def get_profiles_from_HYCOM(N,folder_hycom,prefix,lon_track,lat_track,\
lon_hycom,lat_hycom,var):
afiles = sorted(glob.glob(os.path.join(folder_hycom, prefix + '*.a')))
file = afiles[N]
#Reading time stamp
year = int(file.split('/')[-1].split('.')[1][0:4])
month = int(file.split('/')[-1].split('.')[1][4:6])
day = int(file.split('/')[-1].split('.')[1][6:8])
hour = int(file.split('/')[-1].split('.')[1][8:10])
dt = int(file.split('/')[-1].split('.')[3][1:])
timestamp_hycom = mdates.date2num(datetime(year, month, day,
hour)) + dt / 24
time_hycom = mdates.num2date(timestamp_hycom)
# Interpolating lat_track and lon_track into HYCOM grid
oklon = np.round(
np.interp(lon_track + 360, lon_hycom[0, :],
np.arange(len(lon_hycom[0, :])))).astype(int)
oklat = np.round(
np.interp(lat_track, lat_hycom[:, 0],
np.arange(len(lat_hycom[:, 0])))).astype(int)
# Reading 3D variable from binary file
var_hyc = readBinz(file[:-2], '3z', var)
var_hycom = var_hyc[oklat, oklon, :].T
time_hycom = np.asarray(time_hycom)
return var_hycom, time_hycom
def get_glider_transect_from_HYCOM(folder_hycom, prefix, nz, lon_hycom,
lat_hycom, var, timestamp_glider,
lon_glider, lat_glider):
afiles = sorted(glob.glob(os.path.join(folder_hycom, prefix + '*.a')))
target_var_hycom = np.empty((nz, len(afiles)))
target_var_hycom[:] = np.nan
time_hycom = []
for x, file in enumerate(afiles):
print(x)
#lines=[line.rstrip() for line in open(file[:-2]+'.b')]
#Reading time stamp
year = int(file.split('/')[-1].split('.')[1][0:4])
month = int(file.split('/')[-1].split('.')[1][4:6])
day = int(file.split('/')[-1].split('.')[1][6:8])
hour = int(file.split('/')[-1].split('.')[1][8:10])
dt = int(file.split('/')[-1].split('.')[3][1:])
timestamp_hycom = mdates.date2num(datetime(year, month, day,
hour)) + dt / 24
time_hycom.append(mdates.num2date(timestamp_hycom))
# Interpolating latg and longlider into HYCOM grid
sublon_hycom = np.interp(timestamp_hycom, timestamp_glider, lon_glider)
sublat_hycom = np.interp(timestamp_hycom, timestamp_glider, lat_glider)
oklon_hycom = np.int(
np.round(
np.interp(sublon_hycom, lon_hycom[0, :],
np.arange(len(lon_hycom[0, :])))))
oklat_hycom = np.int(
np.round(
np.interp(sublat_hycom, lat_hycom[:, 0],
np.arange(len(lat_hycom[:, 0])))))
# Reading 3D variable from binary file
var_hycom = readBinz(file[:-2], '3z', var)
#ts=readBin(afile,'archive','temp')
target_var_hycom[:, x] = var_hycom[oklat_hycom, oklon_hycom, :]
time_hycom = np.asarray(time_hycom)
#timestamp_hycom = mdates.date2num(time_hycom)
return target_var_hycom, time_hycom
dt = int(file.split('.')[3][1:])
timestamp_HMON_HYCOM = date2num(datetime(year, month, day, hour)) + dt / 24
time_HMON_HYCOM.append(num2date(timestamp_HMON_HYCOM))
# Interpolating latg and longlider into RTOFS grid
#sublonHMON_HYCOM = np.interp(timestamp_HMON_HYCOM,timestampg,target_long)
#sublatHMON_HYCOM = np.interp(timestamp_HMON_HYCOM,timestampg,target_latg)
oklonHMON_HYCOM = np.int(
np.round(np.interp(target_lonG, hlon[0, :],
np.arange(len(hlon[0, :])))))
