Xin_ACP_2021_Convection_Effect

This repository provides the scripts and some of the data used in the 'Influence of convection on the upper tropospheric O3 and NOx budget in southeastern China' paper.

/namelists

Namelists used in the WRF-Chem simulation.

/notebooks

Python jupyter notebooks of plotting my paper's figures.

• Fig 01.

  (a) - (b) plot_ir_swath_traj.ipynb

  (c) - (d) ozonesondes.ipynb

• Fig 02. and Fig. 03.

  comp_wrf_radar.ipynb

• Fig 04., and Table 01.

  (a) - (c) ozone_profile_tendency_2019.ipynb

  (d) - (f) ozone_profile_tendency_2020.ipynb

• Fig 05.

  irr_timeseries.ipynb

• Fig 07., and Fig S05.

  s5p_wrfchem_2019.ipynb and s5p_wrfchem_2020.ipynb

• Fig 08.

  cp_crf.ipynb

• Fig S02.

  waccm_profiles.ipynb

• Fig S03. and S04.

  comp_wrf_radar.ipynb

/scripts

Plotting

• Fig S01

  plot_domain.py

• Fig 06.

  plot_flash_scd.py

• Fig S06

  plot_nox_profile.py

Processing

/subset_data

Some scripts used to subset original data and generate analysis data

• subset_wrfout.sh and subset_irr.sh

  Subset wrfout* files for useful variables

• generate_mean_o3_<yyyy>.py

  Generate mean O3 in region and pressure level

• generate_tendency_<yyyy>.py

  Generate summation of tendency between 8 km and 14 km.

• combine_irr_<yyyy>.py

  Subset irr* files and combine into one NetCDF file.

/data

Input data are all saved in the zenodo Dataset called Xin_ACP_2021_Convection_Effect_data.

Users can download the compressed file, extract it in the root directory, and rename to data. Then, all the Jupyter Notebooks should work well.