Geo_FFP

An automation for the Kljun et al. 2015 flux footprint (FFP) to generate monthly or cumulative single flux footprint map.

Kljun, N., Calanca, P., Rotach, M. W., & Schmid, H. P. (2015). A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP). Geoscientific Model Development, 8(11), 3695–3713.

Project structure

Geo_FFP/
│
├── main.py
├── config.yml
├── doc
├── requirements.txt
│
├── ffp_module/
│   ├── __init__.py          
│   ├── calc_footprint_FFP.py
│   ├── calc_footprint_FFP_climatology.py
│   ├── monthly_ffp.py
│   ├── FFP_clim_monthly.py
│   ├── GEE_module.py
│   ├── load_database.py

Setup

1. Clone the Geo_FFP

2. Change directory (cd) to Geo_FFP

3. Create the virtual environment

   a) using windows terminal or cmd python -m venv .venv

   • Note if "py" doesn't work - try "python" or "python3" instead - the call to python may be different depending on your installation

   b) using VScode

   1. Open the Geo_FFP folder in VS Code
   2. Hit ctrl + shift + p > and select "Create Python Environment"
   • Use Venv, not conda
   3. You will be prompted to select dependencies to install
   • Select "requirements.txt" form the menu. This will automatically install all required packages for you.

4. Activate the virtual environment .\.venv\Scripts\activate

5. Install dependencies pip install -r requirements.txt

   • you dont need to do it again if you are using VScode

Config the yml file and run

1. Open and edit config.yml

   • Provide database path, years, site name, tower height, lat long
   • You can set 1 to compute single cumulative FFP with run_single_ffp and monthly FFP with run_monthly_ffp

   Example

database:
  base_path: "C:/Users/joyso/Matlab/local_database_new1"
  years:
    - 2022
  site_name:
    - "YOUNG"
  levels:
    - "Clean/ThirdStage"
tower_height:
  - 4.08
variables:
  variables_to_read:
    - WS_1_1_1
    - hpbl
    - L
    - V_SIGMA
    - USTAR
    - WD_1_1_1
lat_lon:
  lat: 50.3623 
  lon: -100.2024
# -----------------------------
# PIPELINE CONTROL
# -----------------------------
pipeline:
  run_single_ffp: 1
  run_monthly_ffp: 1

2. Run the Geo_FFP python main.py
3. Output This will generate FFP map, netcdf and FFP model output (as pickle) and will store the output in the database folder with FFP_output (e.g. database\FFP_output).

  FFP_output/
  ├── Sitename
  │   ├── year  
  │   │   ├── map
  │   │   ├── netcdf
  │   │   ├── pickle

Example