Time Series of Phytoplankton Bloom Timing and Environmental Drivers from 2007-2020 at Station S3 (201905 model run)¶
To run this notebook, pickle files for each year of interest must be created in the 'makePickles201905' notebook.
In [1]:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib as mpl
import netCDF4 as nc
import datetime as dt
from salishsea_tools import evaltools as et, places, viz_tools, visualisations
import xarray as xr
import pandas as pd
import pickle
import os
import bloomdrivers
%matplotlib inline
To recreate this notebook at a different location, follow these instructions:¶
In [2]:
# The path to the directory where the pickle files are stored:
savedir='/ocean/aisabell/MEOPAR/extracted_files'
# Change 'S3' to the location of interest
loc='S3'
# What is the start year and end year+1 of the time range of interest?
startyear=2007
endyear=2021 # does NOT include this value
# Note: What is the model run?
# Note: non-location specific variables only need to be done for each year, not for each location
# Note: xticks in the plots will need to be changed
# Note: 201812 bloom timing variable load and plotting will also need to be removed
In [3]:
modver='201905'
# lat and lon information for place:
lon,lat=places.PLACES[loc]['lon lat']
# get place information on SalishSeaCast grid:
ij,ii=places.PLACES[loc]['NEMO grid ji']
jw,iw=places.PLACES[loc]['GEM2.5 grid ji']
fig, ax = plt.subplots(1,1,figsize = (6,6))
with xr.open_dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/mesh_mask201702.nc') as mesh:
ax.contour(mesh.nav_lon,mesh.nav_lat,mesh.tmask.isel(t=0,z=0),[0.1,],colors='k')
tmask=np.array(mesh.tmask)
gdept_1d=np.array(mesh.gdept_1d)
e3t_0=np.array(mesh.e3t_0)
ax.plot(lon, lat, '.', markersize=14, color='red')
ax.set_ylim(48,50)
ax.set_xlim(-125,-122)
ax.set_title('Location of Station %s'%loc)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
viz_tools.set_aspect(ax,coords='map')
Out[3]:
1.1363636363636362
Strait of Georgia Region:¶
In [4]:
# define sog region:
fig, ax = plt.subplots(1,2,figsize = (6,6))
with xr.open_dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc') as bathy:
bath=np.array(bathy.Bathymetry)
ax[0].contourf(bath,np.arange(0,250,10))
viz_tools.set_aspect(ax[0],coords='grid')
sogmask=np.copy(tmask[:,:,:,:])
sogmask[:,:,740:,:]=0
sogmask[:,:,700:,170:]=0
sogmask[:,:,550:,250:]=0
sogmask[:,:,:,302:]=0
sogmask[:,:,:400,:]=0
sogmask[:,:,:,:100]=0
#sogmask250[bath<250]=0
ax[1].contourf(np.ma.masked_where(sogmask[0,0,:,:]==0,bathy.Bathymetry),[0,100,250,550])
Out[4]:
<matplotlib.contour.QuadContourSet at 0x7f2f67eba760>
*** Stop and check, have you made pickle files for all the years? ***¶
In [5]:
# loop through years of spring time series (mid feb-june) for bloom timing for 201905 run
years=list()
bloomtime1=list()
bloomtime2=list()
bloomtime3=list()
for year in range(startyear,endyear):
fname3=f'springBloomTime_{str(year)}_{loc}_{modver}.pkl'
savepath3=os.path.join(savedir,fname3)
bio_time0,sno30,sdiat0,sflag0,scili0,diat_alld0,no3_alld0,flag_alld0,cili_alld0,phyto_alld0,\
intdiat0,intphyto0,fracdiat0,sphyto0,percdiat0=pickle.load(open(savepath3,'rb'))
# put code that calculates bloom timing here
bt1=bloomdrivers.metric1_bloomtime(phyto_alld0,no3_alld0,bio_time0)
bt2=bloomdrivers.metric2_bloomtime(sphyto0,sno30,bio_time0)
bt3=bloomdrivers.metric3_bloomtime(sphyto0,sno30,bio_time0)
years.append(year)
bloomtime1.append(bt1)
bloomtime2.append(bt2)
bloomtime3.append(bt3)
years=np.array(years)
bloomtime1=np.array(bloomtime1)
bloomtime2=np.array(bloomtime2)
bloomtime3=np.array(bloomtime3)
# get year day
yearday1=et.datetimeToYD(bloomtime1) # convert to year day tool
yearday2=et.datetimeToYD(bloomtime2)
yearday3=et.datetimeToYD(bloomtime3)
In [6]:
# loop through years of spring time series (mid feb-june) for bloom timing for 201812 run
shortyears=list()
bloomtime1_18=list()
bloomtime2_18=list()
bloomtime3_18=list()
for year in range(2015,2020):
modver18='201812'
fname3=f'springBloomTime_{str(year)}_{loc}_{modver18}.pkl'
savepath3=os.path.join(savedir,fname3)
bio_time0,sno30,sdiat0,sflag0,scili0,diat_alld0,no3_alld0,flag_alld0,cili_alld0,phyto_alld0,\
intdiat0,intphyto0,fracdiat0,sphyto0,percdiat0=pickle.load(open(savepath3,'rb'))
# put code that calculates bloom timing here
bt1_18=bloomdrivers.metric1_bloomtime(phyto_alld0,no3_alld0,bio_time0)
bt2_18=bloomdrivers.metric2_bloomtime(sphyto0,sno30,bio_time0)
bt3_18=bloomdrivers.metric3_bloomtime(sphyto0,sno30,bio_time0)
shortyears.append(year)
bloomtime1_18.append(bt1_18)
bloomtime2_18.append(bt2_18)
bloomtime3_18.append(bt3_18)
shortyears=np.array(shortyears)
bloomtime1_18=np.array(bloomtime1_18)
bloomtime2_18=np.array(bloomtime2_18)
bloomtime3_18=np.array(bloomtime3_18)
# get year day
yearday1_18=et.datetimeToYD(bloomtime1_18) # convert to year day tool
yearday2_18=et.datetimeToYD(bloomtime2_18)
yearday3_18=et.datetimeToYD(bloomtime3_18)
Combine separate year files into arrays:¶
In [7]:
# loop through years (for location specific drivers)
years=list()
windjan=list()
windfeb=list()
windmar=list()
solarjan=list()
solarfeb=list()
solarmar=list()
parjan=list()
parfeb=list()
parmar=list()
tempjan=list()
tempfeb=list()
tempmar=list()
saljan=list()
salfeb=list()
salmar=list()
zoojan=list()
zoofeb=list()
zoomar=list()
mesozoojan=list()
mesozoofeb=list()
mesozoomar=list()
