def point_fcst(
model='ECMWF',
output_dir=None,
t_range=[0,60],
t_gap=3,
points={'lon':[116.3833], 'lat':[39.9], 'altitude':[1351]},
initTime=None,day_back=0,
extra_info={
'output_head_name':' ',
'output_tail_name':' ',
'point_name':' '}
):
#+get all the directories needed
try:
dir_rqd=[utl.Cassandra_dir(data_type='surface',data_source=model,var_name='T2m'),
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='u10m'),
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='v10m'),
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='RAIN'+str(t_gap).zfill(2))]
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if(initTime == None):
initTime = get_latest_initTime(dir_rqd[0])
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
directory=dir_rqd[0][0:-1]
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [initTime+'.'+str(fhour).zfill(3) for fhour in fhours]
t2m=utl.get_model_points_gy(dir_rqd[0], filenames, points,allExists=False)
u10m=utl.get_model_points_gy(dir_rqd[1], filenames, points,allExists=False)
v10m=utl.get_model_points_gy(dir_rqd[2], filenames, points,allExists=False)
rn=utl.get_model_points_gy(dir_rqd[3], filenames, points,allExists=False)
sta_graphics.draw_point_fcst(t2m=t2m,u10m=u10m,v10m=v10m,rn=rn,
model=model,
output_dir=output_dir,
points=points,
extra_info=extra_info
)
def point_fcst_rn_according_to_3D_field_box_line(output_dir=None,
t_range=[6, 60],
t_gap=6,
points={
'lon': [116.3833],
'lat': [39.9]
},
initTime=None,
obs_ID=54511,
extra_info={
'output_head_name': ' ',
'output_tail_name': ' ',
'point_name': ' ',
'drw_thr': True
},
**kwargs):
try:
dir_rqd = utl.Cassandra_dir(data_type='surface',
data_source='ECMWF_ENSEMBLE',
var_name='RAIN' + str(t_gap).zfill(2) +
'_RAW')
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if (initTime == None):
initTime = get_latest_initTime(dir_rqd)
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
if (t_range[1] > 72):
fhours = np.append(np.arange(t_range[0], 72, t_gap),
np.arange(72, t_range[1], 6))
else:
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [initTime + '.' + str(fhour).zfill(3) for fhour in fhours]
rn = utl.get_model_points_gy(dir_rqd, filenames, points, allExists=False)
rn.attrs['model'] = 'ECMWF_ENSEMBLE'
Ensemble_graphics.box_line_rn(rn=rn,
points=points,
extra_info=extra_info,
output_dir=output_dir)
def point_fcst_according_to_3D_field(
model='ECMWF',
output_dir=None,
t_range=[0,60],
t_gap=3,
points={'lon':[116.3833], 'lat':[39.9], 'altitude':[1351]},
initTime=None,obs_ID=54511,day_back=0,
extra_info={
'output_head_name':' ',
'output_tail_name':' ',
'point_name':' ',
'drw_thr':True,
'levels_for_interp':[1000, 950, 925, 900, 850, 800, 700, 600, 500]}
):
try:
dir_rqd=[utl.Cassandra_dir(data_type='high',data_source=model,var_name='HGT',lvl=''),
utl.Cassandra_dir(data_type='high',data_source=model,var_name='UGRD',lvl=''),
utl.Cassandra_dir(data_type='high',data_source=model,var_name='VGRD',lvl=''),
utl.Cassandra_dir(data_type='high',data_source=model,var_name='TMP',lvl=''),
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='RAIN'+str(t_gap).zfill(2))]
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if(initTime == None):
initTime = get_latest_initTime(dir_rqd[0][0:-1]+'/850')
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
directory=dir_rqd[0][0:-1]
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [initTime+'.'+str(fhour).zfill(3) for fhour in fhours]
