def getPressureLevels(self):
total_ele37 = [
100, 125, 150, 175, 200, 225, 250, 300, 350, 400, 450, 500, 550,
600, 650, 700, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975,
1000
]
# flip max and min because 1000 is the bottom and 0 is the top
elevationMax = pressure_from_elevation(self.elevation['min'])
elevationMin = pressure_from_elevation(self.elevation['max'])
minNum = min(total_ele37, key=lambda x: abs(x - elevationMin))
maxNum = min(total_ele37, key=lambda x: abs(x - elevationMax))
if (minNum > elevationMin and total_ele37.index(minNum) > 0):
elevationMinRange = total_ele37.index(minNum) - 1
else:
elevationMinRange = total_ele37.index(minNum)
if (maxNum < elevationMin and total_ele37.index(maxNum) < 36):
elevationMaxRange = total_ele37.index(maxNum) - 1
else:
elevationMaxRange = total_ele37.index(maxNum)
elevation = []
for e in range(elevationMinRange, elevationMaxRange + 1):
elevation.append(total_ele37[e])
elevation = [str(ele) for ele in elevation]
elevation = '/'.join(elevation)
return elevation
def getPressureLevels(self, elevation):
"""Restrict list of ERA5 pressure levels to be downloaded"""
Pmax = pressure_from_elevation(elevation['min']) + 55
Pmin = pressure_from_elevation(elevation['max']) - 55
levs = np.array([
300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775, 800, 825,
850, 875, 900, 925, 950, 975, 1000
])
mask = (levs >= Pmin) * (levs <= Pmax) # select
levs = [str(levi) for levi in levs[mask]]
return levs
def era5_pressure_levels(elev_min: float, elev_max: float) -> "list[str]":
"""Restrict list of ERA5 pressure levels to be downloaded"""
Pmax = pressure_from_elevation(
elev_min) + 55 # Pressure inversely correlated
Pmin = pressure_from_elevation(elev_max) - 55
levs = np.array([
300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775, 800, 825, 850,
875, 900, 925, 950, 975, 1000
])
mask = (levs >= Pmin) * (levs <= Pmax) # select
levs = [str(levi) for levi in levs[mask]]
return levs
def elevation_corrected_sw(zenith, grid_sw, lat, lon, time, grid_elevation,
sub_elevation) -> "tuple":
grid_pressure = pressure_from_elevation(grid_elevation)
sub_pressure = pressure_from_elevation(sub_elevation)
# atmospheric properties
if zenith is None:
zenith = solar_zenith(lat=lat, lon=lon, time=time)
else:
zenith = np.atleast_1d(zenith)
toa = sw_toa(zenith=zenith)
if (toa < grid_sw).any():
warnings.warn(
"Calculated top-of-atmosphere radiation is less than grid-level radiation "
f"(max difference = {(toa-grid_sw).min()} W m2). This could be because "
"grid-level radiation is the average of an accumulation over an interval but TOA is calculated instantaneously "
"at either the beginning or end of the interval.")
""" try averaging out the TOA """
toa[toa < grid_sw] = grid_sw[
toa < grid_sw] # a workaround: just bump up the TOA a bit
mr = relative_optical_airmass(zenith_angle=zenith)
# grid
grid_local_airmass = local_condition_airmass(mr=mr, p=grid_pressure)
# kt = clearness_index(grid_sw, toa)
diffuse, direct = sw_partition(grid_sw, toa)
k = broadband_attenuation(sw_d=grid_sw * direct,
toa=toa,
m=grid_local_airmass)
# subgrid site
sub_local_airmass = local_condition_airmass(mr=mr, p=sub_pressure)
sw_dir_sub = np.where(toa == 0, 0, beer_lambert(toa, k, sub_local_airmass))
# print(f"grid p {grid_pressure} \nsub_pressure {sub_pressure}\nzenith {zenith}\ntoa {toa}\nmr {mr}\nk {k}\ngrid_local = {grid_local_airmass}\nsub local {sub_local_airmass}")
diffuse = grid_sw * diffuse
return diffuse, sw_dir_sub
def subset_lev(self, elev_min, elev_max):
Pmax = pressure_from_elevation(elev_min) + 55
Pmin = pressure_from_elevation(elev_max) - 55
indices = np.where((self.LEVS >= Pmin) & (self.LEVS <= Pmax))
return "[{}:{}]".format(np.min(indices), np.max(indices))
def test_array(self):
self.assertEqual(
4, len(met.pressure_from_elevation(np.array([10, 150, 300,
1000]))))
def test_zero(self):
self.assertAlmostEqual(met.pressure_from_elevation(0), 1013.25)