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makegefscapecsv.py
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makegefscapecsv.py
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#!/bin/usr/env python
import pygrib
import csv
import datetime
import ncepy
import numpy as np
import matplotlib
import math
import subprocess
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from scipy import interpolate
import sys
ymdh = str(sys.argv[1])
slist=[]
slats=[]
slons=[]
with open('gfsxstations.txt','r') as f:
for row in f:
x=row.split(',')
slist.append(x[0])
slats.append(float(x[1]))
slons.append(float(x[2]))
members=['time','date','c00','p01','p02','p03','p04','p05','p06','p07','p08','p09','p10','p11','p12','p13','p14','p15','p16','p17','p18','p19','p20','p21','p22','p23','p24','p25','p26','p27','p28','p29','p30','GFS']
fhours=[]
preciptotal=[]
amount=1.0
fhour=60
closest=0 #starting range of forecast hour
furthest=195 #3 hours more than the actual ending forecast hour you want
ymd=ymdh[0:8]
year=int(ymdh[0:4])
month=int(ymdh[4:6])
day=int(ymdh[6:8])
hour=int(ymdh[8:10])
print(year, month , day, hour)
dtime=datetime.datetime(year,month,day,hour,0)
date_list = [dtime + datetime.timedelta(hours=x) for x in range(closest,furthest,3)]
firstdate=dtime - datetime.timedelta(hours=fhour)
fhours1=list(range(closest,furthest,3))
nmbtotal=np.empty((len(slist),len(fhours1),len(members)+1),dtype='object')
print(nmbtotal.shape)
for i in range(len(members)):
print(members[i])
ptotal=0
for j in range(len(fhours1)):
if i==0:
nmbtotal[:,j,i]=fhours1[j]
elif i==1:
nmbtotal[:,j,i]=date_list[j].strftime("%m-%d-%Y:%H")
elif i>1 and members[i]!='GFS':
grbind = pygrib.index('/gpfs/dell4/nco/ops/com/gefs/prod/gefs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/pgrb2bp5/ge'+members[i]+'.t'+str(hour).zfill(2)+'z.pgrb2b.0p50.f'+str(fhours1[j]).zfill(3),'name','level')
#for grb in grbs:
if j==0:
precip=grbind.select(name='Convective available potential energy',level=0)[0].values
precip=np.asarray(precip[::-1,:])
elif j==1:
precip=grbind.select(name='Convective available potential energy',level=0)[0].values
precip=np.asarray(precip[::-1,:])
else:
precip=grbind.select(name='Convective available potential energy',level=0)[0].values
precip=np.asarray(precip[::-1,:])
lats,lons = grbind.select(name='Convective available potential energy',level=0)[0].latlons()
latlist=lats[::-1,0]
lonlist=lons[0,:]
lonlist=np.asarray(lonlist)
latlist=np.asarray(latlist)
f=interpolate.interp2d(lonlist,latlist,precip,kind='linear')
for k in range(len(slats)):
znew=np.round(f((360+slons[k]),slats[k]),3)
nmbtotal[k,j,i]=znew
else:
grbs = pygrib.open('/gpfs/dell1/nco/ops/com/gfs/prod/gfs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/gfs.t'+str(hour).zfill(2)+'z.pgrb2.0p50.f'+str(fhours1[j]).zfill(3))
#for grb in grbs:
if j==0:
precip=grbs[602].values
precip=np.asarray(precip[::-1,:])
elif j==1:
precip=grbs[624].values
precip=np.asarray(precip[::-1,:])
else:
precip=grbs[624].values
precip=np.asarray(precip[::-1,:])
lats,lons = grbs[31].latlons()
latlist=lats[::-1,0]
lonlist=lons[0,:]
lonlist=np.asarray(lonlist)
latlist=np.asarray(latlist)
f=interpolate.interp2d(lonlist,latlist,precip,kind='linear')
for k in range(len(slats)):
znew=np.round(f((360+slons[k]),slats[k]),3)
nmbtotal[k,j,34]=znew
for k in range(len(slats)):
for j in range(len(fhours1)):
nmbtotal[k,j,33]=np.round(np.sum(nmbtotal[k,j,2:33])/31.0,3)
for k in range(len(slats)):
f = open("GEFS"+slist[k]+ymdh+"cape.csv","wt")
try:
writer = csv.writer(f)
writer.writerow(('time','date','c0','p1','p2','p3','p4','p5','p6','p7','p8','p9','p10','p11','p12','p13','p14','p15','p16','p17','p18','p19','p20','p21','p22','p23','p24','p25','p26','p27','p28','p29','p30','mean','GFS'))
for i in range(nmbtotal.shape[1]):
writer.writerow((str(m).replace("[","")).replace("]","") for m in nmbtotal[k,i,:])
finally:
f.close()