HGT_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
directory=dir_rqd[1][0:-1]
U_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
directory=dir_rqd[2][0:-1]
V_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
directory=dir_rqd[3][0:-1]
TMP_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
rn=utl.get_model_points_gy(dir_rqd[4], filenames, points,allExists=False)
directory=dir_rqd[3][0:-1]
coords_info_2D=utl.get_model_points_gy(directory+str(extra_info['levels_for_interp'][0])+'/',
points=points,filenames=filenames,allExists=False)
delt_xy=HGT_4D['lon'].values[1]-HGT_4D['lon'].values[0]
mask = (HGT_4D['lon']<(points['lon']+2*delt_xy))&(HGT_4D['lon']>(points['lon']-2*delt_xy))&(HGT_4D['lat']<(points['lat']+2*delt_xy))&(HGT_4D['lat']>(points['lat']-2*delt_xy))
HGT_4D_sm=HGT_4D['data'].where(mask,drop=True)
U_4D_sm=U_4D['data'].where(mask,drop=True)
V_4D_sm=V_4D['data'].where(mask,drop=True)
TMP_4D_sm=U_4D['data'].where(mask,drop=True)
lon_md=np.squeeze(HGT_4D_sm['lon'].values)
lat_md=np.squeeze(HGT_4D_sm['lat'].values)
alt_md=np.squeeze(HGT_4D_sm.values*10).flatten()
time_md=np.squeeze(HGT_4D_sm['forecast_period'].values)
coords = np.zeros((len(time_md),len(extra_info['levels_for_interp']),len(lat_md),len(lon_md),4))
coords[...,0]=time_md.reshape((len(time_md),1,1,1))
coords[...,2] = lat_md.reshape((1,1,len(lat_md),1))
coords[...,3] = lon_md.reshape((1,1,1,len(lon_md)))
coords = coords.reshape((alt_md.size,4))
coords[:,1]=alt_md
interpolator_U = LinearNDInterpolator(coords,U_4D_sm.values.reshape((U_4D_sm.values.size)),rescale=True)
interpolator_V = LinearNDInterpolator(coords,V_4D_sm.values.reshape((V_4D_sm.values.size)),rescale=True)
interpolator_TMP = LinearNDInterpolator(coords,TMP_4D_sm.values.reshape((TMP_4D_sm.values.size)),rescale=True)
coords2 = np.zeros((len(time_md),1,1,1,4))
coords2[...,0]=time_md.reshape((len(time_md),1,1,1))
coords2[...,1]=points['altitude'][0]
coords2[...,2] = points['lat'][0]
coords2[...,3] = points['lon'][0]
coords2 = coords2.reshape((time_md.size,4))
U_interped=np.squeeze(interpolator_U(coords2))
V_interped=np.squeeze(interpolator_V(coords2))
TMP_interped=np.squeeze(interpolator_TMP(coords2))
U_interped_xr=coords_info_2D.copy()
U_interped_xr['data'].values=U_interped.reshape(U_interped.size,1,1)
V_interped_xr=coords_info_2D.copy()
V_interped_xr['data'].values=V_interped.reshape(V_interped.size,1,1)
TMP_interped_xr=coords_info_2D.copy()
TMP_interped_xr['data'].values=TMP_interped.reshape(TMP_interped.size,1,1)
sta_graphics.draw_point_fcst(t2m=TMP_interped_xr,u10m=U_interped_xr,v10m=V_interped_xr,rn=rn,
model=model,
output_dir=output_dir,
points=points,
extra_info=extra_info
)
def Station_Synthetical_Forecast_From_Cassandra(
model='ECMWF',
output_dir=None,
t_range=[0,84],
t_gap=3,
points={'lon':[116.3833], 'lat':[39.9]},
initTime=None,
draw_VIS=True,drw_thr=False,
extra_info={
'output_head_name':' ',
'output_tail_name':' ',
'point_name':' '}
):
#+get all the directories needed
try:
dir_rqd=[
"ECMWF_HR/10_METRE_WIND_GUST_IN_THE_LAST_3_HOURS/",
"ECMWF_HR/10_METRE_WIND_GUST_IN_THE_LAST_6_HOURS/",
"ECMWF_HR/TCDC/",
"ECMWF_HR/LCDC/",
"ECMWF_HR/UGRD_100M/",
"ECMWF_HR/VGRD_100M/",
"NWFD_SCMOC/VIS/",
