Notebook

In [1]:

import netCDF4 as nc
import datetime as dt
import subprocess
import requests
import matplotlib.pyplot as plt
import cmocean
import numpy as np
import os
import glob
import dateutil as dutil
from salishsea_tools import viz_tools
import pickle
%matplotlib inline

In [2]:

recalc=True #False

In [3]:

t0=dt.datetime(2014,11,15) # 1st start date of run
if recalc:
    with nc.Dataset('/ocean/eolson/MEOPAR/NEMO-forcing/grid/mesh_mask201702_noLPE.nc') as fm:
        tmask=np.copy(fm.variables['tmask'])
        umask=np.copy(fm.variables['umask'])
        vmask=np.copy(fm.variables['vmask'])
        navlon=np.copy(fm.variables['nav_lon'])
        navlat=np.copy(fm.variables['nav_lat'])
        e3t_0=np.copy(fm.variables['e3t_0'])
        e3u_0=np.copy(fm.variables['e3u_0'])
        e3v_0=np.copy(fm.variables['e3v_0'])
        e1t=np.copy(fm.variables['e1t'])
        e2t=np.copy(fm.variables['e2t'])
        e1v=np.copy(fm.variables['e1v'])
        e2u=np.copy(fm.variables['e2u'])
        A=fm.variables['e1t'][0,:,:]*fm.variables['e2t'][0,:,:]*tmask[0,0,:,:]


    #te=dt.datetime(2016,12,1)# last start date of runfnum=18
    stm=np.shape(tmask)
    SiN=2.0
    #nlen=36*2
    nlen=36#100
    dlist=[t0+dt.timedelta(days=ii*10) for ii in range(0,nlen)]

    #sdir0='/results/SalishSea/nowcast-green/'
    sdir1='/results/SalishSea/spinup_v201812/'
    #sdir3='/data/eolson/MEOPAR/SS36runs/CedarRuns/spring2015_HCMZ/'

    tmaskC=np.copy(tmask)
    tmaskC[:,:,370:490,:12]=0
    tmaskC[:,:,887:,30:70]=0

In [4]:

if recalc:
    tlist=dlist
    SiGlobalTot=dict()
    SiTot=dict()
    BSiTot=dict()
    DiatTot=dict()
    changeSiGlobalTot=dict()
    for idir in (sdir1,):
        fformat1='%d%b%y/'
        if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):
            fformatT='SalishSea_1d_*_ptrc_T_%Y%m%d-*.nc'
            fformatP='SalishSea_1d_*_ptrc_T_%Y%m%d-*.nc'
        #elif idir==sdir0:
        #    fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'
        #    fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_grid_T.nc'
        elif idir==sdir1:
            fformatT='SalishSea_1d_%Y%m%d_%Y%m%d_ptrc_T.nc'
            fformatP='SalishSea_1d_%Y%m%d_%Y%m%d_carp_T.nc'
        sumSi=np.zeros((len(tlist),stm[2],stm[3]))
        sumBSi=np.zeros((len(tlist),stm[2],stm[3]))
        sumDiat=np.zeros((len(tlist),stm[2],stm[3]))
        ind=-1
        for idt0 in tlist:
            ind=ind+1
            cdir=idt0.strftime(fformat1).lower()
            iffT=idt0.strftime(fformatT)
            iffP=idt0.strftime(fformatP)
            if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):
                sffT=idir+iffT
                sffP=idir+iffP
            elif idir.startswith('/results/') or idir.startswith('/results2/'):
                sffT=idir+cdir+iffT
                sffP=idir+cdir+iffP
            print(sffT)
            f=nc.Dataset(glob.glob(sffT)[0])
            fP=nc.Dataset(glob.glob(sffP)[0])
            #if idir==sdir0:
            #    e3t=np.expand_dims((1+fP.variables['sossheig'][0,:,:]/np.sum(e3t_0*tmask,1)),0)*e3t_0
            if idir==sdir1:
                e3t=fP.variables['e3t'][:2,:,:,:]
            Vol=A*e3t
            sumSi[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['silicon'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumBSi[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['biogenic_silicon'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumDiat[ind,:,:]=SiN*1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['diatoms'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            f.close()
            fP.close()
        SiGlobalTot[idir]=np.sum(np.sum(sumSi+sumBSi+sumDiat,2),1)
        SiTot[idir]=np.sum(np.sum(sumSi,2),1)
        BSiTot[idir]=np.sum(np.sum(sumBSi,2),1)
        DiatTot[idir]=np.sum(np.sum(sumDiat,2),1)
        changeSiGlobalTot[idir]=[SiGlobalTot[idir][ii+1]-SiGlobalTot[idir][ii] for ii in range(0,len(tlist)-1)]

