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README.txt
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The folder "Software" contains all code that was used for plotting of data and for calculations done for the corresponding published manuscript "Continuous secondary ice production initiated by updrafts through the melting layer in mountainous regions" by Lauber et al. 2021, ACP. The corresponding data is published under https://doi.org/10.5281/zenodo.4534382.
Functions holding different copyrights are stated in the README file in the folder "Software".
In the following, all functions and data used for each plot are named as well as the plotting routine. The original publication for each data is named under origin.
Figure 1
Plot DHM with measurement locations
Origin: https://shop.swisstopo.admin.ch/de/products/height_models/dhm25200
Functions: plot_DHM.m, xyzread.m, xyz2grid.m, cbarrow.m
Data: /Data/DHM25/DHM200.xyz
Run on MATLAB:
path_DHM = '.../Data/DHM25/DHM200.xyz';
[x,y,z] = xyzread(path_DHM);
grid = xyz2grid(x,y,z);
xpos = [-10 10];
ypos = [-10 10];
plot_DHM(x,y,grid,'large',xpos,ypos,0);
plot_DHM(x,y,grid,'small',xpos,ypos,0);
Figure 3
Cloud radar plot
Origin: Cloudnet
Functions: read_cloud_radar.m, plot_cloud_radar.m, get_runs.m
Data: /Data/HoloGondel/190222_runs_gondola_up.txt, /Data/Cloudnet/20190222_davos_categorize.nc
Run on MATLAB:
ncpath= '.../Data/Cloudnet/';
runs_path = '.../Data/HoloGondel/190222_runs_gondola_up.txt';
YMD = '20190222';
[radar,height,~] = read_cloud_radar(ncpath,YMD);
startDate=datenum(2019,02,22,06,00,00);
endDate=datenum(2019,02,22,12,00,00);
runs = get_runs(runs_path);
plot_cloud_radar(radar,height,startDate,endDate,runs);
Ceilometer plot
Origin: http://dx.doi.org/10.16904/envidat.127
Functions: get_Klosters_data_from_files.m, plot_ceilometer.m, magma.m
Data: /Data/Ceilometer, /Data/HoloGondel/190222_runs_gondola_up.txt
Run on MATLAB:
root_folder='.../Data/Ceilometer/';
runs_path = '.../Data/HoloGondel/190222_runs_gondola_up.txt';
start_str = '20190222060000';
end_str = '20190222120000';
[cl31, ~, ~]=get_Klosters_data_from_files(start_str,end_str,root_folder);
runs = get_runs(runs_path);
plot_ceilometer(cl31,start_str,end_str,runs);
Temperature and RH plot
Origin: HoloGondel, http://dx.doi.org/10.16904/envidat.129
Functions: plot_temp_RH_Klosters_gondola.py, read_log_files.py, read_time_rides.py
Data: /Data/HoloGondel/190222_holimo_log.txt, /Data/HoloGondel/190222_runs_gondola_up.txt, /Data/Klosters_weather/raclets_weather_klosters.mat
Run on Python:
path_log_file = '.../Data/HoloGondel/190222_holimo_log.txt'
path_time_rides '.../Data/HoloGondel/190222_runs_gondola_up.txt'
path_data_Klosters = '.../Data/Klosters_weather/raclets_weather_klosters.mat'
from plot_temp_RH_Klosters_gondola import *
plot_temp_RH_Klosters_gondola(path_log_file,path_time_rides,path_data_Klosters)
Figure 4
Plot wind profiler
Origin: http://dx.doi.org/10.16904/envidat.130
Functions: plot_wind_profiler.m, windbarbs.m, uv2ddff.m
Data: /Data/Wind_profiler/wp_high_20190222_dav.csv
Run on MATLAB:
wind_path = '.../Data/Wind_profiler/wp_high_20190222_dav.csv';
plot_wind_profiler(wind_path)
Plot DHM with wind
Origin: https://shop.swisstopo.admin.ch/de/products/height_models/dhm25200, last access: 9 March 2020, Bundesamt für Meteorologie und Klimatologie, MeteoSchweiz
Functions: get_wind_IDAWEB.py, plot_DHM.m, xyzread.m, xyz2grid.m, windbarbs.m, cbarrow.m
Data: /Data/DHM25/DHM200.xyz, /Data/Wind/order_80401_data.txt, /Data/Wind/Holfuy_data.csv
Run on MATLAB:
path_DHM = '.../Data/DHM25/DHM200.xyz';
[x,y,z] = xyzread(path_DHM );
grid = xyz2grid(x,y,z);
xpos = [-17 10];
ypos = [-10 15];
plot_DHM(x,y,grid,'small',xpos,ypos,1);
Figure 5
Plot random sample of ice crystals
Origin: HoloGondel
Functions: save_particle_images.m
Data: /Data/HoloGondel/ice_habits
Run on MATLAB:
ice_crystals_path = '.../Data/HoloGondel/ice_habits';
saving_folder = '.../Data/HoloGondel/';
per = 40;
save_particle_images(ice_crystals_path,saving_folder,per)
Plot histogram of size distribution of ice crystal habits
Origin: HoloGondel
Functions: plot_size_spectrum_ice.m, get_uncertainty_ice.m
Data: /Data/HoloGondel/ice_habits.mat, /Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc
Run on MATLAB
ice_crystals_path = '.../Data/HoloGondel/ice_habits';
V_source = '.../Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc';
plot_size_spectrum_ice(ice_crystals_path,V_source)
Figure 6
Plot cloud particle concentration over time
Origin: HoloGondel
Functions: plot_conc_time.m, get_uncertainty_ice.m, get_runs.m, rgb.m, mseb.m
Data: /Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc, /Data/HoloGondel/RACLETS_merged_8-10h_lt_25e-6.nc', /Data/HoloGondel/ice_habits.mat, /Data/HoloGondel/190222_runs_gondola_up.txt
Run on MATLAB
source_big = '.../Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc';
source_small = '.../Data/HoloGondel/RACLETS_merged_8-10h_lt_25e-6.nc';
ice_crystals_path = '.../Data/HoloGondel/ice_habits';
runs_path = '.../Data/HoloGondel/190222_runs_gondola_up.txt';
runs = get_runs(runs_path);
plot_conc_time(source_big,source_small,ice_crystals_path,runs)
Figure 8
Plot parameter over droplet size
Origin: HoloGondel
Functions: calculate_production_rate_observations.py, diffusional_growth_plates.py, calculate_splinter_production.m, get_fall_velocity.m, get_fcol.m, get_pdf.m, plot_parametrization_parameters.m
Data: /Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc, /Data/HoloGondel/droplets_ge_40e-6.mat, /Data/HoloGondel/ice_habits.mat
Run on MATLAB
V_source = '.../Data/HoloGondel/RACLETS_merged_8-10h_rescaled_habits.nc';
droplets_path = .../Data/HoloGondel/droplets_ge_40e-6';
ice_crystals_path = '.../Data/HoloGondel/ice_habits';
plot_parametrization_parameters(droplets_path, ice_crystals_path,V_source)