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='RAIN03'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='RAIN06'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='T2m'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='u10m'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='v10m'),
]
except KeyError:
raise ValueError('Can not find all required directories needed')
try:
dir_opt=[
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='Td2m')
]
name_opt=['Td2m']
except:
dir_opt=[
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='rh2m')
]
name_opt=['rh2m']
#+get all the directories needed
if(initTime == None):
last_file={model:get_latest_initTime(dir_rqd[0]),
'SCMOC':get_latest_initTime(dir_rqd[6]),
}
else:
last_file={model:initTime[0],
'SCMOC':initTime[1],
}
y_s={model:int('20'+last_file[model][0:2]),
'SCMOC':int('20'+last_file['SCMOC'][0:2])}
m_s={model:int(last_file[model][2:4]),
'SCMOC':int(last_file['SCMOC'][2:4])}
d_s={model:int(last_file[model][4:6]),
'SCMOC':int(last_file['SCMOC'][4:6])}
h_s={model:int(last_file[model][6:8]),
'SCMOC':int(last_file['SCMOC'][6:8])}
fhours = np.arange(t_range[0], t_range[1], t_gap)
for ifhour in fhours:
if (ifhour == fhours[0] ):
time_all=datetime(y_s['SCMOC'],m_s['SCMOC'],d_s['SCMOC'],h_s['SCMOC'])+timedelta(hours=int(ifhour))
else:
time_all=np.append(time_all,datetime(y_s['SCMOC'],m_s['SCMOC'],d_s['SCMOC'],h_s['SCMOC'])+timedelta(hours=int(ifhour)))
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
t2m=utl.get_model_points_gy(dir_rqd[9], filenames, points,allExists=False)
if(name_opt[0] == 'rh2m'):
rh2m=utl.get_model_points_gy(dir_opt[0], filenames, points,allExists=False)
Td2m=mpcalc.dewpoint_rh(t2m['data'].values*units('degC'),rh2m['data'].values/100.)
p_vapor=(rh2m['data'].values/100.)*6.105*(math.e**((17.27*t2m['data'].values/(237.7+t2m['data'].values))))
if(name_opt[0] == 'Td2m'):
Td2m=utl.get_model_points_gy(dir_opt[0], filenames, points,allExists=False)
rh2m=mpcalc.relative_humidity_from_dewpoint(t2m['data'].values* units('degC'),
Td2m['data'].values* units('degC'))
p_vapor=(np.array(rh2m))*6.105*(math.e**((17.27*t2m['data'].values/(237.7+t2m['data'].values))))
Td2m=np.array(Td2m['data'].values)* units('degC')
u10m=utl.get_model_points_gy(dir_rqd[10], filenames, points,allExists=False)
v10m=utl.get_model_points_gy(dir_rqd[11], filenames, points,allExists=False)
wsp10m=(u10m['data']**2+v10m['data']**2)**0.5
AT=1.07*t2m['data'].values+0.2*p_vapor-0.65*wsp10m-2.7
if((t_range[1]) > 72):
fhours = np.arange(6, t_range[1], 6)
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
r03=utl.get_model_points_gy(dir_rqd[8], filenames, points,allExists=False)
else:
r03=utl.get_model_points_gy(dir_rqd[7], filenames, points,allExists=False)
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file['SCMOC']+'.'+str(fhour).zfill(3) for fhour in fhours]
VIS=utl.get_model_points_gy(dir_rqd[6], filenames, points,allExists=False,fill_null=True,Null_value=-0.001)
if(last_file['SCMOC'] == last_file[model] and t_range[1] > 72):
fhours = np.append(np.arange(3,72,3),np.arange(72, (t_range[1]), 6))
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model] and t_range[1] > 60):
fhours = np.append(np.arange(3,60,3),np.arange(60, (t_range[1]), 6))
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model] and t_range[1] <= 60):
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] == last_file[model] and t_range[1] <= 72):
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