microzoojan=list()
microzoofeb=list()
microzoomar=list()
intzoojan=list()
intzoofeb=list()
intzoomar=list()
intmesozoojan=list()
intmesozoofeb=list()
intmesozoomar=list()
intmicrozoojan=list()
intmicrozoofeb=list()
intmicrozoomar=list()
midno3jan=list()
midno3feb=list()
midno3mar=list()
for year in range(startyear,endyear):
fname=f'JanToMarch_TimeSeries_{year}_{loc}_{modver}.pkl'
savepath=os.path.join(savedir,fname)
bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\
intdiat,intphyto,spar,intmesoz,intmicroz,grid_time,temp,salinity,u_wind,v_wind,twind,\
solar,no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,\
percdiat,wspeed,winddirec=pickle.load(open(savepath,'rb'))
# put code that calculates drivers here
wind=bloomdrivers.janfebmar_wspeed3(twind,wspeed)
solar=bloomdrivers.janfebmar_irradiance(twind,solar)
par=bloomdrivers.janfebmar_spar(bio_time,spar)
temp=bloomdrivers.janfebmar_temp(grid_time,temp)
sal=bloomdrivers.janfebmar_temp(grid_time,salinity)
zoo=bloomdrivers.janfebmar_zooplankton(bio_time,zoop_alld)
mesozoo=bloomdrivers.janfebmar_mesozooplankton(bio_time,mesozoo_alld)
microzoo=bloomdrivers.janfebmar_microzooplankton(bio_time,microzoo_alld)
intzoo=bloomdrivers.janfebmar_depth_intzoop(bio_time,intzoop)
intmesozoo=bloomdrivers.janfebmar_depth_intmesozoop(bio_time,intmesoz)
intmicrozoo=bloomdrivers.janfebmar_depth_intmicrozoop(bio_time,intmicroz)
midno3=bloomdrivers.janfebmar_mid_depth_no3(bio_time,no3_30to90m)
years.append(year)
windjan.append(wind[0])
windfeb.append(wind[1])
windmar.append(wind[2])
solarjan.append(solar[0])
solarfeb.append(solar[1])
solarmar.append(solar[2])
parjan.append(par[0])
parfeb.append(par[1])
parmar.append(par[2])
tempjan.append(temp[0])
tempfeb.append(temp[1])
tempmar.append(temp[2])
saljan.append(sal[0])
salfeb.append(sal[1])
salmar.append(sal[2])
zoojan.append(zoo[0])
zoofeb.append(zoo[1])
zoomar.append(zoo[2])
mesozoojan.append(mesozoo[0])
mesozoofeb.append(mesozoo[1])
mesozoomar.append(mesozoo[2])
microzoojan.append(microzoo[0])
microzoofeb.append(microzoo[1])
microzoomar.append(microzoo[2])
intzoojan.append(intzoo[0])
intzoofeb.append(intzoo[1])
intzoomar.append(intzoo[2])
intmesozoojan.append(intmesozoo[0])
intmesozoofeb.append(intmesozoo[1])
intmesozoomar.append(intmesozoo[2])
intmicrozoojan.append(intmicrozoo[0])
intmicrozoofeb.append(intmicrozoo[1])
intmicrozoomar.append(intmicrozoo[2])
midno3jan.append(midno3[0])
midno3feb.append(midno3[1])
midno3mar.append(midno3[2])
years=np.array(years)
windjan=np.array(windjan)
windfeb=np.array(windfeb)
windmar=np.array(windmar)
solarjan=np.array(solarjan)
solarfeb=np.array(solarfeb)
solarmar=np.array(solarmar)
parjan=np.array(parjan)
parfeb=np.array(parfeb)
parmar=np.array(parmar)
tempjan=np.array(tempjan)
tempfeb=np.array(tempfeb)
tempmar=np.array(tempmar)
saljan=np.array(saljan)
salfeb=np.array(salfeb)
salmar=np.array(salmar)
zoojan=np.array(zoojan)
zoofeb=np.array(zoofeb)
zoomar=np.array(zoomar)
mesozoojan=np.array(mesozoojan)
mesozoofeb=np.array(mesozoofeb)
mesozoomar=np.array(mesozoomar)
microzoojan=np.array(microzoojan)
microzoofeb=np.array(microzoofeb)
microzoomar=np.array(microzoomar)
intzoojan=np.array(intzoojan)
intzoofeb=np.array(intzoofeb)
intzoomar=np.array(intzoomar)
intmesozoojan=np.array(intmesozoojan)
intmesozoofeb=np.array(intmesozoofeb)
intmesozoomar=np.array(intmesozoomar)
intmicrozoojan=np.array(intmicrozoojan)
intmicrozoofeb=np.array(intmicrozoofeb)
intmicrozoomar=np.array(intmicrozoomar)
midno3jan=np.array(midno3jan)
midno3feb=np.array(midno3feb)
midno3mar=np.array(midno3mar)
In [8]:
# loop through years (for non-location specific drivers)
fraserjan=list()
fraserfeb=list()
frasermar=list()
deepno3jan=list()
deepno3feb=list()
deepno3mar=list()
for year in range(startyear,endyear):
fname2=f'JanToMarch_TimeSeries_{year}_{modver}.pkl'
savepath2=os.path.join(savedir,fname2)
no3_past250m,riv_time,rivFlow=pickle.load(open(savepath2,'rb'))
# Code that calculates drivers here
fraser=bloomdrivers.janfebmar_fraserflow(riv_time,rivFlow)
fraserjan.append(fraser[0])
fraserfeb.append(fraser[1])
frasermar.append(fraser[2])
fname=f'JanToMarch_TimeSeries_{year}_{loc}_{modver}.pkl'
savepath=os.path.join(savedir,fname)
bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\
intdiat,intphyto,spar,intmesoz,intmicroz,grid_time,temp,salinity,u_wind,v_wind,twind,\
solar,no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,\
percdiat,wspeed,winddirec=pickle.load(open(savepath,'rb'))
deepno3=bloomdrivers.janfebmar_deepno3(bio_time,no3_past250m)
deepno3jan.append(deepno3[0])
deepno3feb.append(deepno3[1])
deepno3mar.append(deepno3[2])
fraserjan=np.array(fraserjan)
fraserfeb=np.array(fraserfeb)
frasermar=np.array(frasermar)
deepno3jan=np.array(deepno3jan)
deepno3feb=np.array(deepno3feb)
deepno3mar=np.array(deepno3mar)
In [9]:
# loop through years (for mixing drivers)
halojan=list()
halofeb=list()
halomar=list()
for year in range(startyear,endyear):
fname4=f'JanToMarch_Mixing_{year}_{loc}_{modver}.pkl'
savepath4=os.path.join(savedir,fname4)
halocline,eddy,diss,depth=pickle.load(open(savepath4,'rb'))
fname=f'JanToMarch_TimeSeries_{year}_{loc}_{modver}.pkl'
savepath=os.path.join(savedir,fname)
bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\
intdiat,intphyto,spar,intmesoz,intmicroz,grid_time,temp,salinity,u_wind,v_wind,twind,\
