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Commit 4d27a624 authored by Johannes Hörner's avatar Johannes Hörner
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Reworked scripts, removed unnecessary clutter code

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%% Cell type:markdown id: tags:
# Create CO2 - ice-edge latitude diagrams and calculate stability
Stability is assessed by reading simulation data and applying the stability criterion. CO2 - ice-edge latitude diagrams are created by manual input of stability and equilibrium ice-edge latitude. The actual bifurcation diagram is added afterwards as a best guess.
%% Cell type:code id: tags:
``` python
%matplotlib inline
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def load_experiment(expname): #loads the dataset of a simulation
fname = expname +"_atm_2d_ml.mm.gm.nc" #filename of global yearly mean
dpath = "/work/bb1092/pp_JH/" +expname +"/" #simulation path
DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset
print(dpath +fname)
return expname, DS # returns the name of the experiment & the actual dataset
def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable
da=getattr(dataset,varname) #read dataarray
da.squeeze() #squeeze dataarray (time is the only dimension)
if offsettime:
da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0
else:
da=da.assign_coords(time=((da.time)/360)) #change time units from days to years
return da
def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram
handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line
#plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#
if stable:
if stable==2:
axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor="none")
else:
axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')
else:
if endlat<startlat:
axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')
else:
axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')
return handle
def plot_simulation_merged(axes,co2, startlat, endlat, col, stable, offset=0): #plot a simulation into the bifurcation diagram
#plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#
handle = []
if stable==2: # metastable
axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor="none",clip_on=False)
elif stable==1: # stable from warm
axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='o',clip_on=False)
elif stable==3: # towards Snowball
if endlat==0:
axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='v',clip_on=False)
else:
axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='v',clip_on=False)
handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line
elif stable==4: # towards icefree
axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='^',clip_on=False)
handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line
return handle
def plot_co2_equivalent(co2, startlat, endlat, col, stable, heatflux):
CO2_fac=np.exp(heatflux/5.35)
handle, =plt.plot([co2*CO2_fac,co2*CO2_fac],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line
#plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#
if stable:
plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='o')
else:
if endlat<startlat:
plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='v')
else:
plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='^')
return handle
def legend_color(ax, handle_array, pos):
legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)
for item in legend.legendHandles:
item.set_visible(False)
for text in legend.get_texts():
if text.get_text()=='Winton':
text.set_color('C1')
if text.get_text()=='3L-Winton':
text.set_color('C1')
elif text.get_text()=='Semtner':
text.set_color('C0')
elif text.get_text()=='0L-Semtner':
text.set_color('C0')
elif text.get_text()=='Semtner_5m':
text.set_color('C2')
elif text.get_text()=='0L-Semtner-lim5':
text.set_color('C2')