TCDC=utl.get_model_points_gy(dir_rqd[2], filenames2, points,allExists=False)
LCDC=utl.get_model_points_gy(dir_rqd[3], filenames2, points,allExists=False)
u100m=utl.get_model_points_gy(dir_rqd[4], filenames2, points,allExists=False)
v100m=utl.get_model_points_gy(dir_rqd[5], filenames2, points,allExists=False)
wsp100m=(u100m['data']**2+v100m['data']**2)**0.5
if(fhours[-1] < 120):
gust10m=utl.get_model_points_gy(dir_rqd[0], filenames, points,allExists=False)
if(fhours[-1] > 120):
if(last_file['SCMOC'] == last_file[model]):
fhours = np.arange(0, t_range[1], 6)
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model]):
fhours = np.arange(0, t_range[1], 6)
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
gust10m=utl.get_model_points_gy(dir_rqd[1], filenames, points,allExists=False)
sta_graphics.draw_Station_Synthetical_Forecast_From_Cassandra(
t2m=t2m,Td2m=Td2m,AT=AT,u10m=u10m,v10m=v10m,u100m=u100m,v100m=v100m,
gust10m=gust10m,wsp10m=wsp10m,wsp100m=wsp100m,r03=r03,TCDC=TCDC,LCDC=LCDC,
draw_VIS=draw_VIS,VIS=VIS,drw_thr=drw_thr,
time_all=time_all,
model=model,points=points,
output_dir=output_dir,extra_info=extra_info)
def Station_Snow_Synthetical_Forecast_From_Cassandra(
model='ECMWF',
output_dir=None,
t_range=[0,84],
t_gap=3,
points={'lon':[116.3833], 'lat':[39.9]},
initTime=None,
draw_VIS=True,drw_thr=False,
extra_info={
'output_head_name':' ',
'output_tail_name':' ',
'point_name':' '}
):
#+get all the directories needed
try:
dir_rqd=[
"ECMWF_HR/10_METRE_WIND_GUST_IN_THE_LAST_3_HOURS/",
"ECMWF_HR/10_METRE_WIND_GUST_IN_THE_LAST_6_HOURS/",
"ECMWF_HR/SNOD/",
"ECMWF_HR/SDEN/",
"ECMWF_HR/UGRD_100M/",
"ECMWF_HR/VGRD_100M/",
"NWFD_SCMOC/VIS/",
"NCEP_GFS_HR/SNOD/",
"ECMWF_HR/SNOW06/",
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='T2m'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='u10m'),
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='v10m'),
'ECMWF_ENSEMBLE/RAW/SNOW06/'
]
except KeyError:
raise ValueError('Can not find all required directories needed')
try:
dir_opt=[
utl.Cassandra_dir(
data_type='surface',data_source=model,var_name='Td2m')
]
name_opt=['Td2m']
except:
dir_opt=[
utl.Cassandra_dir(data_type='surface',data_source=model,var_name='rh2m')
]
name_opt=['rh2m']
#+get all the directories needed
if(initTime == None):
last_file={model:get_latest_initTime(dir_rqd[0]),
'SCMOC':get_latest_initTime(dir_rqd[6]),
}
else:
last_file={model:initTime[0],
'SCMOC':initTime[1],
}
y_s={model:int('20'+last_file[model][0:2]),
'SCMOC':int('20'+last_file['SCMOC'][0:2])}
m_s={model:int(last_file[model][2:4]),
'SCMOC':int(last_file['SCMOC'][2:4])}
d_s={model:int(last_file[model][4:6]),
'SCMOC':int(last_file['SCMOC'][4:6])}
h_s={model:int(last_file[model][6:8]),
'SCMOC':int(last_file['SCMOC'][6:8])}
fhours = np.arange(t_range[0], t_range[1], t_gap)
for ifhour in fhours:
if (ifhour == fhours[0] ):
time_all=datetime(y_s['SCMOC'],m_s['SCMOC'],d_s['SCMOC'],h_s['SCMOC'])+timedelta(hours=int(ifhour))
else:
time_all=np.append(time_all,datetime(y_s['SCMOC'],m_s['SCMOC'],d_s['SCMOC'],h_s['SCMOC'])+timedelta(hours=int(ifhour)))
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
t2m=utl.get_model_points_gy(dir_rqd[9], filenames, points,allExists=False)
if(name_opt[0] == 'rh2m'):
rh2m=utl.get_model_points_gy(dir_opt[0], filenames, points,allExists=False)
Td2m=mpcalc.dewpoint_rh(t2m['data'].values*units('degC'),rh2m['data'].values/100.)
