def estimate_fao56_daily(self, day_of_year, temp_c, temp_c_min, temp_c_max,
tdew, elevation, latitude, rh, wind_m_s,
atmos_pres):
""" Estimate fao56 from weather """
sha = pyeto.sunset_hour_angle(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year))
daylight_hours = pyeto.daylight_hours(sha)
sunshine_hours = 0.8 * daylight_hours
ird = pyeto.inv_rel_dist_earth_sun(day_of_year)
et_rad = pyeto.et_rad(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year), sha, ird)
sol_rad = pyeto.sol_rad_from_sun_hours(daylight_hours, sunshine_hours,
et_rad)
net_in_sol_rad = pyeto.net_in_sol_rad(sol_rad=sol_rad, albedo=0.23)
cs_rad = pyeto.cs_rad(elevation, et_rad)
avp = pyeto.avp_from_tdew(tdew)
net_out_lw_rad = pyeto.net_out_lw_rad(
pyeto.convert.celsius2kelvin(temp_c_min),
pyeto.convert.celsius2kelvin(temp_c_max), sol_rad, cs_rad, avp)
net_rad = pyeto.net_rad(net_in_sol_rad, net_out_lw_rad)
eto = pyeto.fao56_penman_monteith(
net_rad=net_rad,
t=pyeto.convert.celsius2kelvin(temp_c),
ws=wind_m_s,
svp=pyeto.svp_from_t(temp_c),
avp=avp,
delta_svp=pyeto.delta_svp(temp_c),
psy=pyeto.psy_const(atmos_pres))
return eto
def get_evap_i(lat, elev, wind, srad, tmin, tmax, tavg, month):
if month == 1:
J = 15
else:
J = 15 + (month - 1) * 30
latitude = pyeto.deg2rad(lat)
atmosphericVapourPressure = pyeto.avp_from_tmin(tmin)
saturationVapourPressure = pyeto.svp_from_t(tavg)
ird = pyeto.inv_rel_dist_earth_sun(J)
solarDeclination = pyeto.sol_dec(J)
sha = [pyeto.sunset_hour_angle(l, solarDeclination) for l in latitude]
extraterrestrialRad = [
pyeto.et_rad(x, solarDeclination, y, ird)
for x, y in zip(latitude, sha)
]
clearSkyRad = pyeto.cs_rad(elev, extraterrestrialRad)
netInSolRadnet = pyeto.net_in_sol_rad(srad * 0.001, albedo=0.23)
netOutSolRadnet = pyeto.net_out_lw_rad(tmin, tmax, srad * 0.001,
clearSkyRad,
atmosphericVapourPressure)
netRadiation = pyeto.net_rad(netInSolRadnet, netOutSolRadnet)
tempKelvin = pyeto.celsius2kelvin(tavg)
windSpeed2m = pyeto.wind_speed_2m(wind, 10)
slopeSvp = pyeto.delta_svp(tavg)
atmPressure = pyeto.atm_pressure(elev)
psyConstant = pyeto.psy_const(atmPressure)
return pyeto.fao56_penman_monteith(netRadiation,
tempKelvin,
windSpeed2m,
saturationVapourPressure,
atmosphericVapourPressure,
slopeSvp,
psyConstant,
shf=0.0)
et_rad=pyeto.et_rad(lat, sol_dec, sha, ird)
sol_rad=pyeto.sol_rad_from_sun_hours(daylight_hours,sunshine_hours,et_rad)
ni_sw_rad=pyeto.net_in_sol_rad(sol_rad, albedo=0.23)
cs_rad=pyeto.cs_rad(altitude, et_rad)
svp_tmin=pyeto.svp_from_t(tmin)
svp_tmax=pyeto.svp_from_t(tmax)
avp=pyeto.avp_from_rhmean(svp_tmin, svp_tmax, rh_mean)
no_lw_rad=pyeto.net_out_lw_rad(tmink, tmaxk, sol_rad, cs_rad, avp)
net_rad=pyeto.net_rad(ni_sw_rad, no_lw_rad)
#Presion de vapor de saturacion
svp=pyeto.svp_from_t(t)
#Delta presion de vapor de saturacion
delta_svp=pyeto.delta_svp(t)
#Constante psicrométrica
atmos_pres=pyeto.atm_pressure(altitude)
psy=pyeto.psy_const(atmos_pres)
#Calculo ETo Fao Penman Monteith
ETo=pyeto.fao56_penman_monteith(net_rad, tk, ws, svp, avp, delta_svp, psy, shf=0.0)
ETO.append(ETo)
if day>=365:
if Ano%4==0:
Ano=Ano+1
else:
day=1
if Ano%4!=1:
Ano=Ano+1
ETO=pd.DataFrame.from_dict(ETO)
pd.DataFrame.to_csv(ETO, esta[i]+"_ETo"+".csv", index=False, header=False)
#Escribo todos los datos en el archivo
def get_data_from_WU():
###array to store the reports
wu_weather_reports = []
