def exec(self):
log.info('[START] {}'.format("exec"))
try:
if (platform.system() == 'Windows'):
# 옵션 설정
sysOpt = {
# 시작/종료 시간
'srtDate': '2020-09-01',
'endDate': '2020-09-03'
# 경도 최소/최대/간격
,
'lonMin': 0,
'lonMax': 360,
'lonInv': 0.5
# 위도 최소/최대/간격
,
'latMin': -90,
'latMax': 90,
'latInv': 0.5
}
else:
# 옵션 설정
sysOpt = {
# 시작/종료 시간
# 'srtDate': globalVar['srtDate']
# , 'endDate': globalVar['endDate']
}
# globalVar['outPath'] = 'F:/Global Temp/aski'
modelList = ['MRI-ESM2-0']
for i, modelInfo in enumerate(modelList):
log.info("[CHECK] modelInfo : {}".format(modelInfo))
inpFile = '{}/{}/{} ssp585 2015-2100_*.nc'.format(
globalVar['inpPath'], serviceName, modelInfo)
fileList = sorted(glob.glob(inpFile))
log.info("[CHECK] fileList : {}".format(fileList))
dsData = xr.open_mfdataset(fileList)
dsData = dsData.sel(lon=slice(120, 150),
time=slice('2015-01', '2015-12'))
# dsData = dsData.sel(time = slice('2015-01', '2020-12'))
# 월별 시간 변환
dsData['time'] = pd.to_datetime(pd.to_datetime(
dsData['time'].values).strftime("%Y-%m"),
format='%Y-%m')
# 단위 설정
# 켈빈 to 섭씨
dsData['tasCel'] = dsData['tas'] - 273.15
dsData['tasminCel'] = dsData['tasmin'] - 273.15
dsData['tasmaxCel'] = dsData['tasmax'] - 273.15
dsData['tasminCel'].attrs['units'] = 'degC'
dsData['tasmaxCel'].attrs['units'] = 'degC'
dsData['tasCel'].attrs['units'] = 'degC'
# 단위 환산을 위한 매월 마지막 날 계산
lon1D = dsData['lon'].values
lat1D = dsData['lat'].values
time1D = dsData['time'].values
timeEndMonth = []
timeYear = dsData['time.year'].values
timeMonth = dsData['time.month'].values
for i in range(0, len(timeYear)):
timeEndMonth.append(
calendar.monthrange(timeYear[i], timeMonth[i])[1])
latRad1D = pyeto.deg2rad(dsData['lat'])
dayOfYear1D = dsData['time.dayofyear']
latRad3D = np.tile(
np.transpose(np.tile(latRad1D, (len(lon1D), 1))),
(len(time1D), 1, 1))
dayOfYear3D = np.transpose(
np.tile(dayOfYear1D, (len(lon1D), len(lat1D), 1)))
timeEndMonth3D = np.transpose(
np.tile(timeEndMonth, (len(lon1D), len(lat1D), 1)))
tmpData = xr.Dataset(
{
'timeEndMonth':
(('time', 'lat', 'lon'), (timeEndMonth3D).reshape(
len(time1D), len(lat1D), len(lon1D))),
'latRad': (('time', 'lat', 'lon'), (latRad3D).reshape(
len(time1D), len(lat1D), len(lon1D))),
'dayOfYear':
(('time', 'lat', 'lon'), (dayOfYear3D).reshape(
len(time1D), len(lat1D), len(lon1D)))
},
coords={
'lat': lat1D,
'lon': lon1D,
'time': time1D
})
# ********************************************************************************************
# FAO-56 Penman-Monteith 방법
# ********************************************************************************************
# https://pyeto.readthedocs.io/en/latest/fao56_penman_monteith.html 매뉴얼 참조
# 1 W/m2 = 1 J/m2를 기준으로 MJ/day 변환
dsData['rsdsMJ'] = dsData['rsds'] * 86400 / (10**6)
dsData['tasKel'] = dsData['tas']
dsData['tasminKel'] = dsData['tasmin']
dsData['tasmaxKel'] = dsData['tasmax']
dsData['tasKel'].attrs['units'] = 'degK'
dsData['tasminKel'].attrs['units'] = 'degK'
dsData['tasmaxKel'].attrs['units'] = 'degK'
