This tutorials repository relies on packages found in the available requirements.txt file.
pip install -r requirements.txt
conda create --name <env_name> --file requirements.txt
CFAPI is a RESTful API that allows users to access GEOS-CF model forecasts and historical estimates.
Documentation for using the API via URL and curl requests can be found here.
This repository also contains a jupyter notebook that shows some examples for accessing and plotting a GEOS-CF forecast by requesting information from CFAPI.
Google Earth Engine provides a multi-petabyte catalog of satellite imagery and geospatial datasets. Selected collections from the GEOS Composition Forecast model were added to this catalog for easy availability in the GEE code editor and via the GEE Python API.
The tutorial available in this repository explains how to access the GEOS-CF data via the GEE Python API. Users will visualize the data in time-series and in interactive maps along with data from the TROPOMI instrument. This plots and maps visualize tropospheric NO2 concentrations.