oklatHMON_HYCOM = np.int(
np.round(np.interp(target_latG, hlat[:, 0], np.arange(len(hlat[:,
0])))))
# Reading 3D variable from binary file
temp_HMON_HYCOM = readBinz(file[:-2], '3z', var_name)
#ts=readBin(afile,'archive','temp')
target_temp_HMON_HYCOM[x, :] = temp_HMON_HYCOM[oklatHMON_HYCOM,
oklonHMON_HYCOM, :]
time_HMON_HYCOM = np.asarray(time_HMON_HYCOM)
timestamp_HMON_HYCOM = date2num(time_HMON_HYCOM)
#%% Reading POM grid files
pom_grid = xr.open_dataset(ncfolder + grid_file)
lonc = np.asarray(pom_grid['east_e'][:])
latc = np.asarray(pom_grid['north_e'][:])
#lonu, latu = pom_grid['east_u'][:], pom_grid['north_u'][:]
#lonv, latv = pom_grid['east_v'][:], pom_grid['north_v'][:]
dt = int(file.split('.')[3][1:])
timestamp_RTOFS = date2num(datetime(year, month, day, hour)) + dt / 24
time_RTOFS.append(num2date(timestamp_RTOFS))
# Interpolating latg and longlider into RTOFS grid
sublonRTOFS = np.interp(timestamp_RTOFS, timestampg, target_long)
sublatRTOFS = np.interp(timestamp_RTOFS, timestampg, target_latg)
oklonRTOFS = np.int(
np.round(np.interp(sublonRTOFS, hlon[0, :],
np.arange(len(hlon[0, :])))))
oklatRTOFS = np.int(
np.round(np.interp(sublatRTOFS, hlat[:, 0], np.arange(len(hlat[:,
0])))))
# Reading 3D variable from binary file
temp_RTOFS = readBinz(file[:-2], '3z', var_name)
#ts=readBin(afile,'archive','temp')
target_temp_RTOFS[x, :] = temp_RTOFS[oklatRTOFS, oklonRTOFS, :]
# Extracting list of variables
#count=0
#for line in lines:
# count+=1
# if line[0:5] == 'field':
# break
#lines=lines[count:]
#vars=[line.split()[0] for line in lines]
time_RTOFS = np.asarray(time_RTOFS)
timestamp_RTOFS = date2num(time_RTOFS)
def HMON_HYCOM_fields(cycle,storm_id,lon_forec_track,lat_forec_track,lon_lim,lat_lim,temp_lim,salt_lim,temp200_lim,salt200_lim,tempb_lim,tempt_lim,folder_fig):
#%%
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
import os
import os.path
import glob
import cmocean
from matplotlib.dates import date2num, num2date
import xarray as xr
import sys
sys.path.append('/home/aristizabal/NCEP_scripts/')
from utils4HYCOM import readBinz,readgrids
#from utils4HYCOM import readdepth, readVar
#from utils4HYCOM2 import readBinz
# Increase fontsize of labels globally
plt.rc('xtick',labelsize=14)
plt.rc('ytick',labelsize=14)
plt.rc('legend',fontsize=14)
#%% Bathymetry file
bath_file = '/home/aristizabal/bathymetry_files/GEBCO_2014_2D_-100.0_0.0_-10.0_70.0.nc'
#%% Reading bathymetry data
ncbath = xr.open_dataset(bath_file)
bath_lat = ncbath.variables['lat'][:]
bath_lon = ncbath.variables['lon'][:]
bath_elev = ncbath.variables['elevation'][:]
oklatbath = np.logical_and(bath_lat >= lat_lim[0],bath_lat <= lat_lim[-1])
oklonbath = np.logical_and(bath_lon >= lon_lim[0],bath_lon <= lon_lim[-1])
bath_latsub = bath_lat[oklatbath]
bath_lonsub = bath_lon[oklonbath]
bath_elevs = bath_elev[oklatbath,:]
bath_elevsub = bath_elevs[:,oklonbath]
#%% folder and file names
ti = datetime.today() - timedelta(1)
