def test_bird_hulstrom80_aod_bb():
"""Test Bird_Hulstrom broadband AOD."""
aod380, aod500 = 0.22072480948195175, 0.1614279181106312
bird_hulstrom = atmosphere.bird_hulstrom80_aod_bb(aod380, aod500)
assert np.isclose(0.11738229553812768, bird_hulstrom)
def bird(zenith, airmass_relative, aod380, aod500, precipitable_water,
ozone=0.3, pressure=101325., dni_extra=1364., asymmetry=0.85,
albedo=0.2):
"""
Bird Simple Clear Sky Broadband Solar Radiation Model
Based on NREL Excel implementation by Daryl R. Myers [1, 2].
Bird and Hulstrom define the zenith as the "angle between a line to
the sun and the local zenith". There is no distinction in the paper
between solar zenith and apparent (or refracted) zenith, but the
relative airmass is defined using the Kasten 1966 expression, which
requires apparent zenith. Although the formulation for calculated
zenith is never explicitly defined in the report, since the purpose
was to compare existing clear sky models with "rigorous radiative
transfer models" (RTM) it is possible that apparent zenith was
obtained as output from the RTM. However, the implentation presented
in PVLIB is tested against the NREL Excel implementation by Daryl
Myers which uses an analytical expression for solar zenith instead
of apparent zenith.
Parameters
----------
zenith : numeric
Solar or apparent zenith angle in degrees - see note above
airmass_relative : numeric
Relative airmass
aod380 : numeric
Aerosol optical depth [cm] measured at 380[nm]
aod500 : numeric
Aerosol optical depth [cm] measured at 500[nm]
precipitable_water : numeric
Precipitable water [cm]
ozone : numeric
Atmospheric ozone [cm], defaults to 0.3[cm]
pressure : numeric
Ambient pressure [Pa], defaults to 101325[Pa]
dni_extra : numeric
Extraterrestrial radiation [W/m^2], defaults to 1364[W/m^2]
asymmetry : numeric
Asymmetry factor, defaults to 0.85
albedo : numeric
Albedo, defaults to 0.2
Returns
-------
clearsky : DataFrame (if Series input) or OrderedDict of arrays
DataFrame/OrderedDict contains the columns/keys
``'dhi', 'dni', 'ghi', 'direct_horizontal'`` in [W/m^2].
See also
--------
pvlib.atmosphere.bird_hulstrom80_aod_bb
pvlib.atmosphere.relativeairmass
References
----------
[1] R. E. Bird and R. L Hulstrom, "A Simplified Clear Sky model for Direct
and Diffuse Insolation on Horizontal Surfaces" SERI Technical Report
SERI/TR-642-761, Feb 1981. Solar Energy Research Institute, Golden, CO.
[2] Daryl R. Myers, "Solar Radiation: Practical Modeling for Renewable
Energy Applications", pp. 46-51 CRC Press (2013)
`NREL Bird Clear Sky Model <http://rredc.nrel.gov/solar/models/clearsky/>`_
`SERI/TR-642-761 <http://rredc.nrel.gov/solar/pubs/pdfs/tr-642-761.pdf>`_
`Error Reports <http://rredc.nrel.gov/solar/models/clearsky/error_reports.html>`_
"""
etr = dni_extra # extraradiation
ze_rad = np.deg2rad(zenith) # zenith in radians
airmass = airmass_relative
# Bird clear sky model
am_press = atmosphere.get_absolute_airmass(airmass, pressure)
t_rayleigh = (
np.exp(-0.0903 * am_press ** 0.84 * (
1.0 + am_press - am_press ** 1.01
))
)
am_o3 = ozone*airmass
t_ozone = (
1.0 - 0.1611 * am_o3 * (1.0 + 139.48 * am_o3) ** -0.3034 -
0.002715 * am_o3 / (1.0 + 0.044 * am_o3 + 0.0003 * am_o3 ** 2.0)
)
t_gases = np.exp(-0.0127 * am_press ** 0.26)
am_h2o = airmass * precipitable_water
t_water = (
1.0 - 2.4959 * am_h2o / (
(1.0 + 79.034 * am_h2o) ** 0.6828 + 6.385 * am_h2o
)
)
bird_huldstrom = atmosphere.bird_hulstrom80_aod_bb(aod380, aod500)
t_aerosol = np.exp(
-(bird_huldstrom ** 0.873) *
(1.0 + bird_huldstrom - bird_huldstrom ** 0.7088) * airmass ** 0.9108
)
taa = 1.0 - 0.1 * (1.0 - airmass + airmass ** 1.06) * (1.0 - t_aerosol)
rs = 0.0685 + (1.0 - asymmetry) * (1.0 - t_aerosol / taa)
id_ = 0.9662 * etr * t_aerosol * t_water * t_gases * t_ozone * t_rayleigh
ze_cos = np.where(zenith < 90, np.cos(ze_rad), 0.0)
id_nh = id_ * ze_cos
ias = (
etr * ze_cos * 0.79 * t_ozone * t_gases * t_water * taa *
(0.5 * (1.0 - t_rayleigh) + asymmetry * (1.0 - (t_aerosol / taa))) / (
1.0 - airmass + airmass ** 1.02
)
)
gh = (id_nh + ias) / (1.0 - albedo * rs)
diffuse_horiz = gh - id_nh
# TODO: be DRY, use decorator to wrap methods that need to return either
# OrderedDict or DataFrame instead of repeating this boilerplate code
irrads = OrderedDict()
irrads['direct_horizontal'] = id_nh
irrads['ghi'] = gh
irrads['dni'] = id_
irrads['dhi'] = diffuse_horiz
if isinstance(irrads['dni'], pd.Series):
irrads = pd.DataFrame.from_dict(irrads)
return irrads
def test_bird_hulstrom80_aod_bb():
"""Test Bird_Hulstrom broadband AOD."""
aod380, aod500 = 0.22072480948195175, 0.1614279181106312
bird_hulstrom = atmosphere.bird_hulstrom80_aod_bb(aod380, aod500)
assert np.isclose(0.11738229553812768, bird_hulstrom)