/results/SalishSea/spinup_v201812/15nov14/SalishSea_1d_20141115_20141115_ptrc_T.nc
/results/SalishSea/spinup_v201812/25nov14/SalishSea_1d_20141125_20141125_ptrc_T.nc
/results/SalishSea/spinup_v201812/05dec14/SalishSea_1d_20141205_20141205_ptrc_T.nc
/results/SalishSea/spinup_v201812/15dec14/SalishSea_1d_20141215_20141215_ptrc_T.nc
/results/SalishSea/spinup_v201812/25dec14/SalishSea_1d_20141225_20141225_ptrc_T.nc
/results/SalishSea/spinup_v201812/04jan15/SalishSea_1d_20150104_20150104_ptrc_T.nc
/results/SalishSea/spinup_v201812/14jan15/SalishSea_1d_20150114_20150114_ptrc_T.nc
/results/SalishSea/spinup_v201812/24jan15/SalishSea_1d_20150124_20150124_ptrc_T.nc
/results/SalishSea/spinup_v201812/03feb15/SalishSea_1d_20150203_20150203_ptrc_T.nc
/results/SalishSea/spinup_v201812/13feb15/SalishSea_1d_20150213_20150213_ptrc_T.nc
/results/SalishSea/spinup_v201812/23feb15/SalishSea_1d_20150223_20150223_ptrc_T.nc
/results/SalishSea/spinup_v201812/05mar15/SalishSea_1d_20150305_20150305_ptrc_T.nc
/results/SalishSea/spinup_v201812/15mar15/SalishSea_1d_20150315_20150315_ptrc_T.nc
/results/SalishSea/spinup_v201812/25mar15/SalishSea_1d_20150325_20150325_ptrc_T.nc
/results/SalishSea/spinup_v201812/04apr15/SalishSea_1d_20150404_20150404_ptrc_T.nc
/results/SalishSea/spinup_v201812/14apr15/SalishSea_1d_20150414_20150414_ptrc_T.nc
/results/SalishSea/spinup_v201812/24apr15/SalishSea_1d_20150424_20150424_ptrc_T.nc
/results/SalishSea/spinup_v201812/04may15/SalishSea_1d_20150504_20150504_ptrc_T.nc
/results/SalishSea/spinup_v201812/14may15/SalishSea_1d_20150514_20150514_ptrc_T.nc
/results/SalishSea/spinup_v201812/24may15/SalishSea_1d_20150524_20150524_ptrc_T.nc
/results/SalishSea/spinup_v201812/03jun15/SalishSea_1d_20150603_20150603_ptrc_T.nc
/results/SalishSea/spinup_v201812/13jun15/SalishSea_1d_20150613_20150613_ptrc_T.nc
/results/SalishSea/spinup_v201812/23jun15/SalishSea_1d_20150623_20150623_ptrc_T.nc
/results/SalishSea/spinup_v201812/03jul15/SalishSea_1d_20150703_20150703_ptrc_T.nc
/results/SalishSea/spinup_v201812/13jul15/SalishSea_1d_20150713_20150713_ptrc_T.nc
/results/SalishSea/spinup_v201812/23jul15/SalishSea_1d_20150723_20150723_ptrc_T.nc
/results/SalishSea/spinup_v201812/02aug15/SalishSea_1d_20150802_20150802_ptrc_T.nc
/results/SalishSea/spinup_v201812/12aug15/SalishSea_1d_20150812_20150812_ptrc_T.nc
/results/SalishSea/spinup_v201812/22aug15/SalishSea_1d_20150822_20150822_ptrc_T.nc
/results/SalishSea/spinup_v201812/01sep15/SalishSea_1d_20150901_20150901_ptrc_T.nc
/results/SalishSea/spinup_v201812/11sep15/SalishSea_1d_20150911_20150911_ptrc_T.nc
/results/SalishSea/spinup_v201812/21sep15/SalishSea_1d_20150921_20150921_ptrc_T.nc
/results/SalishSea/spinup_v201812/01oct15/SalishSea_1d_20151001_20151001_ptrc_T.nc
/results/SalishSea/spinup_v201812/11oct15/SalishSea_1d_20151011_20151011_ptrc_T.nc
/results/SalishSea/spinup_v201812/21oct15/SalishSea_1d_20151021_20151021_ptrc_T.nc
/results/SalishSea/spinup_v201812/31oct15/SalishSea_1d_20151031_20151031_ptrc_T.nc