folder_hmon_hycom = '/home/aristizabal/HMON_HYCOM_' + storm_id + '_' + str(ti.year) + '/' + 'HMON_HYCOM_' + storm_id + '_' + cycle + '/'
#%% Reading RTOFS grid
grid_file = sorted(glob.glob(os.path.join(folder_hmon_hycom,'*regional.grid.*')))[0][:-2]
#%% Reading RTOFS grid
print('Retrieving coordinates from RTOFS')
# Reading lat and lon
#lines_grid = [line.rstrip() for line in open(grid_file+'.b')]
lon_hycom = np.array(readgrids(grid_file,'plon:',[0]))
lat_hycom = np.array(readgrids(grid_file,'plat:',[0]))
#depth_HMON_HYCOM = np.asarray(readdepth(HMON_HYCOM_depth,'depth'))
# Reading depths
afiles = sorted(glob.glob(os.path.join(folder_hmon_hycom,'*hat10_3z'+'*.a')))
lines=[line.rstrip() for line in open(afiles[0][:-2]+'.b')]
z = []
for line in lines[6:]:
if line.split()[2]=='temp':
#print(line.split()[1])
z.append(float(line.split()[1]))
depth_HYCOM = np.asarray(z)
#%%
time_HYCOM = []
for x, file in enumerate(afiles):
print(x)
#lines=[line.rstrip() for line in open(file[:-2]+'.b')]
#Reading time stamp
year = int(file.split('/')[-1].split('.')[1][0:4])
month = int(file.split('/')[-1].split('.')[1][4:6])
day = int(file.split('/')[-1].split('.')[1][6:8])
hour = int(file.split('/')[-1].split('.')[1][8:10])
dt = int(file.split('/')[-1].split('.')[-2][1:])
timestamp_HYCOM = date2num(datetime(year,month,day,hour)) + dt/24
time_HYCOM.append(num2date(timestamp_HYCOM))
# Reading 3D variable from binary file
oktime = 0 # first file
temp_HMON_HYCOM = readBinz(afiles[oktime][:-2],'3z','temp')
salt_HMON_HYCOM = readBinz(afiles[oktime][:-2],'3z','salinity')
uvel_HMON_HYCOM = readBinz(afiles[oktime][:-2],'3z','u-veloc.')
vvel_HMON_HYCOM = readBinz(afiles[oktime][:-2],'3z','v-veloc.')
#%%
oklon_HYCOM = np.where(np.logical_and(lon_hycom[0,:] >= lon_lim[0]+360,lon_hycom[0,:] <= lon_lim[1]+360))[0]
oklat_HYCOM = np.where(np.logical_and(lat_hycom[:,0] >= lat_lim[0],lat_hycom[:,0] <= lat_lim[1]))[0]
lon_HYCOM =lon_hycom[0,oklon_HYCOM]-360
lat_HYCOM =lat_hycom[oklat_HYCOM,0]
sst_HYCOM = temp_HMON_HYCOM[oklat_HYCOM,:,0][:,oklon_HYCOM]
sss_HYCOM = salt_HMON_HYCOM[oklat_HYCOM,:,0][:,oklon_HYCOM]
su_HYCOM = uvel_HMON_HYCOM[oklat_HYCOM,:,0][:,oklon_HYCOM]
sv_HYCOM = vvel_HMON_HYCOM[oklat_HYCOM,:,0][:,oklon_HYCOM]
#okdepth200 = np.where(depth_HYCOM >= 200)[0][0]
#temp200_HYCOM = temp_HMON_HYCOM[oklat_HYCOM,:,okdepth200][:,oklon_HYCOM]
#salt200_HYCOM = salt_HMON_HYCOM[oklat_HYCOM,:,okdepth200][:,oklon_HYCOM]
#%% SST
kw = dict(levels = np.arange(temp_lim[0],temp_lim[1],0.5))
plt.figure()
plt.contour(bath_lonsub,bath_latsub,bath_elevsub,levels=[0],colors='k')
plt.contourf(bath_lonsub,bath_latsub,bath_elevsub,levels=[0,10000],colors='papayawhip',alpha=0.5)
plt.contourf(lon_HYCOM,lat_HYCOM,sst_HYCOM,cmap=cmocean.cm.thermal,**kw)
plt.plot(lon_forec_track,lat_forec_track,'.-',color='grey')
cbar = plt.colorbar()
cbar.ax.tick_params(labelsize=14)
cbar.ax.set_ylabel('($^\circ$C)',fontsize=14,labelpad=15)
plt.axis('scaled')
plt.xlim(lon_lim[0],lon_lim[1])
plt.ylim(lat_lim[0],lat_lim[1])