elif text.get_text()=='0L-Semtner-limited':
text.set_color('C2')
elif text.get_text()=='1438ppmv':
text.set_color('C0')
elif text.get_text()=='1500ppmv':
text.set_color('C1')
elif text.get_text()=='3000ppmv':
text.set_color('C2')
elif text.get_text()=='5000ppmv':
text.set_color('C3')
return legend
def stability_index(DS):
LW = get_var(DS,"rlut",True)
SW = get_var(DS,"rsdt",True)-get_var(DS,"rsut",True)
T = get_var(DS,'ts',True)
N = np.squeeze(SW[-50*12:]-LW[-50*12:])
Nparm = stats.linregress(LW.time[-50*12:]-LW.time[-50*12],N)
f=(Nparm.slope) #*np.sign(np.squeeze(SW-LW).values[-1])
return f
def is_stable(f):
if f>0: return False
else: return True
```
%% Cell type:code id: tags:
``` python
experiment1, DS1 = load_experiment("mlo_aqua_1500ppmv_hice_unlim")
experiment2, DS2 = load_experiment("mlo_aqua_1594ppmv_hice_unlim")
experiment3, DS3 = load_experiment("mlo_aqua_1688ppmv_hice_unlim")
experiment4, DS4 = load_experiment("mlo_aqua_1875ppmv_hice_unlim")
experiment5, DS5 = load_experiment("mlo_aqua_2250ppmv_hice_unlim")
experiment1_Jor, DS1_Jor = load_experiment("mlo_aqua_3000ppmv_77sic_hice_unlim")
experiment2_Jor, DS2_Jor = load_experiment("mlo_aqua_3000ppmv_61sic_hice_unlim")
experiment3_Jor, DS3_Jor = load_experiment("mlo_aqua_3750ppmv_69sic_hice_unlim")
experiment4_Jor, DS4_Jor = load_experiment("mlo_aqua_3750ppmv_77sic_hice_unlim")
experiment5_Jor, DS5_Jor = load_experiment("mlo_aqua_3907ppmv_77sic_hice_unlim")
experiment6_Jor, DS6_Jor = load_experiment("mlo_aqua_4063ppmv_77sic_hice_unlim")
experiment7_Jor, DS7_Jor = load_experiment("mlo_aqua_4219ppmv_77sic_hice_unlim")
experiment8_Jor, DS8_Jor = load_experiment("mlo_aqua_4375ppmv_77sic_hice_unlim")
experiment9_Jor, DS9_Jor = load_experiment("mlo_aqua_5000ppmv_77sic_hice_unlim")
experiment10_Jor, DS10_Jor = load_experiment("mlo_aqua_5000ppmv_83sic_hice_unlim")
experiment11_Jor, DS11_Jor = load_experiment("mlo_aqua_10000ppmv_77sic_hice_unlim")
experiment1_5m, DS1_5m = load_experiment("mlo_aqua_1500ppmv")
experiment2_5m, DS2_5m = load_experiment("mlo_aqua_3000ppmv")
experiment3_5m, DS3_5m = load_experiment("mlo_aqua_5000ppmv")
DS_array=[DS1, DS2, DS3, DS4, DS5] #, DS1_Jor, DS2_Jor, DS3_Jor, DS4_Jor, DS5_Jor, DS6_Jor
# , DS7_Jor, DS8_Jor, DS9_Jor, DS10_Jor, DS11_Jor
```
%% Output
/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_1594ppmv_hice_unlim/mlo_aqua_1594ppmv_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3000ppmv_61sic_hice_unlim/mlo_aqua_3000ppmv_61sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3750ppmv_69sic_hice_unlim/mlo_aqua_3750ppmv_69sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3750ppmv_77sic_hice_unlim/mlo_aqua_3750ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3907ppmv_77sic_hice_unlim/mlo_aqua_3907ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_4063ppmv_77sic_hice_unlim/mlo_aqua_4063ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_4375ppmv_77sic_hice_unlim/mlo_aqua_4375ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_5000ppmv_83sic_hice_unlim/mlo_aqua_5000ppmv_83sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_10000ppmv_77sic_hice_unlim/mlo_aqua_10000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc
/work/bb1092/pp_JH/mlo_aqua_5000ppmv/mlo_aqua_5000ppmv_atm_2d_ml.mm.gm.nc
%% Cell type:code id: tags:
``` python
### %matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
save_plot = True
plot_unlim = True
plot_5m = True
offset=0.01
labelsize=10
ticksize=10
fig, ax = plt.subplots(figsize=(6,4))
ax.spines['left'].set_position(('outward',5))
ax.spines['bottom'].set_position(('outward',5))
# 5m simulations
if plot_5m:
color_5m='C2'
#b=plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)
#plot_simulation_merged(ax,1375, 90, 0, color_5m, 1)
plot_simulation_merged(ax,1438, 90, 0, color_5m, 1)
plot_simulation_merged(ax,1500, 90, 46.6, color_5m, 1)