p_vapor=(rh2m['data'].values/100.)*6.105*(math.e**((17.27*t2m['data'].values/(237.7+t2m['data'].values))))
if(name_opt[0] == 'Td2m'):
Td2m=utl.get_model_points_gy(dir_opt[0], filenames, points,allExists=False)
rh2m=mpcalc.relative_humidity_from_dewpoint(t2m['data'].values* units('degC'),
Td2m['data'].values* units('degC'))
p_vapor=(np.array(rh2m))*6.105*(math.e**((17.27*t2m['data'].values/(237.7+t2m['data'].values))))
Td2m=np.array(Td2m['data'].values)* units('degC')
#SN06_ensm=utl.get_model_points_gy(dir_rqd[12], filenames, points,allExists=False)
'''
for i in range(0,len(SN06_ensm['forecast_period'])):
SN06_std=np.std(np.squeeze(SN06_ensm['data'].values[i,:]))
SN06_mean=np.mean(np.squeeze(SN06_ensm['data'].values[i,:]))
if(i == 0):
SN06_01=norm.pdf(0.01, SN06_mean, SN06_std)
SN06_10=norm.pdf(0.1, SN06_mean, SN06_std)
SN06_25=norm.pdf(0.25, SN06_mean, SN06_std)
SN06_50=norm.pdf(0.5, SN06_mean, SN06_std)
SN06_75=norm.pdf(0.75, SN06_mean, SN06_std)
SN06_90=norm.pdf(0.9, SN06_mean, SN06_std)
SN06_99=norm.pdf(0.99, SN06_mean, SN06_std)
if(i > 0):
SN06_01=[SN06_01,norm.pdf(0.01, SN06_mean, SN06_std)]
SN06_10=[SN06_10,norm.pdf(0.1, SN06_mean, SN06_std)]
SN06_25=[SN06_25,norm.pdf(0.25, SN06_mean, SN06_std)]
SN06_50=[SN06_50,norm.pdf(0.5, SN06_mean, SN06_std)]
SN06_75=[SN06_75,norm.pdf(0.75, SN06_mean, SN06_std)]
SN06_90=[SN06_90,norm.pdf(0.9, SN06_mean, SN06_std)]
SN06_99=[SN06_99,norm.pdf(0.99, SN06_mean, SN06_std)]
SN06_ensm_stc={
'SN06_01'=SN06_01
'SN06_10'=SN06_10
'SN06_25'=SN06_25
'SN06_50'=SN06_50
'SN06_75'=SN06_75
'SN06_90'=SN06_90
'SN06_99'=SN06_99
}
'''
u10m=utl.get_model_points_gy(dir_rqd[10], filenames, points,allExists=False)
v10m=utl.get_model_points_gy(dir_rqd[11], filenames, points,allExists=False)
wsp10m=(u10m['data']**2+v10m['data']**2)**0.5
AT=1.07*t2m['data'].values+0.2*p_vapor-0.65*wsp10m-2.7
#https://en.wikipedia.org/wiki/Wind_chill
TWC=13.12+0.6215*t2m['data'].values-11.37*(wsp10m**0.16)+0.3965*t2m['data'].values*(wsp10m**0.16)
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file['SCMOC']+'.'+str(fhour).zfill(3) for fhour in fhours]
VIS=utl.get_model_points_gy(dir_rqd[6], filenames, points,allExists=False,fill_null=True,Null_value=-0.001)
if(last_file['SCMOC'] == last_file[model] and t_range[1] > 72):
fhours = np.append(np.arange(3,72,3),np.arange(72, (t_range[1]), 6))
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model] and t_range[1] > 60):
fhours = np.append(np.arange(3,60,3),np.arange(60, (t_range[1]), 6))
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model] and t_range[1] <= 60):
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] == last_file[model] and t_range[1] <= 72):
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
filenames2 = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
SNOD1=utl.get_model_points_gy(dir_rqd[2], filenames2, points,allExists=False)
SNOD2=utl.get_model_points_gy(dir_rqd[7], filenames2, points,allExists=False)
SDEN=utl.get_model_points_gy(dir_rqd[3], filenames2, points,allExists=False)
SN06=utl.get_model_points_gy(dir_rqd[8], filenames2, points,allExists=False)
u100m=utl.get_model_points_gy(dir_rqd[4], filenames2, points,allExists=False)
v100m=utl.get_model_points_gy(dir_rqd[5], filenames2, points,allExists=False)
wsp100m=(u100m['data']**2+v100m['data']**2)**0.5
if(fhours[-1] < 120):
gust10m=utl.get_model_points_gy(dir_rqd[0], filenames, points,allExists=False)
if(fhours[-1] > 120):
if(last_file['SCMOC'] == last_file[model]):
fhours = np.arange(0, t_range[1], 6)
