def main(args):
start_time = time.time()
wrf_procdir = args.wrf_dir
save_dir = args.save_dir
if wrf_procdir.endswith('/'):
ext = '*.nc'
else:
ext = '/*.nc'
files = sorted(glob.glob(wrf_procdir + ext))
# get the model version (3km or 9km) from the filename
f0 = files[0]
model_ver = f0.split('/')[-1].split('_')[1] # 3km or 9km
os.makedirs(save_dir, exist_ok=True)
# List of variables to plot
plt_vars = ['power160']
kwargs = dict()
# kwargs['lease_areas'] = cf.extract_lease_areas()
for i, f in enumerate(files):
fname = f.split('/')[-1].split('.')[0]
splitter = fname.split('/')[-1].split('_')
ncfile = xr.open_dataset(f, mask_and_scale=False)
for pv in plt_vars:
sfile = cf.save_filepath(save_dir, pv, splitter)
if pv == 'power160':
plt_power(ncfile, model_ver, '160m', sfile, **kwargs)
print('')
print('Script run time: {} minutes'.format(
round(((time.time() - start_time) / 60), 2)))
def main(args):
start_time = time.time()
wrf_procdir = args.wrf_dir
save_dir = args.save_dir
if wrf_procdir.endswith('/'):
ext = '*.nc'
else:
ext = '/*.nc'
files = sorted(glob.glob(wrf_procdir + ext))
# get the model version (3km or 9km) from the filename
f0 = files[0]
model_ver = f0.split('/')[-1].split('_')[1] # 3km or 9km
os.makedirs(save_dir, exist_ok=True)
for i, f in enumerate(files):
fname = f.split('/')[-1].split('.')[0]
splitter = fname.split('/')[-1].split('_')
ncfile = xr.open_dataset(f, mask_and_scale=False)
sfile = cf.save_filepath(save_dir, 'tsk', splitter)
plt_tsk(ncfile, model_ver, sfile)
print('')
print('Script run time: {} minutes'.format(
round(((time.time() - start_time) / 60), 2)))
def main(args):
start_time = time.time()
wrf_procdir = args.wrf_dir
save_dir = args.save_dir
if wrf_procdir.endswith('/'):
ext = '*.nc'
else:
ext = '/*.nc'
files = sorted(glob.glob(wrf_procdir + ext))
# get the model version (3km or 9km) from the filename
f0 = files[0]
model_ver = f0.split('/')[-1].split('_')[1] # 3km or 9km
os.makedirs(save_dir, exist_ok=True)
kwargs = dict()
#kwargs['lease_areas'] = cf.extract_lease_areas()
for i, f in enumerate(files):
fname = f.split('/')[-1].split('.')[0]
splitter = fname.split('/')[-1].split('_')
ncfile = xr.open_dataset(f, mask_and_scale=False)
sfile = cf.save_filepath(save_dir, 'rain', splitter)
# plot hourly and accumulated rainfall (each .nc file contains accumulated precipitation)
# plot accumulated rainfall
plt_rain(ncfile, model_ver, sfile, 'acc', **kwargs)
# plot hourly rainfall
if i > 0:
fprev = files[i - 1]
nc_prev = xr.open_dataset(fprev, mask_and_scale=False)
else:
nc_prev = None
kwargs['ncprev'] = nc_prev
plt_rain(ncfile, model_ver, sfile, 'hourly', **kwargs)
print('')
print('Script run time: {} minutes'.format(
round(((time.time() - start_time) / 60), 2)))
def main(args):
start_time = time.time()
wrf_procdir = args.wrf_dir
save_dir = args.save_dir
if wrf_procdir.endswith('/'):
ext = '*.nc'
else:
ext = '/*.nc'
files = sorted(glob.glob(wrf_procdir + ext))
files = [f for f in files if f.endswith('_M00.nc')]
# get the model version (3km or 9km) from the filename
f0 = files[0]
model_ver = f0.split('/')[-1].split('_')[1] # 3km or 9km
os.makedirs(save_dir, exist_ok=True)
# List of variables to plot
plt_vars = ['ws925']
seabreeze_locations = {
'atlantic_city': {
'lat': 39.4520,
'lon': -74.5670
},
'ocean_city_md': {
'lat': 38.3083,
'lon': -75.1239
},
'oyster_creek': {
'lat': 39.817102,
'lon': -74.213449
},
'sea_isle_city': {
'lat': 39.191604,
'lon': -74.788602
},
'asbury_park': {
'lat': 40.233804,
'lon': -74.089406
}
}
kwargs = dict()
# kwargs['lease_areas'] = cf.extract_lease_areas()
summary = dict(rows=[], locations=seabreeze_locations)
kwargs['summary'] = summary
kwargs['add_text'] = True
for i, f in enumerate(files):
fname = f.split('/')[-1].split('.')[0]
splitter = fname.split('/')[-1].split('_')
ncfile = xr.open_dataset(f, mask_and_scale=False)
for pv in plt_vars:
sfile = cf.save_filepath(save_dir, pv, splitter)
if pv == 'ws925':
plt_windsp(ncfile, model_ver, 925, sfile, **kwargs)
df_headers = [
'time', 'location', 'lat', 'lon', 'pressure_mb', 'wrf_lat', 'wrf_lon',
'wind_speed_meterspersec', 'wind_direction'
]
df = pd.DataFrame(summary['rows'], columns=df_headers)
df.to_csv('{}/seabreeze_summary.csv'.format(save_dir), index=False)
print('')
print('Script run time: {} minutes'.format(
round(((time.time() - start_time) / 60), 2)))