meteosatpy 0.0.5

Library designed for downloading and managing meteorological data sourced from satellites and global models.

MeteoSatPy

What is it?

MeteoSatPy is a Python library designed for downloading and managing hydro-meteorological data sourced from satellites and global models. It offers users efficient access to near-real-time and historical weather conditions globally. With features for data acquisition, processing, and analysis. MeteoSatPy is a versatile tool for meteorological research, forecasting, and decision-making across various sectors.

Where to get it?

The source code is currently hosted on GitHub at: https://github.com/jusethCS/meteosatpy

Binary installers for the latest released version are available at the Python Package Index (PyPI) and on Conda

# PyPI
pip install meteosatpy

# Conda
conda install juseth.chancay::meteosatpy

Dependencies

• rasterio: Reads and writes raster formats based on Numpy N-dimensional arrays.
• xarray: Works with labelled multi-dimensional arrays simple and efficient.
• geopandas: Analysis and manipulation of geographical data.
• request: HTTP library for making requests and working with web APIs.

Prior to installing MeteoSatPy using PyPi, we recommend creating a new conda environment with dependencies:

# Conda
conda create -n [env_name] geopandas rasterio xarray requests

If you need to download MSWEP data, you'll need to install Rclone.

# Conda
conda install conda-forge::rclone

To set up Rclone with a Google Drive account, we recommend watching this tutorial. Note the MSWEP data are store on this Google Drive repository.

Examples

import datetime as dt
import meteosatpy

# Target date
date = dt.datetime(2010, 1, 1) # year, month, day

# Download CHIRPS data
ch = meteosatpy.CHIRPS()
ch.download(
    date=date, 
    timestep="daily", 
    outpath=date.strftime("chirps_%Y-%m-%d.tif")
)

# Download CMORPH data
cm = meteosatpy.CMORPH()
cm.download(
    date=date, 
    timestep="daily", 
    outpath=date.strftime("cmorph_%Y-%m-%d.tif")
)

# Download MSWEP data
mw = meteosatpy.MSWEP()
mw.download(
    date=date, 
    timestep="daily", 
    dataset="Past",
    outpath=date.strftime("mswep_%Y-%m-%d.tif"))

# Download IMERG v07 final run
im = meteosatpy.IMERG(user="username", pw="pass")
im.download(
    date=date, 
    version="v07", 
    run="final", 
    timestep="daily", 
    outpath=date.strftime("imerg_%Y-%m-%d.tif")
)