filenames = [last_file[model]+'.'+str(fhour).zfill(3) for fhour in fhours]
if(last_file['SCMOC'] != last_file[model]):
fhours = np.arange(0, t_range[1], 6)
filenames = [last_file[model]+'.'+str(fhour+12).zfill(3) for fhour in fhours]
gust10m=utl.get_model_points_gy(dir_rqd[1], filenames, points,allExists=False)
sta_graphics.draw_Station_Snow_Synthetical_Forecast_From_Cassandra(
TWC=TWC,AT=AT,u10m=u10m,v10m=v10m,u100m=u100m,v100m=v100m,
gust10m=gust10m,wsp10m=wsp10m,wsp100m=wsp100m,SNOD1=SNOD1,SNOD2=SNOD2,SDEN=SDEN,SN06=SN06,
draw_VIS=draw_VIS,VIS=VIS,drw_thr=drw_thr,
time_all=time_all,
model=model,points=points,
output_dir=output_dir,extra_info=extra_info)
def point_uv_gust_tmp_rh_rn_fcst(output_dir=None,
t_range=[0, 60],
t_gap=3,
points={
'lon': [116.3833],
'lat': [39.9],
'altitude': [1351]
},
initTime=None,
day_back=0,
extra_info={
'output_head_name': ' ',
'output_tail_name': ' ',
'point_name': ' '
},
**kwargs):
#+get all the directories needed
try:
dir_rqd = [
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='T2m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='u10m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='v10m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='rh2m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='RAIN' + str(t_gap).zfill(2)),
utl.Cassandra_dir(data_type='surface',
data_source='OBS',
var_name='PLOT_GUST')
]
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if (initTime == None):
initTime = MICAPS_IO.get_latest_initTime(dir_rqd[0])
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
gust_sta = MICAPS_IO.get_station_data(directory=dir_rqd[5],
dropna=True,
cache=False)
datetime_sta = pd.to_datetime(str(
gust_sta.time[0])).replace(tzinfo=None).to_pydatetime()
datetime_model_initTime = datetime.strptime('20' + initTime, '%Y%m%d%H')
u10_his_md = []
v10_his_md = []
wsp_his_sta_point = []
model_filenames_his = None
for iinit in range(0, 240, 12):
for ifhour in range(0, 87, 3):
for iobs in range(0, 168, 1):
initTime_his = datetime_model_initTime - timedelta(hours=iinit)
validTime_his = initTime_his + timedelta(hours=ifhour)
staTime_his = datetime_sta - timedelta(hours=iobs)
if (staTime_his == validTime_his):
model_filename_his = initTime_his.strftime(
'%Y%m%d%H')[2:10] + '.' + str(ifhour).zfill(3)
sta_filename_his = validTime_his.strftime(
'%Y%m%d%H') + '0000.000'
data_md1 = MICAPS_IO.get_model_grid(
dir_rqd[1], filename=model_filename_his)
if (data_md1 is None):
continue
data_md2 = MICAPS_IO.get_model_grid(
dir_rqd[1], filename=model_filename_his)
if (data_md2 is None):
continue
data_sta = MICAPS_IO.get_station_data(
directory=dir_rqd[5],
filename=sta_filename_his,
dropna=True,
cache=True)
if (data_sta is None):
continue
u10_his_md.append(data_md1)
v10_his_md.append(data_md2)
wsp_his_sta_interp = utl.sta_to_point_interpolation(
points=points, sta=data_sta, var_name='Gust_speed')
wsp_his_sta_point.append(wsp_his_sta_interp[:])
u10_his_md = xr.concat(u10_his_md, dim='time')
v10_his_md = xr.concat(v10_his_md, dim='time')
wsp_his_md = (u10_his_md**2 + v10_his_md**2)**0.5
wsp_his_md_point = wsp_his_md.interp(lon=('points', points['lon']),
lat=('points', points['lat']))
model = LinearRegression(copy_X=True,
fit_intercept=True,
n_jobs=1,
normalize=False)
x = np.squeeze(wsp_his_md_point['data'].values).reshape(-1, 1)
y = np.squeeze(wsp_his_sta_point).reshape(-1, 1)
model.fit(x, y)
if (model.coef_ < 0.2):
f2 = np.polyfit(np.squeeze(x), np.squeeze(y), 2)
model2 = np.poly1d(f2)
