-
Notifications
You must be signed in to change notification settings - Fork 0
/
makegefs2mtcsv.py
executable file
·137 lines (129 loc) · 5.05 KB
/
makegefs2mtcsv.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
#!/bin/usr/env python
#import pygrib
import grib2io
import csv
import datetime
import ncepy
import numpy as np
import matplotlib
import math
import subprocess
import time,os,sys,multiprocessing
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':
#t1a = time.perf_counter()
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')
#t2a = time.perf_counter()
#t3a = round(t2a-t1a, 3)
#print(("%.3f seconds to open") % t3a)
#grib message order changes from f00 to f03 to f06
if j==0:
#precip=(grbs[64][0].data()-273.15)*1.8 + 32
#t4a = time.perf_counter()
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
#t5a = time.perf_counter()
#t6a = round(t5a-t4a, 3)
#print(("%.3f seconds to select") % t6a)
precip=np.asarray(precip[::-1,:])
elif j==1:
#precip=(grbs[63][0].data()-273.15)*1.8 + 32
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
precip=np.asarray(precip[::-1,:])
else:
#precip=(grbs[63][0].data()-273.15)*1.8 + 32
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
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)
#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]),3)
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:
#precip=(grbs[580][0].data()-273.15)*1.8 + 32
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
precip=np.asarray(precip[::-1,:])
elif j==1:
#precip=(grbs[581][0].data()-273.15)*1.8 + 32
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
precip=np.asarray(precip[::-1,:])
else:
#precip=(grbs[581][0].data()-273.15)*1.8 + 32
precip=(grbs.select(shortName='TMP',level='2 m above ground')[0].data-273.15)*1.8 + 32
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)
#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]),3)
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])/31.0,3)
#write csv files
for k in range(len(slats)):
f = open("GEFS"+slist[k]+ymdh+"2mt.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()