solar,no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,\
percdiat,wspeed,winddirec=pickle.load(open(savepath,'rb'))
# put code that calculates drivers here
halo=bloomdrivers.janfebmar_halocline(bio_time,halocline)
halojan.append(halo[0])
halofeb.append(halo[1])
halomar.append(halo[2])
halojan=np.array(halojan)
halofeb=np.array(halofeb)
halomar=np.array(halomar)
Bloom date¶
In [10]:
# plot bloomtime for each year:
fig,ax=plt.subplots(1,1,figsize=(10,7))
p1=ax.plot(years,yearday1, 'o',color='firebrick',label='Metric1 (201905)')
p2=ax.plot(years,yearday2, 'o',color='b',label='Metric2 (201905)')
p3=ax.plot(years,yearday3, 'o',color='orange',label='Metric3 (201905)')
p4=ax.plot(shortyears,yearday1_18, 'x',color='firebrick',label='Metric1 (201812)',markersize=10)
p5=ax.plot(shortyears,yearday2_18, 'x',color='b',label='Metric2 (201812)',markersize=10)
p6=ax.plot(shortyears,yearday3_18, 'x',color='orange',label='Metric3 (201812)',markersize=10)
ax.set_ylabel('Year Day')
ax.set_xlabel('Year')
ax.set_title('Spring Phytoplankton Bloom Date by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0],p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0))
Out[10]:
<matplotlib.legend.Legend at 0x7f2f67667790>
Monthly average wind speed cubed (January-March)¶
In [11]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,windjan, '-',color='green',label='January Average')
p2=ax.plot(years,windfeb, '-',color='c',label='February Average')
p3=ax.plot(years,windmar, '-',color='orchid',label='March Average')
ax.set_ylabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax.set_xlabel('Year')
ax.set_title('Wind Speed Cubed by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# ---------- Jan ---------
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(windjan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(windjan,yearday1)
ax2[0].plot(windjan, y, 'r', label='Fitted Line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(windjan,yearday2,'o',color='b')
ax2[1].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(windjan,yearday2)
ax2[1].plot(windjan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(windjan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(windjan,yearday3)
ax2[2].plot(windjan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].set_title('Bloom Date vs. January Average Wind Speed Cubed')
# ---------- Feb ---------
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(windfeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(windfeb,yearday1)
ax3[0].plot(windfeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(windfeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(windfeb,yearday2)
ax3[1].plot(windfeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(windfeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(windfeb,yearday3)
ax3[2].plot(windfeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2,transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].set_title('Bloom Date vs. February Average Wind Speed Cubed')
# ---------- March ---------
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(windmar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(windmar,yearday1)
ax4[0].plot(windmar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(windmar,yearday2,'o',color='b')
ax4[1].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[1].set_title('Bloom Date vs. March Average Wind Speed Cubed')
y,r2,m,b=bloomdrivers.reg_r2(windmar,yearday2)
ax4[1].plot(windmar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(windmar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Wind Speed Cubed ($\mathregular{m^3}$/$\mathregular{s^3}$)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(windmar,yearday3)
ax4[2].plot(windmar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[11]:
<matplotlib.lines.Line2D at 0x7f2f672fdb20>
Monthly average solar radiation (January-March)¶
In [25]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,solarjan, '-',color='green',label='January Average')
p2=ax.plot(years,solarfeb, '-',color='c',label='February Average')
p3=ax.plot(years,solarmar, '-',color='orchid',label='March Average')
ax.set_ylabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax.set_xlabel('Year')
ax.set_title('Solar Irradiance by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# ----Jan----
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(solarjan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(solarjan,yearday1)
ax2[0].plot(solarjan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(solarjan,yearday2,'o',color='b')
ax2[1].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(solarjan,yearday2)
ax2[1].plot(solarjan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(solarjan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Solar Irradiance')
y,r2,m,b=bloomdrivers.reg_r2(solarjan,yearday3)
ax2[2].plot(solarjan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# ----Feb----
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(solarfeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(solarfeb,yearday1)
ax3[0].plot(solarfeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(solarfeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(solarfeb,yearday2)
ax3[1].plot(solarfeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(solarfeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(solarfeb,yearday3)
