Comparisons between nowcast, spinup, and observed salinity in the Strait of Georgia
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import ACTDR
import netCDF4 as nc
from salishsea_tools import viz_tools
import numpy as np
import comparisons
%matplotlib inline
sns.set_style('darkgrid')
grid_B = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')
ACTDR.load_dat('SOG_2000.dat')
> open SOG_2000.dat > load CTD_DAT > load STANDARD_KEYS > close SOG_2000.dat > complete
data = pd.DataFrame(ACTDR.CTD_DAT)
lon_min=-123.5; lat_min=49;
lon_max=-123.2; lat_max=49.2;
data_region = comparisons.isolate_region(data, lon_min, lon_max, lat_min, lat_max)
fig,axm = plt.subplots(1,figsize=(5,5))
data_region.plot(x='Longitude',y='Latitude',kind='scatter', marker='o',ax=axm)
viz_tools.plot_coastline(axm,grid_B,coords='map')
axm.set_xlim([-124.1,-122.5])
axm.set_ylim([48.4,49.5])
(48.4, 49.5)
data_region.hist('Month',bins=np.arange(0.5,13.5))
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f63b42a0390>]], dtype=object)
data_region.hist('Year', bins= np.arange(data_region['Year'].min()-0.5, data_region['Year'].max() +1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
paths = {'nowcast': '/data/dlatorne/MEOPAR/SalishSea/nowcast/',
'spinup': '/ocean/dlatorne/MEOPAR/SalishSea/results/spin-up/'}
zmax=20
November
month=11
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],zmax=zmax)
fig=comparisons.compare_model_obs(month,2014,'Salinity',data_region,paths['nowcast'],zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
December
month=12
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],zmax=zmax)
fig=comparisons.compare_model_obs(month,2014,'Salinity',data_region,paths['nowcast'],zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
January
month=1
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
February
month=2
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
March
month=3
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
April
month=4
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],vmin=0,zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],vmin=0,zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
May
month=5
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],vmin=0,zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],vmin=0,zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
June
month=6
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],vmin=0,zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],vmin=0,zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
July
month=7
fig=comparisons.compare_model_obs(month,2003,'Salinity',data_region,paths['spinup'],vmin=0,zmax=zmax)
fig=comparisons.compare_model_obs(month,2015,'Salinity',data_region,paths['nowcast'],vmin=0,zmax=zmax)
data_month=data_region[data_region['Month']==month]
data_month.hist('Year',bins = np.arange(data_month['Year'].min()-0.5,data_month['Year'].max()+1.5 ))
ax=plt.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
data_2014 = data_region[data_region['Year']==2014]
data_2014.hist('Month')
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f63aea3c190>]], dtype=object)