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import datetime, os
from datetime import timezone
import glob
import numpy as np
from netCDF4 import Dataset, Dimension, Variable
from aeolus.geos_nav import GEOSNavigation
amv_file_duration = 60 # minutes
half_width = 20 # search box centered on AEOLUS profile (FGF coordinates)
num_elems = 5424
num_lines = 5424
first_time = True
ftimes = []
flist = None
G16_lon_range = [-130.0, -30.0]
G16_lat_range = [-64.0, 64.0]
class MyGenericException(Exception):
def __init__(self, message):
self.message = message
def get_datetime(pathname):
fname = os.path.split(pathname)[1]
toks = fname.split('_')
dstr = toks[4]
tstr = toks[5]
dtstr = dstr+tstr
dto = datetime.datetime.strptime(dtstr, '%Y%j%H%M').replace(tzinfo=timezone.utc)
return dto
def get_datetime_ops(pathname):
fname = os.path.split(pathname)[1]
toks = fname.split('_')
dtstr = toks[3]
dtstr = dtstr[:-3]
dto = datetime.datetime.strptime(dtstr, 's%Y%j%H%M').replace(tzinfo=timezone.utc)
return dto
def get_file_containing_time(timestamp, files_path, file_time_span, amv_source='OPS', band='14'):
global first_time, ftimes, flist
if first_time is True:
if amv_source == 'OPS':
flist = glob.glob(files_path + 'OR_ABI-L2-DMWF*'+'C'+band+'*.nc')
dto_func = get_datetime_ops
elif amv_source == 'SSEC':
flist = glob.glob(files_path + '*WINDS_AMV_EN-'+band+'*.nc')
dto_func = get_datetime
for pname in flist: # TODO: make better with regular expressions (someday)
dto = dto_func(pname)
dto_start = dto
dto_end = dto + datetime.timedelta(minutes=file_time_span)
ftimes.append((dto_start.timestamp(), dto_end.timestamp()))
first_time = False
k = -1
for i in range(len(ftimes)):
if (timestamp >= ftimes[i][0]) and (timestamp < ftimes[i][1]):
k = i
break
if k < 0:
return None, None, None
return flist[k], ftimes[k], k
# imports the S4 NOAA output
# filename: full path as a string, '/home/user/filename'
# returns a dict: time -> list of profiles (a profile is a list of levels)
def get_aeolus_time_dict(filename, lon360=False):
time_dict = {}
with open(filename) as file:
while True:
prof_hdr = file.readline()
if not prof_hdr:
break
toks = prof_hdr.split()
yr = int(float(toks[0]))
mon = int(float(toks[1]))
dy = int(float(toks[2]))
hr = int(float(toks[3]))
mn = int(float(toks[4]))
ss = int(float(toks[5]))
lon = float(toks[6])
lat = float(toks[7])
nlevs = int(toks[8])
if lon360:
if lon < 0:
lon += 360.0
else:
if lon > 180.0:
lon -= 360.0
dto = datetime.datetime(year=yr, month=mon, day=dy, hour=hr, minute=mn, second=ss)
dto = dto.replace(tzinfo=timezone.utc)
timestamp = dto.timestamp()
prof = []
if time_dict.get(timestamp, -1) == -1:
prof_s = []
prof_s.append(prof)
time_dict[timestamp] = prof_s
else:
prof_s = time_dict.get(timestamp)
prof_s.append(prof)
for k in range(nlevs):
line = file.readline()
toks = line.split()
lvlidx = int(toks[0])
hhh = float(toks[1]) * 1000.0
hht = float(toks[2]) * 1000.0
hhb = float(toks[3]) * 1000.0
err = float(toks[4])