ax3[2].plot(solarfeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].set_title('Bloom Date vs. February Average Solar Irradiance')
# ----March----
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(solarmar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(solarmar,yearday1)
ax4[0].plot(solarmar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(solarmar,yearday2,'o',color='b')
ax4[1].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(solarmar,yearday2)
ax4[1].plot(solarmar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(solarmar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Solar Irradiance (W/$\mathregular{m^2}$)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(solarmar,yearday3)
ax4[2].plot(solarmar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].set_title('Bloom Date vs. March Average Solar Irradiance')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[25]:
<matplotlib.lines.Line2D at 0x7f70c23c6700>
Monthly average surface temperature (January-March)¶
In [27]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,tempjan, '-',color='green',label='January Average')
p2=ax.plot(years,tempfeb, '-',color='c',label='February Average')
p3=ax.plot(years,tempmar, '-',color='orchid',label='March Average')
ax.set_ylabel('Surface Temperature ($^\circ$C)')
ax.set_xlabel('Year')
ax.set_title('Surface Conservative Temperature by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# JAN
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(tempjan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Surface Temperature ($^\circ$C)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(tempjan,yearday1)
ax2[0].plot(tempjan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(tempjan,yearday2,'o',color='b')
ax2[1].set_xlabel('Surface Temperature ($^\circ$C)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(tempjan,yearday2)
ax2[1].plot(tempjan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(tempjan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Surface Temperature ($^\circ$C)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(tempjan,yearday3)
ax2[2].plot(tempjan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].set_title('Bloom Date vs. January Average Surface Conservative Temperature')
# FEB
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(tempfeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Surface Temperature ($^\circ$C)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(tempfeb,yearday1)
ax3[0].plot(tempfeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(tempfeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Surface Temperature ($^\circ$C)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(tempfeb,yearday2)
ax3[1].plot(tempfeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(tempfeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Surface Temperature ($^\circ$C)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(tempfeb,yearday3)
ax3[2].plot(tempfeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].set_title('Bloom Date vs. February Average Surface Conservative Temperature')
# MARCH
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(tempmar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Surface Temperature ($^\circ$C)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(tempmar,yearday1)
ax4[0].plot(tempmar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(tempmar,yearday2,'o',color='b')
ax4[1].set_xlabel('Surface Temperature ($^\circ$C)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(tempmar,yearday2)
ax4[1].plot(tempmar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(tempmar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Surface Temperature ($^\circ$C)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Surface Conservative Temperature')
y,r2,m,b=bloomdrivers.reg_r2(tempmar,yearday3)
ax4[2].plot(tempmar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[27]:
<matplotlib.lines.Line2D at 0x7f70c2520f70>
Monthly average surface salinity (January-March)¶
In [28]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,saljan, '-',color='green',label='January Average')
p2=ax.plot(years,salfeb, '-',color='c',label='February Average')
p3=ax.plot(years,salmar, '-',color='orchid',label='March Average')
ax.set_ylabel('Salinity (g/kg)')
ax.set_xlabel('Year')
ax.set_title('Absolute Surface Salinity by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# JAN
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(saljan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Salinity (g/kg)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(saljan,yearday1)
ax2[0].plot(saljan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(saljan,yearday2,'o',color='b')
ax2[1].set_xlabel('Salinity (g/kg)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(saljan,yearday2)
ax2[1].plot(saljan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(saljan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Salinity (g/kg)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Absolute Surface Salinity')
y,r2,m,b=bloomdrivers.reg_r2(saljan,yearday3)
ax2[2].plot(saljan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# FEB
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(salfeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Salinity (g/kg)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(salfeb,yearday1)
