def test_elevation_effect(self):
self.assertGreater(
top.elevation_corrected_sw(zenith=45,
grid_sw=500,
lat=50,
lon=-110,
time=datetime.datetime(
year=2020,
month=5,
day=10,
hour=18,
tzinfo=datetime.timezone.utc),
grid_elevation=100,
sub_elevation=2000)[1],
top.elevation_corrected_sw(zenith=45,
grid_sw=500,
lat=50,
lon=-110,
time=datetime.datetime(
year=2020,
month=5,
day=10,
hour=18,
tzinfo=datetime.timezone.utc),
grid_elevation=100,
sub_elevation=1000)[1])
def test_array(self):
self.assertEqual(
3,
len(
top.elevation_corrected_sw(zenith=self.zenith,
grid_sw=self.sw,
lat=self.lat,
lon=self.lon,
time=self.time,
grid_elevation=self.ge,
sub_elevation=self.se)[0]))
def SW_Wm2_topo(self, ni=10):
"""
Short-wave downwelling radiation corrected using a modified version of TOPOscale.
Partitions into direct and diffuse
"""
# add variable to ncdf file
vn_diff = 'SW_topo_diffuse' # variable name
var = self.rg.createVariable(vn_diff, 'f4', ('time', 'station'))
var.long_name = 'TOPOscale-corrected diffuse solar radiation'
var.units = 'W m-2'
var.standard_name = 'surface_diffuse_downwelling_shortwave_flux_in_air'
vn_dir = 'SW_topo_direct' # variable name
var = self.rg.createVariable(vn_dir, 'f4', ('time', 'station'))
var.long_name = 'TOPOscale-corrected direct solar radiation'
var.units = 'W m-2'
var.standard_name = 'surface_direct_downwelling_shortwave_flux_in_air'
# interpolate station by station
nc_time = self.nc_sf.variables['time']
py_time = nc.num2date(nc_time[:],
nc_time.units,
nc_time.calendar,
only_use_cftime_datetimes=False)
py_time = np.array([pytz.utc.localize(t) for t in py_time])
lat = self.getValues(self.nc_pl, 'latitude', ni)
lon = self.getValues(self.nc_pl, 'longitude', ni)
sw = self.getValues(self.nc_sf, 'ssrd',
ni) / self.interval_in # [J m-2] --> [W m-2]
grid_elev = self.getValues(
self.nc_to, 'z',
ni)[0, :] / 9.80665 # z has 2 dimensions from the scaling step
station_elev = self.getValues(self.nc_pl, 'height', ni)
svf = self.get_sky_view()
slope = self.get_slope()
aspect = self.get_aspect()
interpolation_time = nc_time[:].astype(np.int64)
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
zenith = solar_zenith(lat=lat[n], lon=lon[n], time=py_time)
diffuse, corrected_direct = elevation_corrected_sw(
zenith=zenith,
grid_sw=sw[:, n],
lat=np.ones_like(sw[:, n]) * lat[n],
lon=np.ones_like(sw[:, n]) * lon[n],
time=py_time,
grid_elevation=np.ones_like(sw[:, n]) * grid_elev[n],
sub_elevation=np.ones_like(sw[:, n]) * station_elev[n])
diffuse = diffuse * svf[n] # apply sky-view factor
if not np.all(slope == 0):
azimuth = get_azimuth_fast(lat[n], lon[n], py_time)
cos_i_sub = illumination_angle(zenith, azimuth, slope[n],
aspect[n])
cos_i_grid = np.cos(np.radians(zenith))
corrected_direct = shading_corrected_sw_direct(
corrected_direct, cos_i_sub, cos_i_grid)
sensible_values_mask = np.where(
cos_i_grid < 0.001, 0, 1) * np.where(
corrected_direct > 1366, 0, 1)
corrected_direct *= sensible_values_mask
f = interp1d(interpolation_time * 3600,
corrected_direct,
kind='linear')
self.rg.variables[vn_dir][:, n] = f(self.times_out_nc)
f = interp1d(interpolation_time * 3600, diffuse, kind='linear')
self.rg.variables[vn_diff][:, n] = f(self.times_out_nc)