azm = float(toks[5])
ws = float(toks[6])
len = float(toks[7])
tup = (lat, lon, hhh, hht, hhb, azm, ws)
prof.append(tup)
file.close()
return time_dict
# make each profile at a timestamp a numpy array
def time_dict_to_nd(time_dict):
keys = list(time_dict.keys())
for key in keys:
vals = time_dict[key]
if vals is not None:
for i in range(len(vals)):
nda = np.array(vals[i])
vals[i] = nda
return time_dict
def get_search_box(nav, lon, lat):
cc, ll = nav.earth_to_lc(lon, lat)
c_rng = [cc - half_width, cc + half_width]
l_rng = [ll - half_width, ll + half_width]
if c_rng[0] < 0:
c_rng[0] = 0
if l_rng[0] < 0:
l_rng[0] = 0
if c_rng[1] >= num_elems:
c_rng[1] = num_elems - 1
if l_rng[1] >= num_lines:
l_rng[1] = num_lines - 1
return c_rng, l_rng
# aeolus_dict: time -> profiles
# amv_files_path: directory containing AMVs, '/home/user/amvdir/'
# return dict: aeolus time -> tuple (amv_lon, amv_lat, amv_pres, amv_spd, amv_dir)
def match_amvs_to_aelous(aeolus_dict, amv_files_path, amv_source='OPS', band='C14'):
nav = GEOSNavigation()
match_dict = {}
keys = list(aeolus_dict.keys())
last_f_idx = -1
for key in keys:
fname, ftime, f_idx = get_file_containing_time(key, amv_files_path, amv_file_duration, amv_source, band)
if f_idx is None:
continue
profs = aeolus_dict.get(key)
layers = profs[0]
if layers is None:
continue
lat = layers[0, 0]
lon = layers[0, 1]
# check range
if lat > G16_lat_range[1] or lat < G16_lat_range[0]:
continue
if lon > G16_lon_range[1] or lon < G16_lon_range[0]:
continue
# ------------------------------------------------
if f_idx != last_f_idx:
last_f_idx = f_idx
ds = Dataset(fname)
amv_lons = ds['Longitude'][:]
amv_lats = ds['Latitude'][:]
amv_spd = ds['Wind_Speed'][:]
amv_dir = ds['Wind_Dir'][:]
amv_pres = ds['MedianPress'][:]
cc = ds['Element'][:]
ll = ds['Line'][:]
# cc, ll = nav.earth_to_lc_s(amv_lons, amv_lats)
ds.close()
c_rng, l_rng = get_search_box(nav, lon, lat)
in_cc = np.logical_and(cc > c_rng[0], cc < c_rng[1])
in_ll = np.logical_and(ll > l_rng[0], ll < l_rng[1])
in_box = np.logical_and(in_cc, in_ll)
num_amvs = np.sum(in_box)
if num_amvs == 0:
continue
match_dict[key] = (amv_lons[in_box], amv_lats[in_box], amv_pres[in_box], amv_spd[in_box], amv_dir[in_box])
return match_dict
# full path as string filename to create, '/home/user/newfilename'
# aeolus_to_amv_dct: output from match_amvs_to_aeolus
# aeolus_dct: output from get_aeolus_time_dict
def create_file(filename, aeolus_to_amv_dct, aeolus_dct):
keys = list(aeolus_to_amv_dct.keys())
num_amvs = []
num_levs = []
times = []
namvs = 0
nlevs = 0
for key in keys:
lons, lats, pres, spd, dir = aeolus_to_amv_dct.get(key)
num_amvs.append(len(lons))
namvs += len(lons)
prof_s = aeolus_dct.get(key)
prof = prof_s[0]
num_levs.append(prof.shape[0])
nlevs += prof.shape[0]
times.append(key)
amv_per_alus = len(aeolus_to_amv_dct)
rootgrp = Dataset(filename, 'w', format='NETCDF4')
dim_amvs = rootgrp.createDimension('amvs', size=namvs)
dim_alus = rootgrp.createDimension('profs', size=nlevs)