plt.title('HMON-HYCOM SST ' + 'Storm ' + storm_id + ' Cycle ' + cycle + '\n on '+str(time_HYCOM[oktime])[0:13],fontsize=16)
file_name = folder_fig + 'HMON_HYCOM_SST_' + cycle
plt.savefig(file_name,bbox_inches = 'tight',pad_inches = 0.1)
#%% SSS
kw = dict(levels = np.arange(salt_lim[0],salt_lim[1],0.5))
plt.figure()
plt.contour(bath_lonsub,bath_latsub,bath_elevsub,levels=[0],colors='k')
plt.contourf(bath_lonsub,bath_latsub,bath_elevsub,levels=[0,10000],colors='papayawhip',alpha=0.5)
plt.contourf(lon_HYCOM,lat_HYCOM,sss_HYCOM,cmap=cmocean.cm.haline,**kw)
plt.plot(lon_forec_track,lat_forec_track,'.-',color='grey')
cbar = plt.colorbar()
cbar.ax.tick_params(labelsize=14)
plt.axis('scaled')
plt.xlim(lon_lim[0],lon_lim[1])
plt.ylim(lat_lim[0],lat_lim[1])
plt.title('HMON-HYCOM SSS ' + 'Storm ' + storm_id + ' Cycle ' + cycle + '\n on '+str(time_HYCOM[oktime])[0:13],fontsize=16)
file_name = folder_fig + 'HMON_HYCOM_SSS_' + cycle
plt.savefig(file_name,bbox_inches = 'tight',pad_inches = 0.1)
#%% SST and velocity vectors
kw = dict(levels = np.arange(temp_lim[0],temp_lim[1],0.5))
plt.figure()
plt.contour(bath_lonsub,bath_latsub,bath_elevsub,levels=[0],colors='k')
plt.contourf(bath_lonsub,bath_latsub,bath_elevsub,levels=[0,10000],colors='papayawhip',alpha=0.5)
plt.contourf(lon_HYCOM,lat_HYCOM,sst_HYCOM,cmap=cmocean.cm.thermal,**kw)
cbar = plt.colorbar()
cbar.ax.tick_params(labelsize=14)
cbar.ax.set_ylabel('($^\circ$C)',fontsize=14,labelpad=15)
plt.axis('scaled')
plt.xlim(lon_lim[0],lon_lim[1])
plt.ylim(lat_lim[0],lat_lim[1])
plt.title('HMON-HYCOM SST ' + 'Storm ' + storm_id + ' Cycle ' + cycle + '\n on '+str(time_HYCOM[oktime])[0:13],fontsize=16)
q = plt.quiver(lon_HYCOM[::10], lat_HYCOM[::10],su_HYCOM[::10,::10],sv_HYCOM[::10,::10])
#plt.quiverkey(q,np.min(lon_HYCOM)-5,np.max(lat_HYCOM)-5,1,"1 m/s",coordinates='data',color='k',fontproperties={'size': 14})
file_name = folder_fig + 'HMON_HYCOM_SST_UV_' + cycle
plt.savefig(file_name,bbox_inches = 'tight',pad_inches = 0.1)
#%% Figure temp transect along storm path
lat_forec_tracku, ind = np.unique(lat_forec_track,return_index=True)
lon_forec_tracku = lon_forec_track[ind]
lon_forec_track_interp = np.interp(lat_hycom[:,0],lat_forec_tracku,lon_forec_tracku,left=np.nan,right=np.nan)
lat_forec_track_interp = np.copy(lat_hycom[:,0])
lat_forec_track_interp[np.isnan(lon_forec_track_interp)] = np.nan
lon_forec_track_int = lon_forec_track_interp[np.isfinite(lon_forec_track_interp)]
lat_forec_track_int = lat_forec_track_interp[np.isfinite(lat_forec_track_interp)]
oklon = np.round(np.interp(lon_forec_track_int,lon_hycom[0,:]-360,np.arange(len(lon_hycom[0,:])))).astype(int)
oklat = np.round(np.interp(lat_forec_track_int,lat_hycom[:,0],np.arange(len(lat_hycom[:,0])))).astype(int)
trans_temp_HYCOM = temp_HMON_HYCOM[oklat,oklon,:]
kw = dict(levels = np.arange(tempt_lim[0],tempt_lim[1],1))
plt.figure()
plt.contourf(lat_hycom[oklat,0],-depth_HYCOM,trans_temp_HYCOM.T,cmap=cmocean.cm.thermal,**kw)
cbar = plt.colorbar()
cbar.ax.tick_params(labelsize=16)
