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https://github.com/augustinmortier/aer-ifs

Compute aerosol properties maps from ECMWF IFS model data

https://github.com/augustinmortier/aer-ifs

Science Score: 26.0%

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Keywords

aerosols ecmwf-cams modelling science
Last synced: 5 months ago · JSON representation

Repository

Compute aerosol properties maps from ECMWF IFS model data

Basic Info
  • Host: GitHub
  • Owner: AugustinMortier
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 4.63 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 1
  • Open Issues: 1
  • Releases: 15
Topics
aerosols ecmwf-cams modelling science
Created over 1 year ago · Last pushed 8 months ago
Metadata Files
Readme License

README.md

aer-IFS

Compute aerosol optical properties maps based on ECMWF IFS forecasts. - Lidar Ratio (LR) - Mass to Extinction Coefficient (MEC)

LR computation methodology: - We get the IFS forecasts data of aerosol optical depth forecasts for the different chemical components. - We get the IFS forecasts data of relative humidity. - For each aerosol species, we calculate a LR weighted by the relative optical depth contribution for different RH values. - The total LR is determined as the sum of the weighted LR of the different aerosols species.

Individual aerosol LR are taken from the IFS 49R1 input configuration file. For each species, a specific column is selected, which might correspond to a specific range bins or according to the given literature reference.

example

aer-ifs --date 2024-10-15

LR

IFS LR - 2024-10-15 - 1064 nm

MEC

IFS MEC - 2024-10-15 - 1064 nm

get started

1. clone repo

git clone https://github.com/AugustinMortier/aer-ifs.git

2. install

  • via poetry poetry install

  • via pip/pipx pip install .

[!NOTE] You can also install lr-ifs with this one liner: pip install "git+ssh://git@github.com/AugustinMortier/aer-ifs.git"

how to use

Compute LR and MEC for the 2024-09-26

aer-ifs --date 2024-09-26

This will create into output_path (default: ./data/): - {yyyy}/{mm}/lr_ifs-{yyyymmdd}.nc: netcdf file which contains the computed LR and MEC. - {yyyy}/{mm}/lr_ifs-{yyyymmdd}.json (if aprofiles option enabled (default)): json file which contains, for each E-PROFILE station available and for the selected day, the corresponding IFS-LR and IFS-MEC.

limitations

  • Only one value per day is computed at the moment and corresponds to 00:00:00Z.
  • Only one value per column is computed at the moment. Only the surface RH is considered for the calculation.

Owner

  • Name: augustinm
  • Login: AugustinMortier
  • Kind: user
  • Location: Oslo, Norway
  • Company: @metno

GitHub Events

Total
  • Release event: 8
  • Watch event: 1
  • Delete event: 1
  • Push event: 23
  • Pull request event: 4
  • Create event: 8
Last Year
  • Release event: 8
  • Watch event: 1
  • Delete event: 1
  • Push event: 23
  • Pull request event: 4
  • Create event: 8

Dependencies

pyproject.toml pypi
  • cartopy ^0.23.0 develop
  • ipykernel ^6.29.5 develop
  • dask ^2024.9.0
  • matplotlib ^3.9.2
  • netcdf4 ^1.7.1.post2
  • python ^3.10
  • rich ^13.8.1
  • scipy ^1.14.1
  • typer ^0.12.5
  • xarray ^2024.9.0