In [5]:

#test=np.sum(np.sum((sumSi[-1,:,:]+np.sum(1e-3*7*tmaskC[0,:,:,:]*Vol[0,:,:,:],0))+sumBSi[-1,:,:]+sumDiat[-1,:,:],1),0)
#test2=np.sum(np.sum(sumSi[-1,:,:]+sumBSi[-1,:,:]+sumDiat[-1,:,:],1),0)

In [6]:

if recalc:
    fig,ax=plt.subplots(1,1,figsize=(6,5))
    ax.plot(SiGlobalTot[sdir1]-SiGlobalTot[sdir1][0],'b-')
    ax.set_xlabel('10-day intervals since '+t0.strftime('%b $d $Y'))
    ax.set_ylabel('Difference in Total Si')

In [7]:

# copy restart and add 7 to Si old and new

repeat for N¶

In [8]:

if recalc:
    tlist=dlist
    NGlobalTot=dict()
    VolTot=dict()
    NO3Tot=dict()
    NH4Tot=dict()
    PONTot=dict()
    DONTot=dict()
    DiatTot=dict()
    MyriTot=dict()
    NanoTot=dict()
    MiZoTot=dict()
    changeNGlobalTot=dict()
    for idir in (sdir1,):
        fformat1='%d%b%y/'
        if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):
            fformatT='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'
            fformatP='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'
        #elif idir==sdir0:
        #    fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'
        #    fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_grid_T.nc'
        elif idir==sdir1:
            fformatT='SalishSea_1d_%Y%m%d_%Y%m%d_ptrc_T.nc'
            fformatP='SalishSea_1d_%Y%m%d_%Y%m%d_carp_T.nc'
        sumNO3=np.zeros((len(tlist),stm[2],stm[3]))
        sumVol=np.zeros((len(tlist),stm[2],stm[3]))
        sumNH4=np.zeros((len(tlist),stm[2],stm[3]))
        sumPON=np.zeros((len(tlist),stm[2],stm[3]))
        sumDON=np.zeros((len(tlist),stm[2],stm[3]))
        sumDiat=np.zeros((len(tlist),stm[2],stm[3]))
        sumMyri=np.zeros((len(tlist),stm[2],stm[3]))
        sumNano=np.zeros((len(tlist),stm[2],stm[3]))
        sumMiZo=np.zeros((len(tlist),stm[2],stm[3]))
        ind=-1
        for idt0 in tlist:
            ind=ind+1
            cdir=idt0.strftime(fformat1).lower()
            iffT=idt0.strftime(fformatT)
            iffP=idt0.strftime(fformatP)
            if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):
                sffT=idir+iffT
                sffP=idir+iffP
            elif idir.startswith('/results/') or idir.startswith('/results2/'):
                sffT=idir+cdir+iffT
                sffP=idir+cdir+iffP
            print(sffT)
            f=nc.Dataset(glob.glob(sffT)[0])
            fP=nc.Dataset(glob.glob(sffP)[0])
            #if idir==sdir0:
            #    e3t=np.expand_dims((1+fP.variables['sossheig'][0,:,:]/np.sum(e3t_0*tmask,1)),0)*e3t_0
            if idir==sdir1:
                e3t=fP.variables['e3t'][:2,:,:,:]
            Vol=A*e3t
            sumVol[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumNO3[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['nitrate'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumNH4[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['ammonium'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumPON[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['particulate_organic_nitrogen'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumDON[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['dissolved_organic_nitrogen'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumDiat[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['diatoms'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumMyri[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['ciliates'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            sumMiZo[ind,:,:]=1e-3*np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['microzooplankton'][0,:,:,:],0) #mmol/m3*m3*10^-3=mol
            f.close()
            fP.close()
        NGlobalTot[idir]=np.sum(np.sum(sumNO3+sumNH4+sumPON+sumDON+sumDiat+sumMyri+sumNano+sumMiZo,2),1)
        VolTot[idir]=np.sum(np.sum(sumVol,2),1)
        NO3Tot[idir]=np.sum(np.sum(sumNO3,2),1)
        NH4Tot[idir]=np.sum(np.sum(sumNH4,2),1)
        PONTot[idir]=np.sum(np.sum(sumPON,2),1)
        DONTot[idir]=np.sum(np.sum(sumDON,2),1)
        DiatTot[idir]=np.sum(np.sum(sumDiat,2),1)
        MyriTot[idir]=np.sum(np.sum(sumMyri,2),1)
        NanoTot[idir]=np.sum(np.sum(sumNano,2),1)
        MiZoTot[idir]=np.sum(np.sum(sumMiZo,2),1)
        changeNGlobalTot[idir]=[NGlobalTot[idir][ii+1]-NGlobalTot[idir][ii] for ii in range(0,len(tlist)-1)]

