ex_daily_parameters.rst

Example 1: Daily Ionospheric Parameters

PyIRTAM can calculate daily ionospheric parameters for the user provided IRTAM coefficients and grid. The estimation of the parameters occurs simultaneously at all grid points and for all desired diurnal time frames.

1. Import libraries:

import numpy as np
import PyIRI.main_library as ml
import PyIRI.plotting as plot
import PyIRTAM

2. Specify a directory on your machine where IRTAM coefficients live. Example:

irtam_dir = '~/Documents/Science_VF2/PyIRTAM/IRTAM/'

3. Specify a directory on your machine where to save plots. Example:

save_plot_dir = '~/Documents/'

4. Specify a year, a month, and a day:

year = 2022
month = 1
day = 1

5. Specify solar flux index F10.7 in SFU:

f107 = 90.8

6. Create any horizontal grid (regular or irregular, global or regional). The grid arrays (alon and alat) should be flattened to be 1-D arrays. This is an example of a regular global grid:

dlon = 5
dlat = 5
# Create 5x5 horizontal grid:
alon, alat, alon_2d, alat_2d = ml.set_geo_grid(dlon, dlat)

7. Create any temporal array expressed in decimal hours (regular or irregular). IRTAM coefficients have 15-min resolution. For max resolution use 15 min. For this example we use regularly spaced time array:

hr_res = 0.25
ahr = np.arange(0, 24, hr_res)

8. Create height array. It can be regular or irregular. Here is an example for regularly spaced array:

alt_res = 10
alt_min = 90
alt_max = 700
aalt = np.arange(alt_min, alt_max, alt_res)

9. Run PyIRTAM:

(f2_iri, f1_iri, e_iri, es_iri, sun, mag, edp_iri, f2_irtam, f1_irtam,
 e_irtam, es_irtam, edp_irtam) = PyIRTAM.run_PyIRTAM(year, month, day, ahr,
                                                     alon, alat, aalt, f107,
                                                     irtam_dir=irtam_dir,
                                                     use_subdirs=True,
                                                     download=False)

10. Plot results and save at given location, suggestion provided:

UT_show = 10
print('Plot of PyIRI NmF2:')
plot.PyIRI_plot_NmF2(f2_iri, ahr, alon, alat, alon_2d, alat_2d, sun,
                     UT_show, save_plot_dir, plot_name='PyIRI_NmF2.pdf')
print('Plot of PyIRTAM NmF2:')
plot.PyIRI_plot_NmF2(f2_irtam, ahr, alon, alat, alon_2d, alat_2d, sun,
                     UT_show, save_plot_dir, plot_name='PyIRTAM_NmF2.pdf')

11. Plot density time series for PyIRI and PyIRTAM at specified location:

lon_plot = 0
lat_plot = 0

plot.PyIRI_plot_1location_diurnal_density(edp_iri, alon, alat, lon_plot,
                                          lat_plot, aalt, ahr, save_plot_dir,
                                          plot_name='PyIRI_EDP_diurnal.pdf')

plot.PyIRI_plot_1location_diurnal_density(edp_irtam, alon, alat, lon_plot,
                                          lat_plot, aalt, ahr, save_plot_dir,
                                          plot_name='PyIRTAM_EDP_diurnal.pdf')