dim_num_aeolus_prof = rootgrp.createDimension('num_aeolus_profs', size=len(aeolus_to_amv_dct))
amv_lon = rootgrp.createVariable('amv_longitude', 'f4', ['amvs'])
amv_lon.units = 'degrees east'
amv_lat = rootgrp.createVariable('amv_latitude', 'f4', ['amvs'])
amv_lat.units = 'degrees north'
amv_spd = rootgrp.createVariable('amv_spd', 'f4', ['amvs'])
amv_spd.units = 'm s-1'
amv_dir = rootgrp.createVariable('amv_dir', 'f4', ['amvs'])
amv_dir.units = 'degree'
amv_pres = rootgrp.createVariable('amv_pres', 'f4', ['amvs'])
amv_pres.units = 'hPa'
num_amvs_per_prof = rootgrp.createVariable('num_amvs_per_prof', 'i4', ['num_aeolus_profs'])
num_levs_per_prof = rootgrp.createVariable('num_levs_per_prof', 'i4', ['num_aeolus_profs'])
prof_time = rootgrp.createVariable('time', 'f4', ['num_aeolus_profs'])
prof_time.units = 'seconds since 1970-01-1 00:00:00'
prf_azm = rootgrp.createVariable('prof_azm', 'f4', ['profs'])
prf_azm.units = 'degree'
prf_spd = rootgrp.createVariable('prof_spd', 'f4', ['profs'])
prf_spd.units = 'm s-1'
prf_hht = rootgrp.createVariable('prof_hht', 'f4', ['profs'])
prf_hht.units = 'meter'
prf_hhb = rootgrp.createVariable('prof_hhb', 'f4', ['profs'])
prf_hhb.units = 'meter'
i_a = 0
i_c = 0
for idx, key in enumerate(keys):
namvs = num_amvs[idx]
nlevs = num_levs[idx]
i_b = i_a + namvs
i_d = i_c + nlevs
lons, lats, pres, spd, dir = aeolus_to_amv_dct.get(key)
amv_lon[i_a:i_b] = lons[:]
amv_lat[i_a:i_b] = lats[:]
amv_spd[i_a:i_b] = spd[:]
amv_dir[i_a:i_b] = dir[:]
amv_pres[i_a:i_b] = pres[:]
i_a += namvs
prof_s = aeolus_dct.get(key)
prof = prof_s[0]
prf_hht[i_c:i_d] = prof[:, 2]
prf_hhb[i_c:i_d] = prof[:, 3]
prf_azm[i_c:i_d] = prof[:, 5]
prf_spd[i_c:i_d] = prof[:, 6]
i_c += nlevs
num_amvs_per_prof[:] = num_amvs
num_levs_per_prof[:] = num_levs
prof_time[:] = times
rootgrp.close()
# def create_file(filename, aeolus_to_amv_dct, aeolus_dct):
# keys = list(aeolus_to_amv_dct.keys())
#
# num_amvs = []
# num_levs = []
# times = []
#
# namvs = 0
# nlevs = 0
# for key in keys:
# lons, lats, pres, spd, dir = aeolus_to_amv_dct.get(key)
# num_amvs.append(len(lons))
# namvs += len(lons)
#
# prof_s = aeolus_dct.get(key)
# prof = prof_s[0]
# num_levs.append(prof.shape[0])
# nlevs += prof.shape[0]
#
# times.append(key)
#
# amv_per_alus = len(aeolus_to_amv_dct)
# rootgrp = Dataset(filename, 'w', format='NETCDF4')
# dim_amvs = rootgrp.createDimension('amvs', size=namvs)
# dim_alus = rootgrp.createDimension('profs', size=nlevs)
# dim_num_aeolus_prof = rootgrp.createDimension('num_aeolus_profs', size=len(aeolus_to_amv_dct))
#
# amv_lon = rootgrp.createVariable('amv_longitude', 'f4', ['amvs'])
# amv_lat = rootgrp.createVariable('amv_latitude', 'f4', ['amvs'])
# amv_spd = rootgrp.createVariable('amv_spd', 'f4', ['amvs'])
# amv_dir = rootgrp.createVariable('amv_dir', 'f4', ['amvs'])
# amv_pres = rootgrp.createVariable('amv_pres', 'f4', ['amvs'])
#
# num_amvs_per_prof = rootgrp.createVariable('num_amvs_per_prof', 'i4', ['num_aeolus_profs'])