ax3[0].plot(salfeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(salfeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Salinity (g/kg)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(salfeb,yearday2)
ax3[1].plot(salfeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(salfeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Salinity (g/kg)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Absolute Surface Salinity')
y,r2,m,b=bloomdrivers.reg_r2(salfeb,yearday3)
ax3[2].plot(salfeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# MAR
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(salmar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Salinity (g/kg)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(salmar,yearday1)
ax4[0].plot(salmar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(salmar,yearday2,'o',color='b')
ax4[1].set_xlabel('Salinity (g/kg)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(salmar,yearday2)
ax4[1].plot(salmar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(salmar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Salinity (g/kg)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Absolute Surface Salinity')
y,r2,m,b=bloomdrivers.reg_r2(salmar,yearday3)
ax4[2].plot(salmar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[28]:
<matplotlib.lines.Line2D at 0x7f70c1fa7bb0>
Monthly average Fraser river flow (January-March)¶
In [30]:
fraseryears=years[:-1]
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,fraserjan, '-',color='green',label='January Average')
p2=ax.plot(years,fraserfeb, '-',color='c',label='February Average')
p3=ax.plot(years,frasermar, '-',color='orchid',label='March Average')
ax.set_ylabel('Flow (m$^3$s$^{-1}$)')
ax.set_xlabel('Year')
ax.set_title('Fraser River Flow by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# JAN
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(fraserjan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(fraserjan,yearday1)
ax2[0].plot(fraserjan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(fraserjan,yearday2,'o',color='b')
ax2[1].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(fraserjan,yearday2)
ax2[1].plot(fraserjan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(fraserjan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Fraser River Flow')
y,r2,m,b=bloomdrivers.reg_r2(fraserjan,yearday3)
ax2[2].plot(fraserjan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# FEB
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(fraserfeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(fraserfeb,yearday1)
ax3[0].plot(fraserfeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(fraserfeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(fraserfeb,yearday2)
ax3[1].plot(fraserfeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(fraserfeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Fraser River Flow')
y,r2,m,b=bloomdrivers.reg_r2(fraserfeb,yearday3)
ax3[2].plot(fraserfeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# MAR
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(frasermar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(frasermar,yearday1)
ax4[0].plot(frasermar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(frasermar,yearday2,'o',color='b')
ax4[1].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(frasermar,yearday2)
ax4[1].plot(frasermar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(frasermar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Flow (m$^3$s$^{-1}$)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Fraser River Flow')
y,r2,m,b=bloomdrivers.reg_r2(frasermar,yearday3)
ax4[2].plot(frasermar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st'https://open.spotify.com/track/5la5PTcDm8oQuzHX9ssVZf)
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[30]:
<matplotlib.lines.Line2D at 0x7f70c2008fa0>
Monthly average surface zooplankton concentration (January-March)¶
In [40]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,zoojan, '-',color='green',label='January Average')
p2=ax.plot(years,zoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,zoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Zooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Surface Zooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(zoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(zoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(zoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Surface Zooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(zoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(zoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(zoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Surface Zooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(zoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(zoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(zoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Surface Zooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[40]:
<matplotlib.lines.Line2D at 0x7fc9ee54a040>
Monthly average surface mesozooplankton concentration (January-March)¶
In [41]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,mesozoojan, '-',color='green',label='January Average')
