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Bayesian modelling of CH4 and N2O fluxes from Ränskälänkorpi clearcut one year after the harvest

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LukeEcomod/FI-Ran_GHG_2022

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Reproduce Ränskälänkorpi clearcut EC 2024 manuscript results

Order of notebooks

  1. Create surface type specific contribution for each EC 30 min measurement point from EC footprint data create_footprint_soilclass_data.ipynb
  2. Combine all the measurement data into one netcdf file create_biomet_ec_fpr_dataset_all_time_points.ipynb
  3. Create heatmap of flux correlation between environmental variables GHG_env_correlation.ipynb
  4. Create inference data files for CH4 and N2O create_inference_data.ipynb
  5. Check the prior selection is adequate at GHG_models_prior_selection.ipynb
  6. Fit statistical models for CH4 and N2O GHG_models_fit.ipynb
  7. Run model comparison GHG_model_comparison.ipynb
  8. Run create_annual_and_temperature_predictions.ipynb to get model simulations for surface type specific fluxes and annual GHG budget
  9. Visualize the surface type specific fluxes and annual GHG budget GHG_st_T_response.ipynb
  10. Calculate annual GHG emission balance GHG_site_level_annual_flux.ipynb
  11. Calculate map parameter contribution to overall measured flux GHG_map_parameter_contribution.ipynb

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Bayesian modelling of CH4 and N2O fluxes from Ränskälänkorpi clearcut one year after the harvest

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