## today and last 6 days definition
day1 = now - datetime.timedelta(days=6)
day2 = now - datetime.timedelta(days=5)
day3 = now - datetime.timedelta(days=4)
day4 = now - datetime.timedelta(days=3)
day5 = now - datetime.timedelta(days=2)
day6 = now - datetime.timedelta(days=1)
day7 = now
#### convert dates to WU required format
days = {
'day1': day1.strftime('%Y%m%d'),
'day2': day2.strftime('%Y%m%d'),
'day3': day3.strftime('%Y%m%d'),
'day4': day4.strftime('%Y%m%d'),
'day5': day5.strftime('%Y%m%d'),
'day6': day6.strftime('%Y%m%d'),
'day7': day7.strftime('%Y%m%d')
}
### make API wather hisotry call for each day
for day in days:
url = 'http://api.wunderground.com/api/7c2ab99a0ccee978/history_{0}/q/95316.json'.format(
days[day])
headers = {'content-type': 'application/JSON; charset=utf8'}
response = requests.get(url, headers=headers)
data = json.loads(response.text)
#ETo calculation for the day using FAO-56 Penman-Monteith method
lat = pyeto.deg2rad(37.585652)
altitude = 38
julian_day = datetime.datetime.strptime(days.get(day),
'%Y%m%d').timetuple().tm_yday
sol_dec = pyeto.sol_dec(julian_day)
sha = pyeto.sunset_hour_angle(lat, sol_dec)
ird = pyeto.inv_rel_dist_earth_sun(julian_day)
### net radiation calculator
net_rad = pyeto.et_rad(lat, sol_dec, sha, ird)
temp_c = float(data["history"]["observations"][1]["tempm"])
temp_k = float(data["history"]["observations"][1]["tempi"])
humidity = float(data["history"]["observations"][1]["hum"])
dew_point = float(data["history"]["observations"][1]["dewptm"])
ws = float(data["history"]["observations"][1]["wspdm"])
#actual and saturated vapour pressure in kPH
svp = pyeto.svp_from_t(temp_c)
avp = pyeto.avp_from_tdew(dew_point)
delta_svp = pyeto.delta_svp(temp_c)
atm_pressure = pyeto.atm_pressure(altitude)
psy = pyeto.psy_const(atm_pressure)
#### the ETo plugin retun results in mm, it was converted to inched
ETo_in_mm = pyeto.fao56_penman_monteith(net_rad,
temp_k,
ws,
svp,
avp,
delta_svp,
psy,
shf=0.0)
ETo = ETo_in_mm * 0.039370
## insert eto value to day weather report
data["history"]["observations"][1].update(
{"ETo": "{0:.2f}".format(ETo)})
###add report to report collector array
wu_weather_reports.append(data["history"]["observations"][1])
#return all reports
return wu_weather_reports
def calculate_precipitation(self, d):
if "rain" in d:
self.rain_day = float(d["rain"])
if "snow" in d:
self.snow_day = float(d["snow"])
# def calculate_ev_fao56_factor(self, d):
dt = d['dt']
factor = 0.0
if dt > d['sunrise']:
if dt < d['sunset']:
factor = min(float(dt - d['sunrise'])/3600.0, 1.0)
else:
if dt > d['sunset']:
factor = (dt - d['sunrise'])/3600.0
if factor < 1.0:
factor = 1.0 - factor
return factor
#def estimate_fao56_hourly(self, day_of_year, temp_c, tdew, elevation, latitude, rh, wind_m_s, atmos_pres):
""" Estimate fao56 from weather """
sha = pyeto.sunset_hour_angle(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year))
daylight_hours = pyeto.daylight_hours(sha)
sunshine_hours = 0.8 * daylight_hours
ird = pyeto.inv_rel_dist_earth_sun(day_of_year)
et_rad = pyeto.et_rad(pyeto.deg2rad(latitude),
pyeto.sol_dec(day_of_year), sha, ird)
sol_rad = pyeto.sol_rad_from_sun_hours(daylight_hours, sunshine_hours,
et_rad)
net_in_sol_rad = pyeto.net_in_sol_rad(sol_rad=sol_rad, albedo=0.23)
cs_rad = pyeto.cs_rad(elevation, et_rad)
avp = pyeto.avp_from_tdew(tdew)
#not sure if I trust this net_out_lw_rad calculation here!