# 섭씨 to 켈빈
# dsData['tasKel'] = dsData['tas'] + 273.15
# dsData['tasminKel'] = dsData['tasmin'] + 273.15
# dsData['tasmaxKel'] = dsData['tasmax'] + 273.15
dsData['svp'] = svp_from_t(dsData['tasCel'])
dsData['svpMax'] = svp_from_t(dsData['tasmaxCel'])
dsData['svpMin'] = svp_from_t(dsData['tasminCel'])
tmpData['solDec'] = sol_dec(tmpData['dayOfYear'])
tmpData['sha'] = sunset_hour_angle(tmpData['latRad'],
tmpData['solDec'])
tmpData['dayLightHour'] = daylight_hours(tmpData['latRad'])
tmpData['ird'] = inv_rel_dist_earth_sun(tmpData['dayOfYear'])
tmpData['etRad'] = et_rad(tmpData['latRad'], tmpData['solDec'],
tmpData['sha'], tmpData['ird'])
tmpData['csRad'] = pyeto.cs_rad(altitude=1.5,
et_rad=tmpData['etRad'])
dsData['deltaSvp'] = delta_svp(dsData['tasCel'])
# 대기 온도 1.5 m 가정
psy = pyeto.psy_const(atmos_pres=pyeto.atm_pressure(
altitude=15))
dsData['avp'] = pyeto.avp_from_rhmin_rhmax(
dsData['svpMax'], dsData['svpMin'], dsData['hurs'].min(),
dsData['hurs'].max())
niSwRad = pyeto.net_in_sol_rad(dsData['rsdsMJ'], albedo=0.23)
niLwRad = net_out_lw_rad(dsData['tasminKel'],
dsData['tasmaxKel'], dsData['rsdsMJ'],
tmpData['csRad'], dsData['avp'])
dsData['net_rad'] = pyeto.net_rad(ni_sw_rad=niSwRad,
no_lw_rad=niLwRad)
faoRes = pyeto.fao56_penman_monteith(dsData['net_rad'],
dsData['tasKel'],
dsData['sfcWind'],
dsData['svp'],
dsData['avp'],
dsData['deltaSvp'],
psy,
shf=0)
# ********************************************************************************************
# Hargreaves 방법
# ********************************************************************************************
# https://xclim.readthedocs.io/en/stable/indicators_api.html 매뉴얼 참조
harRes = xclim.indices.potential_evapotranspiration(
dsData['tasminCel'],
dsData['tasmaxCel'],
dsData['tasCel'],
dsData['lat'],
method='hargreaves85')
# 1 kg/m2/s = 86400 mm/day를 기준으로 mm/month 변환
harResL1 = harRes * 86400.0 * tmpData['timeEndMonth']
# https://pyeto.readthedocs.io/en/latest/thornthwaite.html 매뉴얼 참조
# harRes = pyeto.hargreaves(dsData['tasminCel'], dsData['tasmaxCel'], dsData['tasCel'], tmpData['etRad'])
# harResL1 = harRes
# ********************************************************************************************
# Thornthwaite 방법
# ********************************************************************************************
# https://xclim.readthedocs.io/en/stable/indicators_api.html 매뉴얼 참조
thwRes = xclim.indices.potential_evapotranspiration(
dsData['tasminCel'],
dsData['tasmaxCel'],
dsData['tasCel'],
dsData['lat'],
method='thornthwaite48')
# 1 kg/m2/s = 86400 mm/day를 기준으로 mm/month 변환
thwResL1 = thwRes * 86400.0 * tmpData['timeEndMonth']
# https://pyeto.readthedocs.io/en/latest/thornthwaite.html 매뉴얼 참조
# thwRes = pyeto.thornthwaite(dsData['tasCel'], tmpData['dayLightHour'])
# thwResL1 = thwResL1
# ********************************************************************************************
# 데이터 병합
# ********************************************************************************************
data = xr.Dataset(
{
'hargreaves':
(('time', 'lat', 'lon'), (harResL1.values).reshape(
len(time1D), len(lat1D), len(lon1D))),