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [initTime + '.' + str(fhour).zfill(3) for fhour in fhours]
t2m = utl.get_model_points_gy(dir_rqd[0],
filenames,
points,
allExists=False)
u10m = utl.get_model_points_gy(dir_rqd[1],
filenames,
points,
allExists=False)
v10m = utl.get_model_points_gy(dir_rqd[2],
filenames,
points,
allExists=False)
rh = utl.get_model_points_gy(dir_rqd[3],
filenames,
points,
allExists=False)
rn = utl.get_model_points_gy(dir_rqd[4],
filenames,
points,
allExists=False)
gust10m_predict = u10m.copy()
if (model.coef_ > 0.2):
gust10m_predict['data'].values = np.squeeze(
model.predict(
np.squeeze((u10m['data'].values**2 +
v10m['data'].values**2)**0.5).reshape(-1,
1))).reshape(
-1, 1, 1)
else:
gust10m_predict['data'].values = np.squeeze(
model2(
np.squeeze((u10m['data'].values**2 +
v10m['data'].values**2)**0.5))).reshape(-1, 1, 1)
sta_graphics.draw_point_uv_tmp_rh_rn_gust_fcst(t2m=t2m,
u10m=u10m,
v10m=v10m,
rh=rh,
rn=rn,
gust=gust10m_predict,
model='中央气象台中短期指导',
output_dir=output_dir,
points=points,
extra_info=extra_info)
def point_uv_ecgust_tmp_rh_rn_fcst(output_dir=None,
t_range=[0, 60],
t_gap=3,
points={
'lon': [116.3833],
'lat': [39.9],
'altitude': [1351]
},
initTime=None,
day_back=0,
extra_info={
'output_head_name': ' ',
'output_tail_name': ' ',
'point_name': ' '
},
**kwargs):
#+get all the directories needed
try:
dir_rqd = [
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='T2m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='u10m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='v10m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='rh2m'),
utl.Cassandra_dir(data_type='surface',
data_source='中央气象台中短期指导',
var_name='RAIN' + str(t_gap).zfill(2)),
utl.Cassandra_dir(data_type='surface',
data_source='ECMWF',
var_name='10M_GUST_3H')
]
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if (initTime == None):
initTime = MICAPS_IO.get_latest_initTime(dir_rqd[0])
initTime2 = MICAPS_IO.get_latest_initTime(dir_rqd[-1])
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
fhours = np.arange(t_range[0], t_range[1], t_gap)
fhours2 = np.arange(t_range[0], t_range[1] + 12, t_gap)
filenames = [initTime + '.' + str(fhour).zfill(3) for fhour in fhours]
filenames2 = [initTime2 + '.' + str(fhour).zfill(3) for fhour in fhours2]
t2m = utl.get_model_points_gy(dir_rqd[0],
filenames,
points,
allExists=False)
u10m = utl.get_model_points_gy(dir_rqd[1],
filenames,
points,
allExists=False)
v10m = utl.get_model_points_gy(dir_rqd[2],
filenames,
points,
allExists=False)
rh = utl.get_model_points_gy(dir_rqd[3],
filenames,
points,
allExists=False)
rn = utl.get_model_points_gy(dir_rqd[4],
filenames,
points,
allExists=False)
gust = utl.get_model_points_gy(dir_rqd[5],
filenames2,
points,
allExists=False)
sta_graphics.draw_point_uv_tmp_rh_rn_gust_fcst(t2m=t2m,
u10m=u10m,
v10m=v10m,
rh=rh,
rn=rn,
gust=gust,
model='中央气象台中短期指导',
output_dir=output_dir,
points=points,
extra_info=extra_info)
def point_fcst_tmp_according_to_3D_field_box_line(
output_dir=None,
t_range=[0,60],
t_gap=3,
points={'lon':[116.3833], 'lat':[39.9], 'altitude':[1351]},
initTime=None,obs_ID=54511,day_back=0,
extra_info={
'output_head_name':' ',
'output_tail_name':' ',
'point_name':' ',
'drw_thr':True,
'levels_for_interp':[1000, 925, 850, 700, 500,300,200]}
):
try:
dir_rqd=[utl.Cassandra_dir(data_type='high',data_source='ECMWF_ENSEMBLE',var_name='HGT_RAW',lvl=''),
utl.Cassandra_dir(data_type='high',data_source='ECMWF_ENSEMBLE',var_name='TMP_RAW',lvl='')]
#utl.Cassandra_dir(data_type='surface',data_source=model,var_name='RAIN'+str(t_gap).zfill(2)+'_RAW')]