net_out_lw_rad = pyeto.net_out_lw_rad(temp_c-1, temp_c, sol_rad,
cs_rad, avp)
net_rad = pyeto.net_rad(net_in_sol_rad, net_out_lw_rad)
eto = pyeto.fao56_penman_monteith(
net_rad=net_rad,
t=pyeto.convert.celsius2kelvin(temp_c),
ws=wind_m_s,
svp=pyeto.svp_from_t(temp_c),
avp=avp,
delta_svp=pyeto.delta_svp(temp_c),
psy=pyeto.psy_const(atmos_pres))
return eto
#def calculate_fao56_hourly(self, d):
day_of_year = datetime.datetime.now().timetuple().tm_yday
T_hr = d['temp']
t_dew = float(d["dew_point"])
pressure = d['pressure']
RH_hr = d['humidity']
u_2 = d['wind_speed']
#print("CALCULATE_FAO56:")
#print("T_hr: {}".format(T_hr))
#print("t_dew: {}".format(t_dew))
#print("RH_hr: {}".format(RH_hr))
#print("u_2: {}".format(u_2))
#print("pressure: {}".format(pressure))
fao56 = self.estimate_fao56_hourly(day_of_year,
T_hr,
t_dew,
self.elevation,
LAT,
RH_hr,
u_2,
pressure)
return fao56
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"))
# this data should be from nws. import pyeto latitude_deg = 38.01 latitude = pyeto.deg2rad(latitude_deg) day_of_year = 206 tmin = 37 tmax = 53 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)
def get_data_from_WU():
###array to store the reports
wu_weather_reports = []
## today and last 6 days definition
day1 = now - datetime.timedelta(days=6)
day2 = now - datetime.timedelta(days=5)
day3 = now - datetime.timedelta(days=4)
day4 = now - datetime.timedelta(days=3)
day5 = now - datetime.timedelta(days=2)
day6 = now - datetime.timedelta(days=1)
day7 = now
#### convert dates to WU required format
days = {
'day1': day1.strftime('%Y%m%d'),
'day2': day2.strftime('%Y%m%d'),
'day3': day3.strftime('%Y%m%d'),
'day4': day4.strftime('%Y%m%d'),
'day5': day5.strftime('%Y%m%d'),
'day6': day6.strftime('%Y%m%d'),
'day7': day7.strftime('%Y%m%d')
}
### make API wather hisotry call for each day
for day in days:
url = 'http://api.wunderground.com/api/7c2ab99a0ccee978/history_{0}/q/95316.json'.format(days[day])
headers = {'content-type': 'application/JSON; charset=utf8'}
response = requests.get(url, headers=headers)
data = json.loads(response.text)
#ETo calculation for the day using FAO-56 Penman-Monteith method
lat = pyeto.deg2rad(37.585652)
altitude = 38
julian_day = datetime.datetime.strptime(days.get(day), '%Y%m%d').timetuple().tm_yday
sol_dec = pyeto.sol_dec(julian_day)
sha = pyeto.sunset_hour_angle(lat, sol_dec)
ird = pyeto.inv_rel_dist_earth_sun(julian_day)
### net radiation calculator
net_rad = pyeto.et_rad(lat, sol_dec, sha, ird)
temp_c = float(data["history"]["observations"][1]["tempm"])
temp_k = float(data["history"]["observations"][1]["tempi"])
humidity = float(data["history"]["observations"][1]["hum"])
dew_point = float(data["history"]["observations"][1]["dewptm"])
ws = float(data["history"]["observations"][1]["wspdm"])
#actual and saturated vapour pressure in kPH
svp = pyeto.svp_from_t(temp_c)
avp = pyeto.avp_from_tdew(dew_point)
delta_svp = pyeto.delta_svp(temp_c)
atm_pressure = pyeto.atm_pressure(altitude)
psy = pyeto.psy_const(atm_pressure)
#### the ETo plugin retun results in mm, it was converted to inched
ETo_in_mm = pyeto.fao56_penman_monteith(net_rad, temp_k, ws, svp, avp, delta_svp, psy, shf=0.0)
ETo = ETo_in_mm * 0.039370
## insert eto value to day weather report
data["history"]["observations"][1].update({"ETo": "{0:.2f}".format(ETo)})
###add report to report collector array
wu_weather_reports.append(data["history"]["observations"][1])
#return all reports
return wu_weather_reports
def test_psy_const(self):
# Test based on example 2, p.63 of FAO paper
psy = pyeto.psy_const(81.8)
self.assertAlmostEqual(psy, 0.054, 3)
def test_psy_const(self):
# Test based on example 2, p.63 of FAO paper
psy = pyeto.psy_const(81.8)
self.assertAlmostEqual(psy, 0.054, 3)