p2=ax.plot(years,mesozoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,mesozoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Mesozooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Surface Mesozooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(mesozoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(mesozoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(mesozoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Surface Mesozooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(mesozoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(mesozoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(mesozoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Surface Mesozooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(mesozoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(mesozoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(mesozoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Surface Mesozooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[41]:
<matplotlib.lines.Line2D at 0x7fc9edb84dc0>
Monthly average surface microzooplankton concentration (January-March)¶
In [42]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,microzoojan, '-',color='green',label='January Average')
p2=ax.plot(years,microzoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,microzoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Microzooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Surface Microzooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(microzoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(microzoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(microzoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Surface Microzooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(microzoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(microzoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(microzoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Surface Microzooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(microzoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(microzoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(microzoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Surface Microzooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[42]:
<matplotlib.lines.Line2D at 0x7fc9edb68e20>
Monthly average depth-integrated zooplankton concentration (January-March)¶
In [43]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,intzoojan, '-',color='green',label='January Average')
p2=ax.plot(years,intzoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,intzoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Zooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Depth-integrated Zooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(intzoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(intzoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(intzoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Depth-integrated Zooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(intzoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(intzoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(intzoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Depth-integrated Zooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(intzoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(intzoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(intzoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Depth-integrated Zooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[43]:
<matplotlib.lines.Line2D at 0x7fc9ede2e970>
Monthly average depth-integrated mesozooplankton concentration (January-March)¶
In [44]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,intmesozoojan, '-',color='green',label='January Average')
p2=ax.plot(years,intmesozoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,intmesozoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Mesozooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Depth-integrated Mesozooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(intmesozoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(intmesozoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(intmesozoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Depth-integrated Mesozooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(intmesozoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(intmesozoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(intmesozoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Depth-integrated Mesozooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(intmesozoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(intmesozoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(intmesozoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Depth-integrated Mesozooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[44]:
<matplotlib.lines.Line2D at 0x7fc9ee64e9d0>
Monthly average depth-integrated microzooplankton concentration (January-March)¶
In [45]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,intmicrozoojan, '-',color='green',label='January Average')
p2=ax.plot(years,intmicrozoofeb, '-',color='c',label='February Average')
p3=ax.plot(years,intmicrozoomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Microzooplankon Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Depth-integrated Microzooplankon Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax.invert_yaxis()
