File:Ocean planet temperature S 93 percent co2 120ppm 1 r 1.png

#
## temperatures, if S=0.93*S0
## sun radiation down 7% from current.
# python3/climlab code
#
# 23.10.2023 0000.0004e
#

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm

import climlab
from climlab import constants as const
from climlab.process.diagnostic import DiagnosticProcess
from climlab.domain.field import Field, global_mean



def plot_temp_section(model, timeave=True):
    fig = plt.figure()
    ax = fig.add_subplot(111)
    #viridis = cm.get_cmap('jet')
    #viridis = cm.get_cmap('turbo')
    #viridis = cm.get_cmap('winter')
    viridis = cm.get_cmap('cool_r')
    #viridis = cm.get_cmap('PuBu')
    plt.set_cmap(viridis)
    if timeave:
        field = model.timeave['Tatm'].transpose()
    else:
        field = model.Tatm.transpose()
    levels1=[-90,-80,-70,-60,-50,-40,-30,-20,-10,0,10,20,30,40,50,60,70,80,90,100]
    cax = ax.contourf(model.lat, model.lev,field-273.15, levels=200)
    CS = ax.contour(model.lat, model.lev,field-273.15,levels=levels1,
                 colors='k'  # negative contours will be dashed by default
                 )
    ax.clabel(CS,fmt='%1.1f',fontsize=14, inline=1)
    ax.invert_yaxis()
    ax.set_title("Temperature profile", fontsize=18)
    ax.set_xlabel("Latitude", fontsize=15)
    ax.set_ylabel("Pressure", fontsize=15)
    ax.xaxis.set_tick_params(labelsize=14)
    ax.yaxis.set_tick_params(labelsize=14)
    ax.set_xlim(-90,90)
    ax.set_xticks([-90, -60, -30, 0, 30, 60, 90])
    #cbar1=fig.colorbar(cax)
    #cbar1.ax.tick_params(labelsize=15)

class tanalbedo(DiagnosticProcess):

    def __init__(self, **kwargs):
        super(tanalbedo, self).__init__(**kwargs)

        self.add_diagnostic('albedo')
        Ts = self.state['Ts']
        self._compute_fixed()

    def _compute_fixed(self):
        Ts = self.state['Ts']
        try:
            lon, lat = np.meshgrid(self.lon, self.lat)
        except:
            lat = self.lat
        phi = lat

        try:
            albedo=np.zeros(len(phi));
            albedo=0.42-0.20*np.tanh(0.052*(Ts-3))

        except:
            albedo = np.zeros_like(phi)

        dom = next(iter(self.domains.values()))
        self.albedo = Field(albedo, domain=dom)

    def _compute(self):
        self._compute_fixed()

        return {}



############## main code

num_years=40

rau=1.0 ## planet a au
S1_base=1361.5 ## current
#insok=1/(rau*rau) ## insolation coefficient"
insok=0.93  ## OK 0.93
#insok=1.0

albedo=0.3 ## constant albedo OK , but not stepper
#albedo=0.06
#co2=1*120/1e6
#co2=180/1e6
co2=120/1e6

waterdepth1=50 

cloudiness=0.5
waterdepth=10

S1_abs=S1_base*insok


title1='Temperatures throughout the year deg C. S='+str(round(insok,3))+" CO2="+str(co2*1e6)


orbit1={'ecc': 0.0167643, 'long_peri': 280.32687, 'obliquity': 23.459277, 'S0':S1_abs}

print(rau, insok)

## not used
delta_t = 60. * 60. * 24. * 30

absorber_vmr = {'CO2':co2,
                'CH4':1./1e9,
                'N2O':1./1e9,
                'O2':0.25,
                'CFC11':1./1e9,
                'CFC12':1./1e9,
                'CFC22':1./1e9,
                'CCL4':1./1e9,
                'O3':1./1e9}

#state = climlab.column_state(num_lev=20, num_lat=1, water_depth=5.)
state = climlab.column_state(num_lev=8, num_lat=16, water_depth=waterdepth)

insol = climlab.radiation.DailyInsolation(name='Insolation', 
                                          domains=state['Ts'].domain, S0=S1_abs, orb=orbit1)
insol.S0=S1_abs




h2o = climlab.radiation.ManabeWaterVapor(state=state, relative_humidity=1.0)



rad = climlab.radiation.CAM3(name='Radiation', state=state,
return_spectral_olr=True,
icld=cloudiness,
S0 = S1_abs,
insolation=insol.insolation,
coszen=insol.coszen,
absorber_vmr = absorber_vmr,
albedo=albedo
)

print(insol.S0)







conv = climlab.convection.ConvectiveAdjustment(name='Convective Adjustment',state=state, adj_lapse_rate=6.5)


rcm = climlab.couple([insol, rad,conv,h2o], name='RCM')

surface = rcm.domains['Ts']

rcm.water_depth=waterdepth1
rcm.Tf=10

#quit(-1)