/results/SalishSea/spinup_v201812/15nov14/SalishSea_1d_20141115_20141115_ptrc_T.nc
/results/SalishSea/spinup_v201812/25nov14/SalishSea_1d_20141125_20141125_ptrc_T.nc
/results/SalishSea/spinup_v201812/05dec14/SalishSea_1d_20141205_20141205_ptrc_T.nc
/results/SalishSea/spinup_v201812/15dec14/SalishSea_1d_20141215_20141215_ptrc_T.nc
/results/SalishSea/spinup_v201812/25dec14/SalishSea_1d_20141225_20141225_ptrc_T.nc
/results/SalishSea/spinup_v201812/04jan15/SalishSea_1d_20150104_20150104_ptrc_T.nc
/results/SalishSea/spinup_v201812/14jan15/SalishSea_1d_20150114_20150114_ptrc_T.nc
/results/SalishSea/spinup_v201812/24jan15/SalishSea_1d_20150124_20150124_ptrc_T.nc
/results/SalishSea/spinup_v201812/03feb15/SalishSea_1d_20150203_20150203_ptrc_T.nc
/results/SalishSea/spinup_v201812/13feb15/SalishSea_1d_20150213_20150213_ptrc_T.nc
/results/SalishSea/spinup_v201812/23feb15/SalishSea_1d_20150223_20150223_ptrc_T.nc
/results/SalishSea/spinup_v201812/05mar15/SalishSea_1d_20150305_20150305_ptrc_T.nc
/results/SalishSea/spinup_v201812/15mar15/SalishSea_1d_20150315_20150315_ptrc_T.nc
/results/SalishSea/spinup_v201812/25mar15/SalishSea_1d_20150325_20150325_ptrc_T.nc
/results/SalishSea/spinup_v201812/04apr15/SalishSea_1d_20150404_20150404_ptrc_T.nc
/results/SalishSea/spinup_v201812/14apr15/SalishSea_1d_20150414_20150414_ptrc_T.nc
/results/SalishSea/spinup_v201812/24apr15/SalishSea_1d_20150424_20150424_ptrc_T.nc
/results/SalishSea/spinup_v201812/04may15/SalishSea_1d_20150504_20150504_ptrc_T.nc
/results/SalishSea/spinup_v201812/14may15/SalishSea_1d_20150514_20150514_ptrc_T.nc
/results/SalishSea/spinup_v201812/24may15/SalishSea_1d_20150524_20150524_ptrc_T.nc
/results/SalishSea/spinup_v201812/03jun15/SalishSea_1d_20150603_20150603_ptrc_T.nc
/results/SalishSea/spinup_v201812/13jun15/SalishSea_1d_20150613_20150613_ptrc_T.nc
/results/SalishSea/spinup_v201812/23jun15/SalishSea_1d_20150623_20150623_ptrc_T.nc
/results/SalishSea/spinup_v201812/03jul15/SalishSea_1d_20150703_20150703_ptrc_T.nc