'thornthwaite':
(('time', 'lat', 'lon'), (thwResL1.values).reshape(
len(time1D), len(lat1D), len(lon1D))),
'penman-monteith':
(('time', 'lat', 'lon'), (faoRes.values).reshape(
len(time1D), len(lat1D), len(lon1D)))
},
coords={
'lat': lat1D,
'lon': lon1D,
'time': time1D
})
dataL1 = xr.merge([data, dsData])
# # NetCDF 파일 저장
saveFile = '{}/{}/{}_eto.nc'.format(globalVar['outPath'],
serviceName, modelInfo)
os.makedirs(os.path.dirname(saveFile), exist_ok=True)
dataL1.to_netcdf(saveFile)
log.info('[CHECK] saveFile : {}'.format(saveFile))
except Exception as e:
log.error("Exception : {}".format(e))
raise e
finally:
log.info('[END] {}'.format("exec"))
coastal = True altitude = 147 rh_min = 13 rh_max = 88 ws = 1.3 tmean = pyeto.daily_mean_t(tmin, tmax) atmos_pres = pyeto.atm_pressure(altitude) psy = pyeto.psy_const(atmos_pres) # Humidity svp_tmin = pyeto.svp_from_t(tmin) svp_tmax = pyeto.svp_from_t(tmax) delta_svp = pyeto.delta_svp(tmean) svp = pyeto.mean_svp(tmin, tmax) avp = pyeto.avp_from_rhmin_rhmax(svp_tmin, svp_tmax, rh_min, rh_max) # Radiation sol_dec = pyeto.sol_dec(day_of_year) sha = pyeto.sunset_hour_angle(latitude, sol_dec) ird = pyeto.inv_rel_dist_earth_sun(day_of_year) et_rad = pyeto.et_rad(latitude, sol_dec, sha, ird) cs_rad = pyeto.cs_rad(altitude, et_rad) sol_rad = pyeto.sol_rad_from_t(et_rad, cs_rad, tmin, tmax, coastal) ni_sw_rad = pyeto.net_in_sol_rad(sol_rad) no_lw_rad = pyeto.net_out_lw_rad(pyeto.celsius2kelvin(tmin), pyeto.celsius2kelvin(tmax), sol_rad, cs_rad, avp) net_rad = pyeto.net_rad(ni_sw_rad, no_lw_rad) eto = pyeto.fao56_penman_monteith(net_rad, pyeto.celsius2kelvin(tmean), ws, svp, avp, delta_svp, psy) print eto
coastal = True altitude = 147 rh_min = 13 rh_max = 88 ws = 1.3 tmean = pyeto.daily_mean_t(tmin, tmax) atmos_pres = pyeto.atm_pressure(altitude) psy = pyeto.psy_const(atmos_pres) # Humidity svp_tmin = pyeto.svp_from_t(tmin) svp_tmax = pyeto.svp_from_t(tmax) delta_svp = pyeto.delta_svp(tmean) svp = pyeto.mean_svp(tmin, tmax) avp = pyeto.avp_from_rhmin_rhmax(svp_tmin, svp_tmax, rh_min, rh_max) # Radiation sol_dec = pyeto.sol_dec(day_of_year) sha = pyeto.sunset_hour_angle(latitude, sol_dec) ird = pyeto.inv_rel_dist_earth_sun(day_of_year) et_rad = pyeto.et_rad(latitude, sol_dec, sha, ird) cs_rad = pyeto.cs_rad(altitude, et_rad) sol_rad = pyeto.sol_rad_from_t(et_rad, cs_rad, tmin, tmax, coastal) ni_sw_rad = pyeto.net_in_sol_rad(sol_rad) no_lw_rad = pyeto.net_out_lw_rad(pyeto.celsius2kelvin(tmin), pyeto.celsius2kelvin(tmax), sol_rad, cs_rad, avp) net_rad = pyeto.net_rad(ni_sw_rad, no_lw_rad) eto = pyeto.fao56_penman_monteith(net_rad, pyeto.celsius2kelvin(tmean), ws, svp, avp, delta_svp, psy) print eto
def test_avp_from_rhmin_rhmax(self):
# Test based on example 5, p.72 of FAO paper
avp = pyeto.avp_from_rhmin_rhmax(2.064, 3.168, 54, 82)
self.assertAlmostEqual(avp, 1.70, 2)
def test_avp_from_rhmin_rhmax(self):
# Test based on example 5, p.72 of FAO paper
avp = pyeto.avp_from_rhmin_rhmax(2.064, 3.168, 54, 82)
self.assertAlmostEqual(avp, 1.70, 2)