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(intmicrozoojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
ax2[1].plot(intmicrozoojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
ax2[2].plot(intmicrozoojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Depth-integrated Microzooplankon Concentration')
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(intmicrozoofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
ax3[1].plot(intmicrozoofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
ax3[2].plot(intmicrozoofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Depth-integrated Microzooplankon Concentration')
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(intmicrozoomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
ax4[1].plot(intmicrozoomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
ax4[2].plot(intmicrozoomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Depth-integrated Microzooplankon Concentration')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[45]:
<matplotlib.lines.Line2D at 0x7fc9db64d970>
Mid-Depth Nitrate (30-90m)¶
In [31]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,midno3jan, '-',color='green',label='January Average')
p2=ax.plot(years,midno3feb, '-',color='c',label='February Average')
p3=ax.plot(years,midno3mar, '-',color='orchid',label='March Average')
ax.set_ylabel('Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Mid-depth (30-90m) Nitrate Concentration by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
#JAN
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(midno3jan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(midno3jan,yearday1)
ax2[0].plot(midno3jan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(midno3jan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(midno3jan,yearday2)
ax2[1].plot(midno3jan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(midno3jan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Mid-depth (30-90m) Nitrate Concentration')
y,r2,m,b=bloomdrivers.reg_r2(midno3jan,yearday3)
ax2[2].plot(midno3jan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# FEB
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(midno3feb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Concentration ($\mu$M N)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(midno3feb,yearday1)
ax3[0].plot(midno3feb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(midno3feb,yearday2,'o',color='b')
ax3[1].set_xlabel('Concentration ($\mu$M N)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(midno3feb,yearday2)
ax3[1].plot(midno3feb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(midno3feb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Concentration ($\mu$M N)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Mid-depth (30-90m) Nitrate Concentration')
y,r2,m,b=bloomdrivers.reg_r2(midno3feb,yearday3)
ax3[2].plot(midno3feb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# MAR
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(midno3mar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Concentration ($\mu$M N)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(midno3mar,yearday1)
ax4[0].plot(midno3mar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(midno3mar,yearday2,'o',color='b')
ax4[1].set_xlabel('Concentration ($\mu$M N)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(midno3mar,yearday2)
ax4[1].plot(midno3mar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(midno3mar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Concentration ($\mu$M N)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Mid-depth (30-90m) Nitrate Concentration')
y,r2,m,b=bloomdrivers.reg_r2(midno3mar,yearday3)
ax4[2].plot(midno3mar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[31]:
<matplotlib.lines.Line2D at 0x7f70c19a2370>
Nitrate concentration in deep SoG (below 250 m)¶
In [32]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,deepno3jan, '-',color='green',label='January Average')
#p2=ax.plot(years,deepno3feb, '-',color='c',label='February Average')
#p3=ax.plot(years,deepno3mar, '-',color='orchid',label='March Average')
ax.set_ylabel('Concentration ($\mu$M N)')
ax.set_xlabel('Year')
ax.set_title('Deep (below 250m) Nitrate Concentration Throughout SoG by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(deepno3jan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Concentration ($\mu$M N)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(deepno3jan,yearday1)
ax2[0].plot(deepno3jan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(deepno3jan,yearday2,'o',color='b')
ax2[1].set_xlabel('Concentration ($\mu$M N)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(deepno3jan,yearday2)
ax2[1].plot(deepno3jan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(deepno3jan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Concentration ($\mu$M N)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
y,r2,m,b=bloomdrivers.reg_r2(deepno3jan,yearday3)
ax2[2].plot(deepno3jan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].set_title('Bloom Date vs. January Average Deep (below 250m) Nitrate Concentration Throughout SoG')
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[32]:
<matplotlib.lines.Line2D at 0x7f70c4182190>
Halocline¶
In [33]:
fig,ax=plt.subplots(1,1,figsize=(12,5))
