Scripts used for the data analysis for ACP paper 2023. Including function files, and Jupyter notebooks.
See below for figure and corresponding notebook:
| Figures | Notebook |
|---|---|
| Figure1 | Harmonisation_inc_figure1 |
| Figure2 | Trend_plots_in_abs_ATP_inc_figures2_6_S8_S13 |
| Figure3 | Spatial_trends_using_CWT_arrays_inc_figure3 |
| Figure4 | Cluster_mappings_inc_figure4 |
| Figure5 | Cluster_plots_inc_figure5_S12_S6 |
| Figure6 | Trend_plots_in_abs_ATP_inc_figures2_6_S8_S13 |
| Figure7 | Calculating_estimated_abs_from_ATP_figure7 |
| Table1 | Collocate_back_trajs_with_GFED_inc_table1 |
| FigureS1 | Data_availability_inc_figureS1 |
| FigureS2 | Compare_data_with_aethalomter_inc_figureS2_S3 |
| FigureS3 | Compare_data_with_aethalomter_inc_figureS2_S3 |
| FigureS4 | Read_aethalometer_cal_AAE_inc_figureS4 |
| FigureS5 | Collocate_ERA5_and_back_trajectorys_vectorized_inc_S5 |
| FigureS6 | Cluster_plots_inc_figure5_S12_S6 |
| FigureS7 | Active_fires_MODIS_gridding_with_hysplit_inc_figureS7 |
| FigureS8 | Trend_plots_in_abs_ATP_inc_figures2_6_S8_S13 |
| FigureS9 | Calculates_SSA_inc_S9 |
| FigureS10 | Concentration_weighted_plots_inc_figureS10 |
| FigureS11 | Masks_eclipse_trend_array_inc_figureS11 |
| FigureS12 | Cluster_plots_inc_figure5_S12_S6 |
| FigureS13 | Trend_plots_in_abs_ATP_inc_figures2_6_S8_S13 |
| FigureS14 | Seasonality_plot_inc_figureS14 |
| FigureS15 | Extremes_values_inc_figureS15 |
| FigureS16 | Arithmetic_trends_impact_of_fires_inc_figureS16 |
| FigureS17 | Calculating_estimated_abs_from_ATP_figure7 |
Notebooks Description
Harmonisation_inc_figure1 compare instruments:
- applying correction factors
- produce harmonised timeseries
Data_availability_inc_figureS1:
- loads the data sets
- plots the data availability as a simple bar chart
Cluster_mappings_inc_figure4:
- load the data for the clusters
- plot all the lat and lon endpoints as frequency plots
Concentration_weighted_plots_inc_figureS10:
- Reads in full years’ worth of data
- generates the CWT arrays, saves them.
- Also, loads the arrays that were made for the manuscript
Extremes_values_inc_figureS15:
- Generates the extreme values by defining them using a rolling percentile of 15-days 99th, 95th etc...
Active_fires_MODIS_gridding_with_hysplient_inc_figureS7:
- Uses the MODIS Satellite data
- Grids the number active fires
- Counts the number of fires in grids traversed
Seasonality_plot_inc_figureS14:
- plot for the annual cycle
- for ECLIPSE emission inventory
- Accumulated back trajectory precipitation (ATP)
Spatial_trends_using_CWT_arrays_inc_figure3:
- Produces the spatial trend plots using the CWT arrays, which are loaded in
Masks_eclipse_trend_array_inc_figureS11:
- Uses the trend arrays to apply a mask for the eclipse array
Trend_plots_in_abs_ATP_inc_figures2_6_S8_S13:
- Subplot for the trends in the absorption coefficient
- Trend for all seasons for the precipitation
Cluster_plots_inc_figure5_S12_S6:
- Reads in the data files containing the cluster data sets
Compare_data_with_aethalomter_inc_figureS2_S3:
- comparison between with Aethalometer and all the different instruments
- comparisons with 3-month intervals of the PSAPs and MAAP
Read_aethalometer_cal_AAE_inc_figureS4:
- read in the Aeth data and calculate the Absorbing Ångström Exponent.
- produce the data file for the full time series of the Aethalometer data at 660 nm
- Arithmetic_trends_impact_of_fires_inc_figureS16 Removes the extreme B.B. events from the data set to see the impact
Calculates_SSA_inc_S9:
- Calculates SSA
- Timeseries of the absorption coefficient, scattering coefficient and single scattering albedo
Collocate_back_trajs_with_GFED_inc_table1:
- Here we read in the HYSPLIT data then we collocate it with the Global Fire Emission Database, which we have pre-processed and saved as .nc files
- Saves as a GFED.dat file
Calculating_estimated_abs_from_ATP_figure7:
- Compare absorption and precipitation
- Map values to estimate time series
Collocate_ERA5_and_back_trajectorys_vectorized_inc_S5:
- Collocates the ERA data with the HYSPLIT output
- produces figureS5
Processing scripts only:
Converts_global_fire_emission_database_tonetcdf:
- Converts hdf5 files to netcdf for later
- Processes_hysplit_output takes the 'raw' HYSPLIT data i.e. what you get from the output, processes them one by one and saves them in a form with also distance calculated and also the rotated latitudes and longitudes as grid cells.
Generate_trend_mapping_for_ECLIPSE_and_array:
- Plots the trend array for the ECLIPSE emissions and generates the trend array .txt file
Looks_for_missing_hysplit_output:
- look at the folders where you have saved your runs.
- Create a dataframe which lists the missing runs
- Once the dataframe of the missing datetimes is created.
- loop through them and generate HYSPLIT files for them.
Generates_back_trajectories_using_pysplit_and_GDAS:
- Use Pysplit to generate trajectories with metrological data from GDAS
Generates_back_trajectories_using_pysplit_and_FNL:
- Use Pysplit to generate trajectories with metrological data from FNL (different due to the resolution)
Reads_in_and_processes_MAAP_data:
- process the MAAP data
Reads_in_ecotech_data:
- read in and process the Ecotech nephelometer
Compare_TSI_Ecotech:
- compare the TSI and Ecotech data
Reading_in_the_automatic_PSAP_data_applying_Bond:
- reads the raw PSAP data processes it and applies bond
Reading_in_the_manual_PSAP_data_applying_Bond:
- reads the raw PSAP data processes it and applies bond