except KeyError:
raise ValueError('Can not find all required directories needed')
#-get all the directories needed
if(initTime == None):
initTime = get_latest_initTime(dir_rqd[0][0:-1]+'/850')
#initTime=utl.filename_day_back_model(day_back=day_back,fhour=0)[0:8]
directory=dir_rqd[0][0:-1]
if(t_range[1] > 72):
fhours = np.append(np.arange(t_range[0], 72, t_gap),np.arange(72,t_range[1],6))
else:
fhours = np.arange(t_range[0], t_range[1], t_gap)
filenames = [initTime+'.'+str(fhour).zfill(3) for fhour in fhours]
HGT_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
directory=dir_rqd[0][0:-1]
directory=dir_rqd[1][0:-1]
TMP_4D=get_model_3D_grids(directory=directory,filenames=filenames,levels=extra_info['levels_for_interp'], allExists=False)
#rn=utl.get_model_points_gy(dir_rqd[4], filenames, points,allExists=False)
directory=dir_rqd[1][0:-1]
coords_info_2D=utl.get_model_points_gy(directory+str(extra_info['levels_for_interp'][0])+'/',
points=points,filenames=filenames,allExists=False)
delt_xy=HGT_4D['lon'].values[1]-HGT_4D['lon'].values[0]
mask = (HGT_4D['lon']<(points['lon']+2*delt_xy))&(HGT_4D['lon']>(points['lon']-2*delt_xy))&(HGT_4D['lat']<(points['lat']+2*delt_xy))&(HGT_4D['lat']>(points['lat']-2*delt_xy))
HGT_4D_sm=HGT_4D['data'].where(mask,drop=True)
TMP_4D_sm=TMP_4D['data'].where(mask,drop=True)
lon_md=np.squeeze(HGT_4D_sm['lon'].values)
lat_md=np.squeeze(HGT_4D_sm['lat'].values)
alt_md=np.squeeze(HGT_4D_sm.values*10).flatten()
time_md=np.squeeze(HGT_4D_sm['forecast_period'].values)
number_md=np.squeeze(HGT_4D_sm['number'].values)
'''
coords = np.zeros((len(time_md),len(number_md),len(extra_info['levels_for_interp']),len(lat_md),len(lon_md),5))
coords[...,0]=time_md.reshape((len(time_md),1,1,1,1))
coords[...,1]=number_md.reshape((1,len(number_md),1,1,1))
coords[...,3] = lat_md.reshape((1,1,1,len(lat_md),1))
coords[...,4] = lon_md.reshape((1,1,1,1,len(lon_md)))
coords = coords.reshape((alt_md.size,5))
coords[:,2]=alt_md
interpolator_TMP = LinearNDInterpolator(coords,TMP_4D_sm.values.reshape((TMP_4D_sm.values.size)),rescale=True)
coords2 = np.zeros((len(time_md),len(number_md),1,1,1,5))
coords2[...,0]=time_md.reshape((len(time_md),1,1,1,1))
coords2[...,1]=number_md.reshape(1,(len(number_md),1,1,1))
coords2[...,2]=points['altitude'][0]
coords2[...,3] = points['lat'][0]
coords2[...,4] = points['lon'][0]
coords2 = coords2.reshape((time_md.size,5))
TMP_interped=np.squeeze(interpolator_TMP(coords2))
'''
TMP_interped=np.zeros((len(time_md),len(number_md)))
for it in range(0,len(time_md)):
for inum in range(0,len(number_md)):
alt_md=np.squeeze(HGT_4D_sm.values[it,inum,:,:,:]*10).flatten()
coords = np.zeros((len(extra_info['levels_for_interp']),len(lat_md),len(lon_md),3))
coords[...,1] = lat_md.reshape((1,len(lat_md),1))
coords[...,2] = lon_md.reshape((1,1,len(lon_md)))
coords = coords.reshape((alt_md.size,3))
coords[:,0]=alt_md
interpolator_TMP = LinearNDInterpolator(coords,TMP_4D_sm.values[it,inum,:,:,:].reshape((TMP_4D_sm.values[it,inum,:,:,:].size)),rescale=True)
coords2 = np.zeros((1,1,1,3))
coords2[...,0]=points['altitude'][0]
coords2[...,1] = points['lat'][0]
coords2[...,2] = points['lon'][0]
coords2 = coords2.reshape((1,3))
TMP_interped[it,inum]=np.squeeze(interpolator_TMP(coords2))
TMP_interped_xr=coords_info_2D.copy()
TMP_interped_xr['data'].values[:,:,0,0]=TMP_interped
TMP_interped_xr.attrs['model']='ECMWF_ENSEMBLE'
Ensemble_graphics.box_line_temp(TMP=TMP_interped_xr,
points=points,
extra_info=extra_info,output_dir=output_dir)