p1=ax.plot(years,halojan, '-',color='green',label='January Average')
p2=ax.plot(years,halofeb, '-',color='c',label='February Average')
p3=ax.plot(years,halomar, '-',color='orchid',label='March Average')
ax.set_ylabel('Halocline Depth (m)')
ax.set_xlabel('Year')
ax.set_title('Halocline Depth by Year')
ax.set_xticks([2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020])
ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')
ax1=ax.twinx()
p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')
p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')
p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')
ax1.set_ylabel('Year Day')
ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')
# JAN
fig2,ax2=plt.subplots(1,3,figsize=(17,5))
ax2[0].plot(halojan,yearday1,'o',color='firebrick')
ax2[0].set_xlabel('Halocline Depth (m)')
ax2[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(halojan,yearday1)
ax2[0].plot(halojan, y, 'r', label='Fitted line')
ax2[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[1].plot(halojan,yearday2,'o',color='b')
ax2[1].set_xlabel('Halocline Depth (m)')
ax2[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(halojan,yearday2)
ax2[1].plot(halojan, y, 'r', label='Fitted line')
ax2[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax2[2].plot(halojan,yearday3,'o',color='orange')
ax2[2].set_xlabel('Halocline Depth (m)')
ax2[2].set_ylabel('Bloom Day (Metric 3)')
ax2[1].set_title('Bloom Date vs. January Average Halocline Depth')
y,r2,m,b=bloomdrivers.reg_r2(halojan,yearday3)
ax2[2].plot(halojan, y, 'r', label='Fitted line')
ax2[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax2[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# FEB
fig3,ax3=plt.subplots(1,3,figsize=(17,5))
ax3[0].plot(halofeb,yearday1,'o',color='firebrick')
ax3[0].set_xlabel('Halocline Depth (m)')
ax3[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(halofeb,yearday1)
ax3[0].plot(halofeb, y, 'r', label='Fitted line')
ax3[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[1].plot(halofeb,yearday2,'o',color='b')
ax3[1].set_xlabel('Halocline Depth (m)')
ax3[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(halofeb,yearday2)
ax3[1].plot(halofeb, y, 'r', label='Fitted line')
ax3[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax3[2].plot(halofeb,yearday3,'o',color='orange')
ax3[2].set_xlabel('Halocline Depth (m)')
ax3[2].set_ylabel('Bloom Day (Metric 3)')
ax3[1].set_title('Bloom Date vs. February Average Halocline Depth')
y,r2,m,b=bloomdrivers.reg_r2(halofeb,yearday3)
ax3[2].plot(halofeb, y, 'r', label='Fitted line')
ax3[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax3[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# MAR
fig4,ax4=plt.subplots(1,3,figsize=(17,5))
ax4[0].plot(halomar,yearday1,'o',color='firebrick')
ax4[0].set_xlabel('Halocline Depth (m)')
ax4[0].set_ylabel('Bloom Day (Metric 1)')
y,r2,m,b=bloomdrivers.reg_r2(halomar,yearday1)
ax4[0].plot(halomar, y, 'r', label='Fitted line')
ax4[0].text(0.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[0].text(0.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[1].plot(halomar,yearday2,'o',color='b')
ax4[1].set_xlabel('Halocline Depth (m)')
ax4[1].set_ylabel('Bloom Day (Metric 2)')
y,r2,m,b=bloomdrivers.reg_r2(halomar,yearday2)
ax4[1].plot(halomar, y, 'r', label='Fitted line')
ax4[1].text(0.6, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[1].text(0.6,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
ax4[2].plot(halomar,yearday3,'o',color='orange')
ax4[2].set_xlabel('Halocline Depth (m)')
ax4[2].set_ylabel('Bloom Day (Metric 3)')
ax4[1].set_title('Bloom Date vs. March Average Halocline Depth')
y,r2,m,b=bloomdrivers.reg_r2(halomar,yearday3)
ax4[2].plot(halomar, y, 'r', label='Fitted line')
ax4[2].text(1.1, 0.85, '$\mathregular{r^2}$ = %f'%r2, transform=ax.transAxes)
ax4[2].text(1.1,0.81,f'y={m}x+{b}',horizontalalignment='left',verticalalignment='bottom',transform=ax.transAxes)
# Jan month lines
ax2[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax2[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax2[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax2[1].axhline(y=90, color='orchid', linestyle='--')
ax2[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax2[1].axhline(y=120, color='peru', linestyle='--')
ax2[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# Feb month lines
ax3[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax3[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax3[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax3[1].axhline(y=90, color='orchid', linestyle='--')
ax3[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax3[1].axhline(y=120, color='peru', linestyle='--')
ax3[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
# March month lines
ax4[0].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[0].axhline(y=120, color='peru', linestyle='--',label='April 30th')
#ax4[0].axhline(y=151, color='lime', linestyle='--',label='May 31st')
ax4[0].legend(bbox_to_anchor=(-0.25, 1.0))
ax4[1].axhline(y=90, color='orchid', linestyle='--')
ax4[2].axhline(y=90, color='orchid', linestyle='--',label='March 31st')
ax4[1].axhline(y=120, color='peru', linestyle='--')
ax4[2].axhline(y=120, color='peru', linestyle='--',label='April 30th')
Out[33]:
<matplotlib.lines.Line2D at 0x7f70c1860250>
In [ ]: