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makegefsqpfcsv.py
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#!/bin/usr/env python
#import pygrib
import grib2io
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
#input argument in YYYYMMDDHH
ymdh = str(sys.argv[1])
#station info arrays
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]))
#column headers
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))
#array that gets written to csv. Everything will be put in it
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
#do different things for different columns and forecast hours
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':
grbs = grib2io.open('/lfs/h1/ops/prod/com/gefs/v12.3/gefs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/pgrb2ap5/ge'+members[i]+'.t'+str(hour).zfill(2)+'z.pgrb2a.0p50.f'+str(fhours1[j]).zfill(3), mode='r')
#grib message order changes from f00 to f03 to f06
if j==0:
nmbtotal[:,j,i]=0.0
continue
elif j==1:
#precip=grbs[69][0].data()*.03937
precip=grbs.select(shortName='APCP')[0].data*.03937
precip=np.asarray(precip[::-1,:])
elif (j%2)==0:
grbsprev = grib2io.open('/lfs/h1/ops/prod/com/gefs/v12.3/gefs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/pgrb2ap5/ge'+members[i]+'.t'+str(hour).zfill(2)+'z.pgrb2a.0p50.f'+str(fhours1[j-1]).zfill(3), mode='r')
#print(grbs[69][0].data())
#precipnewc=grbs[69][0].data()*.03937
precipnewc=grbs.select(shortName='APCP')[0].data*.03937
precipnewc=np.asarray(precipnewc[::-1,:])
#precipnewp=grbsprev[69][0].data()*.03937
precipnewp=grbsprev.select(shortName='APCP')[0].data*.03937
precipnewp=np.asarray(precipnewp[::-1,:])
precipnew=precipnewc-precipnewp
precip=precip+precipnew
else:
#print(grbs[69][0].data())
#precipnew=grbs[69][0].data()*.03937
precipnew=grbs.select(shortName='APCP')[0].data*.03937
precipnew=np.asarray(precipnew[::-1,:])
precip=precip+precipnew
lats,lons = grbs[31].latlons()
latlist=lats[::-1,0]
lonlist=lons[0,:]
lonlist=np.asarray(lonlist)
latlist=np.asarray(latlist)
#create interpolation function
f=interpolate.interp2d(lonlist,latlist,precip,kind='linear')
for k in range(len(slats)):
znew=np.round(f((360+slons[k]),slats[k]),5)
if j>0:
if nmbtotal[k,j-1,i]>znew:
nmbtotal[k,j-1,i]=znew
nmbtotal[k,j,i]=znew
else:
nmbtotal[k,j,i]=znew
#get GFS data
else:
grbs = grib2io.open('/lfs/h1/ops/prod/com/gfs/v16.3/gfs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/gfs.t'+str(hour).zfill(2)+'z.pgrb2.0p50.f'+str(fhours1[j]).zfill(3), mode='r')
if j==0:
nmbtotal[:,j,34]=0.0
continue
elif j==1:
#precip=grbs[596][0].data()*.03937
precip=grbs.select(shortName='APCP',duration=datetime.timedelta(hours=3))[0].data*.03937
precip=np.asarray(precip[::-1,:])
elif (j%2)==0:
grbsprev = grib2io.open('/lfs/h1/ops/prod/com/gfs/v16.3/gfs.'+str(ymd)+'/'+str(hour).zfill(2)+'/atmos/gfs.t'+str(hour).zfill(2)+'z.pgrb2.0p50.f'+str(fhours1[j-1]).zfill(3), mode='r')
#precipnewc=grbs[596][0].data()*.03937
precipnewc=grbs.select(shortName='APCP',duration=datetime.timedelta(hours=6))[0].data*.03937
precipnewc=np.asarray(precipnewc[::-1,:])
#precipnewp=grbsprev[596][0].data()*.03937
precipnewp=grbsprev.select(shortName='APCP',duration=datetime.timedelta(hours=3))[0].data*.03937
precipnewp=np.asarray(precipnewp[::-1,:])
precipnew=precipnewc-precipnewp
precip=precip+precipnew
else:
#precipnew=grbs[596][0].data()*.03937
precipnew=grbs.select(shortName='APCP',duration=datetime.timedelta(hours=3))[0].data*.03937
precipnew=np.asarray(precipnew[::-1,:])
precip=precip+precipnew
lats,lons = grbs[31].latlons()
latlist=lats[::-1,0]
lonlist=lons[0,:]
lonlist=np.asarray(lonlist)
latlist=np.asarray(latlist)
#create interpolation function
f2=interpolate.interp2d(lonlist,latlist,precip,kind='linear')
for k in range(len(slats)):
znew=np.round(f2((360+slons[k]),slats[k]),5)
if j>0:
if nmbtotal[k,j-1,34]>znew:
nmbtotal[k,j-1,34]=znew
nmbtotal[k,j,34]=znew
else:
nmbtotal[k,j,34]=znew
#compute mean
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])/31.0,5)
#write csv files
for k in range(len(slats)):
f = open("GEFS"+slist[k]+ymdh+"qpf.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()