#rad.a0=albedo

## WARNING DYNAMIC ALBEDO NOK
rcm.remove_subprocess('albedo')

#alb = climlab.surface.albedo.StepFunctionAlbedo(state=rcm.state, Tf=-10, **rcm.param)
#alb = climlab.surface.albedo.ConstantAlbedo(domains=surface, **rcm.param)
#alb.albedo[:]=albedo

#alb = tanalbedo(state=rcm.state, **rcm.param)
#rcm.add_subprocess('albedo', alb)



#print (alb.diagnostics)

#quit(-1)

print(" Integrate ...")

rcm.integrate_years(1)

#  Create and exact clone of the previous model
diffmodel = climlab.process_like(rcm)

diffmodel.name = 'Seasonal RCE with heat transport'

# thermal diffusivity in W/m**2/degC
#D = 0.05
D=0.0001

# meridional diffusivity in m**2/s
K = D / diffmodel.Tatm.domain.heat_capacity[0] * const.a**2
print("K ", K)
d = climlab.dynamics.MeridionalDiffusion(K=K, state={'Tatm': diffmodel.Tatm}, **diffmodel.param)
diffmodel.add_subprocess('Meridional Diffusion', d)

#diffmodel = climlab.couple([rad,conv,h2o, insol,d], name='Seasonal diffmodel')

print(diffmodel)

#diffmodel.integrate_years(1)

diffmodel.integrate_years(num_years)

#diffmodel.integrate_converge()


tatm2=state['Tatm']-273.15

print(tatm2)

print("Plot ")

#plot_temp_section(rcm, timeave=True)

#plot_temp_section(diffmodel, timeave=True)

#plot_temp_section(diffmodel, timeave=True)

tlayer1=tatm2[...,7].ravel()
tlayer2=tatm2[...,7].ravel()

#print (" Tatmlen",len(tlayer1))

tlayer1=np.nan_to_num(tlayer1)
tlayer2=np.nan_to_num(tlayer2)

meantemp=np.mean(tlayer1)
meantemp2=np.mean(tlayer2)

print(tlayer1)
print(tlayer2)

print(" meantemp A ",meantemp)
print(" meantemp B ",meantemp2)

#fig, ax = plt.subplots(dpi=100)

#state['Tatm'].to_xarray().plot(ax=ax, y='lev', yincrease=False)

#state['Tatm'].to_xarray().plot(ax=ax,x='lat', y='lev', yincrease=False)

tatm=state['Tatm']-273.15

rcm=diffmodel

years=1
num_steps_per_year = int(rcm.time['num_steps_per_year'])
Tyear = np.empty((rcm.lat.size, num_steps_per_year*years))
for m in range(num_steps_per_year*years):
     rcm.step_forward()
     Tyear[:,m] = np.squeeze(rcm.Ts)

Tmin=np.min(Tyear)
Tmax=np.max(Tyear)
tmean1=np.mean(Tyear[:,:])
print("Tmean ", tmean1-273.15)
print("Tmin ", Tmin-273.15)
print("Tmax ", Tmax-273.15)  

fig = plt.figure(figsize=(5,5))
ax = fig.add_subplot(111)
       
factor = 365. / num_steps_per_year
#cmap1=plt.cm.seismic
#cmap1=plt.cm.winter
#cmap1=plt.cm.cool_r
cmap1=plt.cm.cool
#cmap1=plt.cm.seismic
#cmap1=plt.cm.RdYlBu_r
#cmap1=plt.cm.turbo_r
cmap1=plt.cm.jet
        
#cmap1=cmap1.reversed()      
#levels1=[-80,-70,-60,-50,-40,-30]
levels2=[-250,-200,-150,-100,-80,-70,-65,-60,-55,-50,-45,-40,-35,-30,-20,-10,0,5,10,15,20,25,30,35,40,45,50,60,80,90,100,120,150,200,250,300,500,1000,2000,4000]
cax = ax.contourf(factor * np.arange(num_steps_per_year*(years-1), num_steps_per_year*years),
    rcm.lat, Tyear[:,:]-273.15, 
    cmap=cmap1, vmin=-100, vmax=100, levels=255)
cs1 = ax.contour(factor * np.arange(num_steps_per_year*(years-1),num_steps_per_year*years),
    rcm.lat, Tyear[:,:]-273.15, 
    colors='#00005f', vmin=Tmin, vmax=Tmax, levels=levels2)
ax.clabel(cs1, cs1.levels, inline=True, fontsize=14)                     
#cbar1 = plt.colorbar(cax)

ax.set_title(title1, fontsize=18)
ax.tick_params(axis='x', labelsize=12)
ax.tick_params(axis='y', labelsize=12)
ax.set_xlabel('Days of year', fontsize=13)
ax.set_ylabel('Latitude', fontsize=13)
plt.show()

#plt.savefig('1000dpi.png', dpi=1000)
#print(rcm)
#quit(-1)

#plot_temp_section(rcm, timeave=True)

#plt.imshow(tatm)

#ax.set_xlabel("Temperature (K)")
#ax.set_ylabel("Pressure (hPa)")
#ax.grid()

#plt.plot()

#plt.show()