plt.contour(lat_hycom[oklat,0],-depth_HYCOM,trans_temp_HYCOM.T,[26],color='k')
cbar.ax.set_ylabel('($^\circ$C)',fontsize=14)
cbar.ax.tick_params(labelsize=14)
plt.ylabel('Depth (m)',fontsize=14)
plt.xlabel('Latitude ($^o$)',fontsize=14)
plt.title('HMON-HYCOM Temperature ' + 'Storm ' + storm_id + ' Cycle ' + cycle + '\n along Forecasted Storm Track',fontsize=16)
plt.ylim([-300,0])
file = folder_fig + 'HMON_HYCOM_temp_along_forecasted_track_' + cycle
plt.savefig(file,bbox_inches = 'tight',pad_inches = 0.1)
plt.axis('scaled')
plt.ylim([ylim[0],ylim[1]])
plt.xlim([xlim[0],xlim[1]])
#%% Surface temperature HYCOM experimental
folder_hycom =folder_hycom_exp
prefix = prefix_hycom
N = 0
var = 'temp'
afiles = sorted(glob.glob(os.path.join(folder_hycom,prefix+'*.a')))
file = afiles[N]
# Reading 3D variable from binary file
var_hyc = readBinz(file[:-2],'3z',var)
temp_HYCOM = var_hyc[:,:,0]
#Reading time stamp
year = int(file.split('/')[-1].split('.')[1][0:4])
month = int(file.split('/')[-1].split('.')[1][4:6])
day = int(file.split('/')[-1].split('.')[1][6:8])
hour = int(file.split('/')[-1].split('.')[1][8:10])
dt = int(file.split('/')[-1].split('.')[3][1:])
timestamp_hycom = mdates.date2num(datetime(year,month,day,hour)) + dt/24
time_hycom = mdates.num2date(timestamp_hycom)
kw = dict(levels = np.linspace(28,30,41))
#fig,ax = plt.subplots(figsize=(5,5))
plt.figure()
plt.contourf(lon_hycom[0,:]-360,lat_hycom[:,0],temp_HYCOM,cmap=cmocean.cm.thermal,**kw)
time_HMON_HYCOM.append(num2date(timestamp_HMON_HYCOM))
# Interpolating latg and longlider into RTOFS grid
sublonHMON_HYCOM = np.interp(timestamp_HMON_HYCOM, timestampg, long + 360)
sublatHMON_HYCOM = np.interp(timestamp_HMON_HYCOM, timestampg, latg)
oklonHMON_HYCOM = np.int(
np.round(
np.interp(sublonHMON_HYCOM, lon_hycom[0, :],
np.arange(len(lon_hycom[0, :])))))
oklatHMON_HYCOM = np.int(
np.round(
np.interp(sublatHMON_HYCOM, lat_hycom[:, 0],
np.arange(len(lat_hycom[:, 0])))))
# Reading 3D variable from binary file
temp_HMON_HYCOM = readBinz(file[:-2], '3z', 'temp')
#ts=readBin(afile,'archive','temp')
target_temp_HMON_HYCOM[x, :] = temp_HMON_HYCOM[oklatHMON_HYCOM,
oklonHMON_HYCOM, :]
# Extracting list of variables
#count=0
#for line in lines:
# count+=1
# if line[0:5] == 'field':
# break
#lines=lines[count:]
#vars=[line.split()[0] for line in lines]
time_HMON_HYCOM = np.asarray(time_HMON_HYCOM)
#%%
N = 0
var = 'temp'
afiles = sorted(
glob.glob(os.path.join(folder_RTOFS_DA, prefix_RTOFS_DA + '*.a')))
file = afiles[N]
lines = [line.rstrip() for line in open(file[:-2] + '.b')]
time_stamp = lines[-1].split()[2]
hycom_days = lines[-1].split()[3]
tzero = datetime(1901, 1, 1, 0, 0)
time_RTOFS_DA = tzero + timedelta(float(hycom_days) - 1)
# Reading 3D variable from binary file
var_rtofs = readBinz(file[:-2], '3z', var)
#%%
oklon = np.where(
np.logical_and(lon_RTOFS_DA[0, :] >= lon_lim[0] + 360,
lon_RTOFS_DA[0, :] <= lon_lim[1] + 360))[0]
oklat = np.where(
np.logical_and(lat_RTOFS_DA[:, 0] >= lat_lim[0],
lat_RTOFS_DA[:, 0] <= lat_lim[1]))[0]