# num_levs_per_prof = rootgrp.createVariable('num_levs_per_prof', 'i4', ['num_aeolus_profs'])
# prof_time = rootgrp.createVariable('time', 'f4', ['num_aeolus_profs'])
#
# prf_azm = rootgrp.createVariable('prof_azm', 'f4', ['profs'])
# prf_spd = rootgrp.createVariable('prof_spd', 'f4', ['profs'])
# prf_hht = rootgrp.createVariable('prof_hht', 'f4', ['profs'])
# prf_hhb = rootgrp.createVariable('prof_hhb', 'f4', ['profs'])
#
# i_a = 0
# i_c = 0
# for idx, key in enumerate(keys):
# namvs = num_amvs[idx]
# nlevs = num_levs[idx]
# i_b = i_a + namvs
# i_d = i_c + nlevs
#
# lons, lats, pres, spd, dir = aeolus_to_amv_dct.get(key)
# amv_lon[i_a:i_b] = lons[:]
# amv_lat[i_a:i_b] = lats[:]
# amv_spd[i_a:i_b] = spd[:]
# amv_dir[i_a:i_b] = dir[:]
# amv_pres[i_a:i_b] = pres[:]
# i_a += namvs
#
# prof_s = aeolus_dct.get(key)
# prof = prof_s[0]
# prf_hht[i_c:i_d] = prof[:, 2]
# prf_hhb[i_c:i_d] = prof[:, 3]
# prf_azm[i_c:i_d] = prof[:, 5]
# prf_spd[i_c:i_d] = prof[:, 6]
# i_c += nlevs
#
# num_amvs_per_prof[:] = num_amvs
# num_levs_per_prof[:] = num_levs
# prof_time[:] = times
#
# rootgrp.close()
# aeolus_file: S4 NOAA txt output
# amv_files_dir: G16/17 AMV product file
# outfile: pathname for the Netcdf match file
def run(aeolus_file, amv_files_dir, outfile=None, amv_source='OPS', band='14'):
a_d = get_aeolus_time_dict(aeolus_file)
a_d = time_dict_to_nd(a_d)
m_d = match_amvs_to_aelous(a_d, amv_files_dir, amv_source, band)
if outfile is not None:
create_file(outfile, m_d, a_d)
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import numpy as np
class MyGenericException(Exception):
def __init__(self, message):
self.message = message
DEG_TO_RAD = np.pi/180.0;
RAD_TO_DEG = 180.0/np.pi;
r_pol = 6356.5838 # km
r_eq = 6378.1690 # km
# AHI -------------------------------
# h = 42164.0 # barycentric height, km
# sub_lon = 140.7
# sub_lon *= DEG_TO_RAD
# scan_geom = 'GEOS'
# signs modified from static nav file to work with ABI FGF code
# CFAC = 5.588799E-05
# LFAC = -5.588799E-05
# COFF = -0.1537199
# LOFF = 0.1537199
# computed from static nav file (lon, lat) grid
# Note 0-based to the pixel center
# CFAC = 5.58924125e-05
# LFAC = -5.58810490e-05
# COFF = -1.53678977e-01
# LOFF = 1.53644345e-01
# GOES ------------------------------
h = 42164.16 # barycentric height, km
scan_geom = 'GOES'
sub_lon = -75.0
sub_lon *= DEG_TO_RAD
# official for FD
CFAC = 5.6E-05
LFAC = -5.6E-05
COFF = -0.151844
LOFF = 0.151844
# official for CONUS
#CFAC = 5.6E-05
#COFF = -0.101332
#LFAC = -5.6E-05
#LOFF = 0.128212
# computed for CLAVRx FD
#CFAC = 5.60016368e-05
#LFAC = -5.59941969e-05
#COFF = -1.51780260e-01
#LOFF = 1.51773560e-01
# 65536 = 2^16
class GEOSNavigation:
def __init__(self, sub_lon=-75.0, barycentric_height=42164.16, scan_geom='GOES', CFAC=5.6E-05, LFAC=-5.6E-05, COFF=-0.151844, LOFF=0.151844, num_elems=5424, num_lines=5424):
self.sub_lon = sub_lon * DEG_TO_RAD
self.h = barycentric_height
self.scan_geom = scan_geom
self.CFAC = CFAC