/results/SalishSea/spinup_v201812/13jul15/SalishSea_1d_20150713_20150713_ptrc_T.nc
/results/SalishSea/spinup_v201812/23jul15/SalishSea_1d_20150723_20150723_ptrc_T.nc
/results/SalishSea/spinup_v201812/02aug15/SalishSea_1d_20150802_20150802_ptrc_T.nc
/results/SalishSea/spinup_v201812/12aug15/SalishSea_1d_20150812_20150812_ptrc_T.nc
/results/SalishSea/spinup_v201812/22aug15/SalishSea_1d_20150822_20150822_ptrc_T.nc
/results/SalishSea/spinup_v201812/01sep15/SalishSea_1d_20150901_20150901_ptrc_T.nc
/results/SalishSea/spinup_v201812/11sep15/SalishSea_1d_20150911_20150911_ptrc_T.nc
/results/SalishSea/spinup_v201812/21sep15/SalishSea_1d_20150921_20150921_ptrc_T.nc
/results/SalishSea/spinup_v201812/01oct15/SalishSea_1d_20151001_20151001_ptrc_T.nc
/results/SalishSea/spinup_v201812/11oct15/SalishSea_1d_20151011_20151011_ptrc_T.nc
/results/SalishSea/spinup_v201812/21oct15/SalishSea_1d_20151021_20151021_ptrc_T.nc
/results/SalishSea/spinup_v201812/31oct15/SalishSea_1d_20151031_20151031_ptrc_T.nc

In [9]:

if recalc:
    #plt.plot(SiGlobalTot[sdir0]-SiGlobalTot[sdir0][0],'r-')
    #plt.plot(SiGlobalTot[sdir3]-SiGlobalTot[sdir3][0],'g-')
    #plt.plot(40,test-SiGlobalTot[sdir1][0],'r*')
    #plt.plot(40,test2-SiGlobalTot[sdir1][0],'k*')
    fig,ax=plt.subplots(1,1,figsize=(6,5))
    ax.plot(NGlobalTot[sdir1]-NGlobalTot[sdir1][0],'r-')
    ax.set_xlabel('10-day intervals since '+t0.strftime('%b $d $Y'))
    ax.set_ylabel('Difference in Total N')

In [10]:

if recalc:
    plt.plot(SiGlobalTot[sdir1]-SiGlobalTot[sdir1][0],'b-')
    plt.plot(NGlobalTot[sdir1]-NGlobalTot[sdir1][0],'r-')

In [11]:

if recalc:
    pickle.dump(SiGlobalTot[sdir1],open('SiGlobalTot_HCspinup.pkl','wb'))
    pickle.dump(NGlobalTot[sdir1],open('NGlobalTot_HCspinup.pkl','wb'))

In [12]:

SiGlobalTotHC=pickle.load(open('SiGlobalTot_HCspinup.pkl','rb'))
NGlobalTotHC=pickle.load(open('NGlobalTot_HCspinup.pkl','rb'))

In [13]:

SiGlobalTotHCold=pickle.load(open('SiGlobalTot_HC.pkl','rb'))
NGlobalTotHCold=pickle.load(open('NGlobalTot_HC.pkl','rb'))

In [14]:

#SiGlobalTotT3=pickle.load(open('SiGlobalTotT3.pkl','rb'))
#NGlobalTotT3=pickle.load(open('NGlobalTotT3.pkl','rb'))

In [15]:

#SiGlobalTotZ1=pickle.load(open('SiGlobalTotZ1.pkl','rb'))
#NGlobalTotZ1=pickle.load(open('NGlobalTotZ1.pkl','rb'))

In [16]:

#tit='spring2015_Z3'
#SiGlobalTotZ3=pickle.load(open('SiGlobalTot_'+tit+'.pkl','rb'))
#NGlobalTotZ3=pickle.load(open('NGlobalTot_'+tit+'.pkl','rb'))

In [17]:

bdir='/data/eolson/MEOPAR/SS36runs/CedarRuns/'

In [18]:

tit='spring15spun_Ztest'
SiGlobalTotZtest=pickle.load(open(bdir+tit+'/SiGlobalTot_'+tit+'.pkl','rb'))
NGlobalTotZtest=pickle.load(open(bdir+tit+'/NGlobalTot_'+tit+'.pkl','rb'))

In [19]:

tit='spring15spun_Z4'
SiGlobalTotZ4=pickle.load(open(bdir+tit+'/SiGlobalTot_'+tit+'.pkl','rb'))
NGlobalTotZ4=pickle.load(open(bdir+tit+'/NGlobalTot_'+tit+'.pkl','rb'))

In [20]:

tit='spring15spun_Z5'
SiGlobalTotZ5=pickle.load(open(bdir+tit+'/SiGlobalTot_'+tit+'.pkl','rb'))
NGlobalTotZ5=pickle.load(open(bdir+tit+'/NGlobalTot_'+tit+'.pkl','rb'))

In [21]:

tit='spring16spun_Z6'
SiGlobalTotZ6=pickle.load(open(bdir+tit+'/SiGlobalTot_'+tit+'.pkl','rb'))
NGlobalTotZ6=pickle.load(open(bdir+tit+'/NGlobalTot_'+tit+'.pkl','rb'))

In [22]:

tit='spring16spun_Z7'
SiGlobalTotZ7=pickle.load(open(bdir+tit+'/SiGlobalTot_'+tit+'.pkl','rb'))
NGlobalTotZ7=pickle.load(open(bdir+tit+'/NGlobalTot_'+tit+'.pkl','rb'))

In [23]:

fig,ax=plt.subplots(1,1,figsize=(8,16))
plt.plot([t0+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotHC))],SiGlobalTotHC,'y-')
plt.plot([t0+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotHC))],NGlobalTotHC,'y-')
plt.plot([t0+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotHCold))],SiGlobalTotHCold,'r--')
plt.plot([t0+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotHCold))],NGlobalTotHCold,'r--')
plt.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ4))],SiGlobalTotZ4,'c--')
plt.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ4))],NGlobalTotZ4,'c--')

ax.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ5))],SiGlobalTotZ5,'m:')
ax.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ5))],NGlobalTotZ5,'m:')
ax.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZtest))],SiGlobalTotZtest,'b:')
ax.plot([dt.datetime(2015,1,11)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZtest))],NGlobalTotZtest,'b:')

ax.plot([dt.datetime(2016,1,6)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ6))],SiGlobalTotZ6,'r:')
ax.plot([dt.datetime(2016,1,6)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ6))],NGlobalTotZ6,'r:')
ax.plot([dt.datetime(2016,1,6)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ7))],SiGlobalTotZ7,'g:')
ax.plot([dt.datetime(2016,1,6)+dt.timedelta(10*ii) for ii in range(0,len(SiGlobalTotZ7))],NGlobalTotZ7,'g:')

Out[23]:

[<matplotlib.lines.Line2D at 0x7fb53ede1278>]

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