temp_RTOFS_DA = np.asarray(var_rtofs[oklat, :, 0][:, oklon])
m = Basemap(projection='merc',
llcrnrlat=15,
urcrnrlat=32.5,
time_HMON_HYCOM.append(num2date(timestamp_HMON_HYCOM))
# Interpolating latg and longlider into RTOFS grid
sublonHMON_HYCOM = np.interp(timestamp_HMON_HYCOM, timestampg, target_long)
sublatHMON_HYCOM = np.interp(timestamp_HMON_HYCOM, timestampg, target_latg)
oklonHMON_HYCOM = np.int(
np.round(
np.interp(sublonHMON_HYCOM, hlon[0, :],
np.arange(len(hlon[0, :])))))
oklatHMON_HYCOM = np.int(
np.round(
np.interp(sublatHMON_HYCOM, hlat[:, 0], np.arange(len(hlat[:,
0])))))
# Reading 3D variable from binary file
temp_HMON_HYCOM = readBinz(file[:-2], '3z', var_name)
#ts=readBin(afile,'archive','temp')
target_temp_HMON_HYCOM[x, :] = temp_HMON_HYCOM[oklatHMON_HYCOM,
oklonHMON_HYCOM, :]
# Extracting list of variables
#count=0
#for line in lines:
# count+=1
# if line[0:5] == 'field':
# break
#lines=lines[count:]
#vars=[line.split()[0] for line in lines]
time_HMON_HYCOM = np.asarray(time_HMON_HYCOM)
# Read HYCOM exp
file = afiles[n]
#Reading time stamp
year = int(file.split('/')[-1].split('.')[1][0:4])
month = int(file.split('/')[-1].split('.')[1][4:6])
day = int(file.split('/')[-1].split('.')[1][6:8])
hour = int(file.split('/')[-1].split('.')[1][8:10])
dt = int(file.split('/')[-1].split('.')[3][1:])
timestamp_hycom = mdates.date2num(datetime(year, month, day,
hour)) + dt / 24
time_hycom_exp.append(datetime(year, month, day, hour))
# Reading 3D variable from binary file
temp_hycom = np.asarray(readBinz(file[:-2], '3z', 'temp'))
temp_hycom[temp_hycom > 100] = np.nan
salt_hycom = np.asarray(readBinz(file[:-2], '3z', 'salinity'))
salt_hycom[salt_hycom > 100] = np.nan
oklon_hycom = np.where(
np.logical_and(lon_hycom[0, :] - 360 > xlim[0],
lon_hycom[0, :] - 360 < xlim[1]))[0]
oklat_hycom = np.where(
np.logical_and(lat_hycom[:, 0] > ylim[0],
lat_hycom[:, 0] < ylim[1]))[0]
meshlon_lat_hycom = np.meshgrid(lon_hycom[0, oklon_hycom],
lat_hycom[oklat_hycom, 0])
lat_lon_matrix_hycom = np.stack(
time_HYCOM = []
for x, file in enumerate(afiles):
print(x)
lines = [line.rstrip() for line in open(file[:-2] + '.b')]
#Reading time stamp
year = int(file.split('.')[1][0:4])
month = int(file.split('.')[1][4:6])
day = int(file.split('.')[1][6:8])
hour = int(file.split('.')[1][8:10])
dt = int(file.split('.')[3][1:])
timestamp_HYCOM = date2num(datetime(year, month, day, hour)) + dt / 24
time_HYCOM.append(num2date(timestamp_HYCOM))
# Reading 3D variable from binary file
temp_HYCOM = readBinz(file[:-2], '3z', 'temp')
sst_HYCOM[x, :, :] = temp_HYCOM[botm:top, left:right, 0]
u_HYCOM = readBinz(file[:-2], '3z', 'u-veloc.')
su_HYCOM[x, :, :] = u_HYCOM[botm:top, left:right, 0]
v_HYCOM = readBinz(file[:-2], '3z', 'v-veloc.')
sv_HYCOM[x, :, :] = v_HYCOM[botm:top, left:right, 0]
time_HYCOM = np.asarray(time_HYCOM)
timestamp_HYCOM = date2num(time_HYCOM)
#%% Reading bathymetry data
ncbath = xr.open_dataset(bath_file)
bath_lat = ncbath.variables['lat'][:]