self.LFAC = LFAC
self.COFF = COFF
self.LOFF = LOFF
self.num_lines = num_lines
self.num_elems = num_elems
def earth_to_sat(self, geographic_lon, geographic_lat):
geographic_lon *= DEG_TO_RAD
geographic_lat *= DEG_TO_RAD
geocentric_lat = np.arctan(((r_pol*r_pol)/(r_eq*r_eq))*np.tan(geographic_lat))
r_earth = r_pol / np.sqrt(1.0 - ((r_eq * r_eq - r_pol * r_pol) / (r_eq * r_eq)) * np.cos(geocentric_lat) * np.cos(geocentric_lat))
r_1 = self.h - r_earth * np.cos(geocentric_lat) * np.cos(geographic_lon - self.sub_lon)
r_2 = -r_earth * np.cos(geocentric_lat) * np.sin(geographic_lon - self.sub_lon)
r_3 = r_earth * np.sin(geocentric_lat)
if r_1 > self.h:
return np.nan, np.nan
if self.scan_geom == 'GEOS':
lamda_sat = np.arctan(-r_2/r_1)
theta_sat = np.arcsin(r_3/np.sqrt(r_1*r_1 + r_2*r_2 + r_3*r_3))
elif self.scan_geom == 'GOES':
lamda_sat = np.arcsin(-r_2/np.sqrt(r_1*r_1 + r_2*r_2 + r_3*r_3))
theta_sat = np.arctan(r_3/r_1)
return lamda_sat, theta_sat
def earth_to_sat_s(self, geographic_lon, geographic_lat):
geographic_lon = geographic_lon * DEG_TO_RAD
geographic_lat = geographic_lat * DEG_TO_RAD
geocentric_lat = np.arctan(((r_pol*r_pol)/(r_eq*r_eq))*np.tan(geographic_lat))
r_earth = r_pol / np.sqrt(1.0 - ((r_eq * r_eq - r_pol * r_pol) / (r_eq * r_eq)) * (np.cos(geocentric_lat))**2)
r_1 = self.h - r_earth * np.cos(geocentric_lat) * np.cos(geographic_lon - self.sub_lon)
r_2 = -r_earth * np.cos(geocentric_lat) * np.sin(geographic_lon - self.sub_lon)
r_3 = r_earth * np.sin(geocentric_lat)
if self.scan_geom == 'GEOS':
lamda_sat = np.arctan(-r_2/r_1)
theta_sat = np.arcsin(r_3/np.sqrt(r_1*r_1 + r_2*r_2 + r_3*r_3))
elif self.scan_geom == 'GOES':
lamda_sat = np.arcsin(-r_2/np.sqrt(r_1*r_1 + r_2*r_2 + r_3*r_3))
theta_sat = np.arctan(r_3/r_1)
np.where(r_1 > self.h, lamda_sat == np.nan, lamda_sat)
np.where(r_1 > self.h, theta_sat == np.nan, theta_sat)
return lamda_sat, theta_sat
def sat_to_lc(self, lamda, theta):
# c = COFF + np.rint(lamda * (1/np.power(2, 16)) * CFAC)
# l = LOFF + np.rint(theta * (1/np.power(2, 16)) * LFAC)
# (float(2 ** 16) * (float(lc) - off)) / float(fac) * DEG_TO_RAD
cc = (lamda - self.COFF) / self.CFAC
ll = (theta - self.LOFF) / self.LFAC
cc = np.floor(cc + 0.5)
ll = np.floor(ll + 0.5)
cc = cc.astype(np.int32)
ll = ll.astype(np.int32)
return cc, ll
def earth_to_lc(self, lon, lat):
lamda, theta = self.earth_to_sat(lon, lat)
if np.isnan(lamda):
return None, None
cc, ll = self.sat_to_lc(lamda, theta)
return cc, ll
def earth_to_lc_s(self, lons, lats):
lamda, theta = self.earth_to_sat_s(lons, lats)
cc, ll = self.sat_to_lc(lamda, theta)
np.where(np.isnan(cc), cc == -1, cc)
np.where(np.isnan(ll), ll == -1, ll)
return cc, ll
def earth_to_indexs(self, lons, lats, len_x):
num = lons.shape[0]
idxs = []
for i in range(num):
cc, ll = self.earth_to_lc(lons[i], lats[i])
if cc is None:
idxs.append(-1)
else:
idx = ll * len_x + cc
idxs.append(idx)
idxs = np.array(idxs)
return idxs
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