BS-FDBCK

Analysis for BSOA paper:

Blichner, S.M. et al. (2024) ‘Process-evaluation of forest aerosol-cloud-climate feedback shows clear evidence from observations and large uncertainty in models’, Nature Communications, 15(1), p. 969. Available at: https://doi.org/10.1038/s41467-024-45001-y.

Setup:

Download:

git clone [email protected]:sarambl/BS-FDBCK.git 
cd BS-FDBCK/

Install environment:

# install environment etc
conda env create -f environment.yml
conda activate env_bs_fdbck
conda develop .

cd ../
git clone https://git.nilu.no/ebas/ebas-io.git  cd
cd ebas-io/dist/
pip install ebas_io-3.6.1-py3-none-any.wh

Download data:

• The SMEAR-II size distribution data was downloaded from the EBAS database and are available for download at ebas-data.nilu.no. The temperature and wind measurements from SMEAR-II is available for download at: https://smear.avaa.csc.fi.

• The full ATTO aerosol measurement data sets can be downloaded in the ATTO data portal under https://www.attodata.org/.

• Temperature measurements from ATTO are available for download at https://www.attodata.org/.

• Model data can be downloaded from: https://doi.org/10.17043/blichner-2023-bvoc-aerosol-1

Edit settings and paths:

Edit paths at the top of bs_fdbck_clean/constants.py.

Data organising:

The observational data is organised as follows:

SMEAR:

Meteo data:

Pressure: 'Data/SMEARII/smeardata_20230307_pressure.csv' Radiation: 'Data/SMEARII/smeardata_20221116_radiation.csv' Temperature:'Data/SMEARII/smeardata_20230307_temp4m.csv' Meteo: 'Data/SMEARII/smeardata_20221116_2012-2014.csv','Data/SMEARII/smeardata_20221116_2014-2016.csv','Data/SMEARII/smeardata_20221116_2016-2018.csv', 'Data/SMEARII/smeardata_20221116_2018-2019.csv',

Size distribution:

'Data/EBAS/raw_data/SMR/FI0050R.20120101000000.20181205100800.dmps.particle_number_size_distribution.pm10.1y.1h.FI03L_UHEL_DMPS_HYY_01.FI03L__TRY_TDMPS.lev2.nc'

ACSM data:

'Data/ACSM_DEFAULT.mat'

ATTO:

Meteo data:

'Data/ATTO/meteodataComplete.dat' 'Data/ATTO/meteo/*'

Size distribution:

'Data/ATTO/ds_atto_2014_2019_4Sara.nc'

ACSM data:

'Data/ATTO/QACSM_time_series_C4_60m_2014_2016STP_v3.xlsx' 'Data/ATTO/acsm_data_for_sara_2017.txt'

Satellite data:

Download satellite data from https://ladsweb.modaps.eosdis.nasa.gov/search/order/2/MYD08_D3--61 to directory: 'Data/satellite/MODIS_raw/'

To reproduce results:

Preprocess model data:

cd bs_fdbck_clean/preprocess/
chmod +x preprocess.sh
./preprocess.sh

Run notebooks:

Run the notebooks in bs_fdbck_clean/notebooks according to their ordering.

cd bs_fdbck_clean/notebooks/01-01-preprocess_station_data/
python 01-01-01-Preprocess_measurement_dataset_HYYTIALA.py
python 01-01-02-Preprocess_ACSM_meteo_sizedit_data_ATTO.py
python 01-01-03-Preprocess_dataset_MODELS_SMR.py
python 01-01-04-Preprocess_dataset_MODELS_ATTO.py

cd ../01-02-preprocess_satellite/
python 01-02-01-download_and_preproc_MODIS.py
python 01-02-02-produce_hyytiala_satellite_dataset.py
python 01-02-03_produce_ATTO_satellite_dataset.py

cd ../02-T2OA_OA2Nx/
python 02-01-relations_plots_TOANx_SMR.py
python 02-02-relation_plots_TOANx_ATTO.py
python 02-03-plot_both_stations_together.py
python 02-04-01_relations_plots_emissions_ATTO.py
python 02-04-01_relations_plots_emissions_SMR.py

cd ../03-cloud_properties/03-01-ATTO
python 03-01-01-create_file-ALL_year_new_version.py
python 03-01-03-01_confidence_interval_diff_median_my_data-ATTO_FMA.py
python 03-01-03-02_confidence_interval_diff_median_my_data-ATTO_Nx_FMA.py
python 03-01-04-01_confidence_interval_diff_median_my_data-ATTO_FMAM.py
python 03-01-05-01_confidence_interval_diff_median_my_data-ATTO_JFM.py
python 03-01-07-01_confidence_interval_diff_median_my_data-ATTO_JFMAM.py
python 03-01-08-01_confidence_interval_diff_median_my_data-ATTO_MAM.py


cd ../03-02-SMR
python 03-02-01-create_file.py
python 03-02-02-01_confidence_interval_diff_median_my_data-SMR_JA.py
python 03-02-02-02_confidence_interval_diff_median_my_data-SMR_JA-Nx.py

cd ../
python 03-03-compare_differentials.py

cd ../04-evaluation_measurements
python 04-01-OA_against_OA.py
python 04-02-OA_against_OA_ATTO.py
python 04-03-Nx_SMR.py
python 04-04-Nx_ATTO.py
python 04-05_NorESM_yield.ipynb