DMSP SSJ Boundaries¶
For more information about these boundaries, see Section DMSP SSJ.
Loading DMSP SSJ Boundaries¶
Unlike the IMAGE and AMPERE boundaries, the DMSP SSJ boundaries are not included
with the package. However, routines to obtain them are. To use them, you need
to install the
ssj_auroral_boundary
package. Once installed, you can download DMSP SSJ data and obtain a boundary
file for a specified time period using
ocbpy.boundaries.dmsp_ssj_files
. For this example, we’ll use a
single day. You can download the files into any directory, but this example will
put them in the same directory as the other OCB files.
import datetime as dt
import matplotlib.pyplot as plt
import ocbpy
import os
stime = dt.datetime(2010, 12, 31)
etime = stime + dt.timedelta(days=1)
out_dir = os.path.join(os.path.split(ocbpy.__file__)[0], "boundaries")
bfiles = ocbpy.boundaries.dmsp_ssj_files.fetch_format_ssj_boundary_files(
stime, etime, out_dir=out_dir, rm_temp=False)
By setting rm_temp=False
, all of the different DMSP files will be kept in
the specified output directory. You should have three CDF files (the data
downloaded from each DMSP spacecraft), the CSV files (the boundaries calculated
for each DMSP spacecraft) and four boundary files. The boundary files have
an extention of .eab
for the Equatorial Auroral Boundary and .ocb
for
the Open-Closed field line Boundary. The files are separated by hemisphere, and
also specify the date range. Because only one day was obtained, the start and
end dates in the filename are identical. When rm_temp=True
, the CDF and CSV
files are removed.
You can now load the DMSP SSJ boundaries by specifying the desired filename, instrument, and hemisphere or merely the instrument and hemisphere.
# Load with filename, instrument, and hemisphere
south_file = os.path.join(out_dir,
"dmsp-ssj_south_20101231_20101231_v1.1.2.ocb")
ocb_south = ocbpy.OCBoundary(filename=south_file, instrument='dmsp-ssj',
hemisphere=-1)
print(ocb_south)
OCBoundary file: ~/ocbpy/ocbpy/boundaries/dmsp-ssj_south_20101231_20101231_v1.1.2.ocb
Source instrument: DMSP-SSJ
Boundary reference latitude: -74.0 degrees
21 records from 2010-12-31 00:27:23 to 2010-12-31 22:11:38
YYYY-MM-DD HH:MM:SS Phi_Centre R_Centre R
-----------------------------------------------------------------------------
2010-12-31 00:27:23 356.72 14.02 12.13
2010-12-31 12:27:56 324.82 0.86 14.73
2010-12-31 18:49:58 233.68 6.12 14.10
2010-12-31 22:11:38 318.60 4.64 12.34
Uses scaling function(s):
ocbpy.ocb_correction.circular(**{})
# Load with date, instrument, and hemisphere
ocb_north = ocbpy.OCBoundary(stime=stime, instrument='dmsp-ssj',
hemisphere=1)
print(ocb_north)
OCBoundary file: ~/ocbpy/ocbpy/boundaries/dmsp-ssj_north_20101231_20101231_v1.1.2.ocb
Source instrument: DMSP-SSJ
Boundary reference latitude: 74.0 degrees
27 records from 2010-12-31 01:19:13 to 2010-12-31 23:02:48
YYYY-MM-DD HH:MM:SS Phi_Centre R_Centre R
-----------------------------------------------------------------------------
2010-12-31 01:19:13 191.07 10.69 8.59
2010-12-31 06:27:18 195.29 13.52 6.77
2010-12-31 21:21:32 259.27 2.73 10.45
2010-12-31 23:02:48 234.73 3.94 10.79
Uses scaling function(s):
ocbpy.ocb_correction.circular(**{})
The circular scaling function with no input adds zero the the boundaries, and so performs no scaling.
Using DMSP SSJ Boundaries¶
Because DMSP SSJ Boundaries are only measured along a satellite track, you
cannot use these boundaries to convert between magnetic and OCB or Dual-boundary
coordinates at just any location or local time. To address this issue, the
ocbpy.cycle_boundary.satellite_track()
function can be used to
determine whether or not a location is close enough to the satellite track.
This example shows the width along the linear approximation of the satellite
track allowed along the Boundary latitude. The axis formatting is performed
using the set_up_polar_plot function defined in the
Coordinate Convertion example.
# Set up the figure
fig = plt.figure()
ax = fig.add_subplot(111, projection="polar"
set_up_polar_plot(ax, hemi=ocb_south.hemisphere)
# Get the OCB location in AACGM coordinates
mlt = np.linspace(0, 24, 64)
ocb_south.get_aacgm_boundary_lat(mlt)
# Plot the OCB location
ax.plot(mlt * np.pi / 12.0,
90 + ocb_south.aacgm_boundary_lat[ocb_south.rec_ind], "m-", lw=2,
label="OCB")
# Deterimine which OCB locations are along the satellite track
igood = ocbpy.cycle_boundary.satellite_track(
ocb_south.aacgm_boundary_lat[ocb_south.rec_ind],
ocb_south.aacgm_boundary_mlt[ocb_south.rec_ind],
ocb_south.x_1[ocb_south.rec_ind], ocb_south.y_1[ocb_south.rec_ind],
ocb_south.x_2[ocb_south.rec_ind], ocb_south.y_2[ocb_south.rec_ind],
hemisphere=ocb_south.hemisphere)
ax.plot(mlt[igood] * np.pi / 12.0,
90 + ocb_south.aacgm_boundary_lat[ocb_south.rec_ind][igood], "ks",
label="Measured OCB")
The default constraints for ocbpy.cycle_boundary.satellite_track()
allow a 1 degree deviation in either Cartesian direction and a maximum distance
of 5 degrees equatorward of the Boundary.
lat = np.arange(-90, -60, 1)
grid_mlt, grid_lat = np.meshgrid(mlt, lat)
grid_mlt = grid_mlt.flatten()
grid_lat = grid_lat.flatten()
igood = ocbpy.cycle_boundary.satellite_track(
grid_lat, grid_mlt, ocb_south.x_1[ocb_south.rec_ind],
ocb_south.y_1[ocb_south.rec_ind], ocb_south.x_2[ocb_south.rec_ind],
ocb_south.y_2[ocb_south.rec_ind], hemisphere=ocb_south.hemisphere)
ax.plot(grid_mlt[~igood] * np.pi / 12.0, 90 + grid_lat[~igood], ".",
color="palegreen", label="Data", zorder=1)
ax.plot(grid_mlt[igood] * np.pi / 12.0, 90 + grid_lat[igood], "g.",
label="Satellite track data")
ax.legend(loc=2, title="{:}".format(ocb_south.dtime[ocb_south.rec_ind]),
bbox_to_anchor=(-0.4, 1.15))
Note that because the OCB is determined based off of only two points, the OCB MLT is not very accurate. With poorly defined OCBs, we recommend using only the gridded latitude along the satellite track.