Aerosol concentration modeling based on satellite data
Run source code:
- Configure as you wish in
configuration.yml
- Run
python main.py
CAMS and aerosol data zipped inside raw/cams.zip
and raw/n100.zip
If using conda:
git clone https://github.com/hd4niel/aerosol-modeling.git
cd aerosol-modeling
conda env create -f environment.yml
conda activate inar
jupyter lab
conda deactivate inar
New dependencies
conda env export --no-builds | grep -v "^prefix: " > environment.yml
Remove environment
conda env remove --name inar
In case of problems with the environment:
conda create -n inar python=3.5.6
conda install -c anaconda pyyaml
conda install -c conda-forge cfgrib
conda install -c conda-forge ecmwf-api-client
conda install -c conda-forge jupyterlab
etc ...
conda activate inar
-
Log in to https://ecmwf.int
-
Save credentials at https://api.ecmwf.int/v1/key/ to
$HOME/.ecmwfapirc
-
Specify
load_data
inconfiguration.yml
-
Run
python main.py
Reanalysis data documentation
https://confluence.ecmwf.int/display/CKB/CAMS%3A+Reanalysis+data+documentation
Data
Efficiently retrieve daily data
https://confluence.ecmwf.int/display/WEBAPI/CAMS+Reanalysis+daily+retrieval+efficiency
Atmospheric model (we use 60, i.e. 10m above ground)
https://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels
Reference CAMS: 'Generated using Copernicus Atmosphere Monitoring Service Information 2020'.
https://confluence.ecmwf.int/pages/viewpage.action?pageId=58131166
Datasource:
In situ by INAR
Faster transfer speeds for future reference, released recently