files and folders:

Files

• README.md: This file provides an overview of the project, usage instructions, configuration details, and dependencies.
• analyse_cdf.py: This script analysis the general structure of a netCDF file for further exploration.
• check_sat_grid_trajectory.py: This script checks and plots the satellite data grid size and compares it to the ship's trajectory hourly to find suitability.
• read_data_sat_animation.py: This script reads NetCDF files from a specified directory, extracts relevant variables (latitude, longitude, time, and short-wave radiation), and creates an animation of the satellite data with the ship's trajectory on the map.
• read_data_ship_animation.py: This script reads the ship's NetCDF files and extracts the relevant variables (latitude, longitude, time, and short-wave radiation), and creates an animation of the ship's trajectory on the map.
• webscrap.py: This script downloads satellite data from the OSI-SAF website for a specified date range.
• interpolate_sat.py: This script interpolates the satellite data to the ship's location and time, generates a CSV file with the interpolated data and plots the interpolated data on a map.
• error_speed_analysis.py: This script analyzes the residuals and the error (MBE, RMSE) between the interpolated satellite data and the ship's measurements for different days and plots the errors.
• Other Python scripts and Jupyter notebooks for specific tasks or exploratory data analysis.

Folders

• data/: This folder contains the data files used in the project.
  • data/satellite/: This folder stores the downloaded satellite data files in NetCDF format, organized by year and day.
  • data/samos/: This folder contains the ship data files in NetCDF format.
  • data/processed/: This folder stores processed data files, such as interpolated satellite data and combined ship data in CSV format.
• figures/: This folder contains generated plots and visualizations.
• docs/: This folder contains some helping documentation of the project.

Dependencies

The project relies on the following Python libraries:

• pandas: For data manipulation and analysis.
• netCDF4: For reading and processing NetCDF files.
• matplotlib: For creating static visualizations.
• cartopy: For creating maps and plotting geographic data.
• xarray: For efficient handling of multi-dimensional data arrays.
• pvlib: For calculating clear sky irradiance using solar radiation models.
• requests and BeautifulSoup: For web scraping and downloading satellite data from the OSI-SAF website.

These dependencies can be installed using pip or conda package managers.

Usage

The main scripts (read_data.py, download_satellite_data.py, and process_data.py) provide instructions on how to use them, including configuration options and required inputs. The README.md file also includes usage instructions and configuration details.

[read_data.py]

USAGE:

1. Read Data:

   • Reads all NetCDF (.nc) files from a specified directory.
   • Gets the following variables: latitude ('lat'), longitude ('lon'), time ('time'), and short-wave radiation ('RAD_SW').
   • Time data should be in minutes since January 1, 1980 (epoch time).

2. Plot Data:

   • Visualize the animated trajectory on a map and plot the radiation over time side by side.

CONFIG:

• folder_path: Set this variable to the directory containing your NetCDF files.
• variables: What to extract from the NetCDF files. Default is ['latitude', 'longitude', 'time', 'radiation'].
• variables_to_plot: Default is plotting 'radiation' against time and showing the trajectory on the map.