plot_simulation_merged(ax,1594, 90, 50.3, color_5m, 1)
#plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)
plot_simulation_merged(ax,3000, 90, 65, color_5m, 1)
plot_simulation_merged(ax,5000, 90, 90, color_5m, 1)
# Jormungand
#mlo_aqua_2000ppmv_Jor2
#plot_simulation_merged(ax,2000, 32.68, 29.34, color_5m, 3)
#mlo_aqua_2000ppmv_Jor5
plot_simulation_merged(ax,2000, 13.48, 0, color_5m, 3)
#mlo_aqua_2000ppmv_Jor5
#plot_simulation_merged(ax,2000, 32.68, 29.34, color_5m, 3)
#mlo_aqua_2500ppmv_Jor2
plot_simulation_merged(ax,2500, 13.48, 0, color_5m, 3)
#mlo_aqua_2500ppmv_Jor5
#plot_simulation_merged(ax,2500, 32.68, 36.16, color_5m, 4)
#mlo_aqua_3000ppmv_Jor
plot_simulation_merged(ax,3000, 28.03, 36.87, color_5m, 4)
#mlo_aqua_3000ppmv_Jor2
plot_simulation_merged(ax,3000, 13.48, 0, color_5m, 3)
#mlo_aqua_3000ppmv_Jor3
#plot_simulation_merged(ax,3000, 16.26, 22.95, color_5m, 4)
#mlo_aqua_5000ppmv_Jor
#plot_simulation_merged(ax,5000, 28.03, 34.75, color_5m, 4)
#mlo_aqua_5000ppmv_Jor2
plot_simulation_merged(ax,5000, 13.29, 30.00, color_5m, 4)
#mlo_aqua_5000ppmv_Jor4
plot_simulation_merged(ax,5000, 7.47, 15.07, color_5m, 4, -offset)
#mlo_aqua_10000ppmv_Jor
#plot_simulation_merged(ax,10000, 28.03, 41.30, color_5m, 4)
#hice_unlim simulations
if plot_unlim:
color_unlim='C0'
offset=0.01
a=plot_simulation_merged(ax,1500, 90, 0, color_unlim, 1)
plot_simulation_merged(ax,1594, 90, 49.54, color_unlim, 1, offset)
plot_simulation_merged(ax,1688, 90, 51.07, color_unlim, 1)
plot_simulation_merged(ax,1875, 90, 53.20, color_unlim, 1)
plot_simulation_merged(ax,2250, 90, 56.85, color_unlim, 1)
plot_simulation_merged(ax,3000, 90, 65, color_unlim, 1, offset) #5m limited, but always under 5m
plot_simulation_merged(ax,3000, 14.46, 0, color_unlim, 3, offset)
#plot_simulation_merged(ax,3000, 22.05, 22.83, color_unlim, 4)
plot_simulation_merged(ax,3750, 14.46, 0, color_unlim, 3)
#plot_simulation_merged(ax,3750, 19.2, 18.7, color_unlim, 4)
#plot_simulation_merged(ax,3907, 14.46, 15.1, color_unlim, 2)
plot_simulation_merged(ax,4063, 14.46, 11.5, color_unlim, 3)
#plot_simulation_merged(ax,4219, 14.46, 16.23, color_unlim, 2)
plot_simulation_merged(ax,4375, 14.46, 18.2, color_unlim, 4)
plot_simulation_merged(ax,5000, 14.46, 24, color_unlim, 4, offset)
#plot_simulation_merged(ax,5000, 11.6, 14.3, color_unlim, 2)
plot_simulation_merged(ax,5000, 90, 90, color_unlim, 1, offset) # limited, but no ice at all
#plot_simulation_merged(ax,10000, 14.46, 18, color_unlim, 4)
ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])
ax.set_ylim(-0.1,1.1)
ax.set_xlabel("Atmospheric CO$_2$ [ppmv]",size=labelsize)
ax.set_ylabel("Ice-Edge Latitude [°]",size=labelsize)
plt.tick_params(axis='both', which='major', labelsize=ticksize)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.yaxis.tick_left()
ax.xaxis.tick_bottom()
ax.set_xscale('log')
ax.set_xticks(np.linspace(1000,10000,10) )
ax.set_xticklabels([1000, 2000,3000,4000,5000,'','','','',10000] )
ax.set_xlim(1000,5000)
ax.set_ylim(0,1)
# extra ticks at bifurcation points
#semtner_bif=1641
#semtner_5m_bif=1547
semtner_bif=1547
semtner_5m_bif=1469
ax.vlines([semtner_5m_bif],-0.04,-0.01,color=color_5m,lw=1,clip_on=False)
ax.vlines([semtner_bif],-0.04,-0.01,color=color_unlim,lw=1,clip_on=False)
#ax.axvline(semtner_bif,-20,0.1)
ax.annotate(semtner_bif,(semtner_bif,0.02),color=color_unlim,ha='center',clip_on=False)
ax.annotate(semtner_5m_bif,(semtner_5m_bif,0.1),xytext=(semtner_5m_bif,-0.05),color=color_5m,ha='center',va='top',clip_on=False)
ax.set_yticklabels([0,10,20,30,45,60,90])
legend_color(ax,["0L-Semtner","0L-Semtner-limited"],2)
if save_plot:
plt.savefig("plots/bifurcation_5mlim_merged.pdf")
```
%% Output
%% Cell type:code id: tags:
``` python
```
%% Cell type:code id: tags:
``` python
```
%% Cell type:code id: tags:
``` python
```
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