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File:Planet that has 90 obliquity temperature through the year 2 1 1 1.png

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Planet that has 90 obliquity - temperature through the year

Summary

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Description
English: Planet that has 90 obliquity - temperature through the year
Date
Source Own work
Author Merikanto

Python3 source code

    1. temperatures, if S=0.93*S0
    2. sun radiation down 7% from current.
  2. python3/climlab code
  4. 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 {}
                            1. main code

num_years=1

rau=1.0 ## planet a au S1_base=1361.5 ## current

  1. insok=1/(rau*rau) ## insolation coefficient"

insok=1 ## OK 0.93

  1. insok=1.0

albedo=0.3 ## constant albedo OK , but not stepper

  1. albedo=0.06
  2. co2=1*120/1e6
  3. co2=180/1e6

co2=280/1e6

  1. ecc= 0.0167643
  2. long_peri=280.32687
  3. obliquity=23.459277

ecc=0.0 long_peri=0 obliquity=90

waterdepth1=50

cloudiness=0.0 waterdepth=10

S1_abs=S1_base*insok

title1='Temperatures throughout the year deg C. \n S='+str(round(insok,3))+" ecc="+str(round(ecc,3))+" long_peri="+str(round(long_peri,1)) +" tilt="+str(round(obliquity,2))+ "\n CO2="+str(co2*1e6)

  1. orbit1={'ecc': 0.0167643, 'long_peri': 280.32687, 'obliquity': 23.459277, 'S0':S1_abs}
  1. orbit1={'ecc': 0.3, 'long_peri': 0, 'obliquity': 60, 'S0':S1_abs}

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

print(rau, insok)

    1. not used

delta_t = 60. * 60. * 24. * 30

absorber_vmr = {'CO2':co2, 

               'CH4':800./1e9,
               'N2O':100./1e9,
               'O2':0.21,
               'CFC11':1./1e9,
               'CFC12':1./1e9,
               'CFC22':1./1e9,
               'CCL4':1./1e9,
               'O3':1./1e6}
  1. 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)
  1. 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)

print (insol.coszen)

  1. quit(-1)

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

  1. quit(-1)
  1. rad.a0=albedo
    1. WARNING DYNAMIC ALBEDO NOK

rcm.remove_subprocess('albedo')

  1. alb = climlab.surface.albedo.StepFunctionAlbedo(state=rcm.state, Tf=-10, **rcm.param)
  2. alb = climlab.surface.albedo.ConstantAlbedo(domains=surface, **rcm.param)
  3. alb.albedo[:]=albedo
  1. alb = tanalbedo(state=rcm.state, **rcm.param)
  2. rcm.add_subprocess('albedo', alb)
  1. print (alb.diagnostics)
  1. quit(-1)

print(" Integrate ...")

rcm.integrate_years(1)

  1. Create and exact clone of the previous model

diffmodel = climlab.process_like(rcm)

diffmodel.name = 'Seasonal RCE with heat transport'

  1. thermal diffusivity in W/m**2/degC
  2. D = 0.05

D=0.0001

  1. 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)

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

print(diffmodel)

  1. diffmodel.integrate_years(1)

diffmodel.integrate_years(num_years)

  1. diffmodel.integrate_converge()

tatm2=state['Tatm']-273.15

print(tatm2)

print("Plot ")

  1. plot_temp_section(rcm, timeave=True)
  1. plot_temp_section(diffmodel, timeave=True)
  1. plot_temp_section(diffmodel, timeave=True)

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

  1. 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)

  1. fig, ax = plt.subplots(dpi=100)
  1. state['Tatm'].to_xarray().plot(ax=ax, y='lev', yincrease=False)
  1. 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

  1. cmap1=plt.cm.seismic
  2. cmap1=plt.cm.winter
  3. cmap1=plt.cm.cool_r
  4. cmap1=plt.cm.cool
  5. cmap1=plt.cm.seismic
  6. cmap1=plt.cm.RdYlBu_r
  7. cmap1=plt.cm.turbo_r
  8. cmap1=plt.cm.jet

cmap1=plt.cm.coolwarm

  1. cmap1=cmap1.reversed()
  2. 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', alpha=0.5, vmin=Tmin, vmax=Tmax, levels=levels2)

ax.clabel(cs1, cs1.levels, inline=True, fontsize=14)

  1. cbar1 = plt.colorbar(cax)

ax.set_title(title1, fontsize=14) 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()

  1. plt.savefig('1000dpi.png', dpi=1000)
  2. print(rcm)
  3. quit(-1)
  1. plot_temp_section(rcm, timeave=True)
  1. plt.imshow(tatm)
  1. ax.set_xlabel("Temperature (K)")
  2. ax.set_ylabel("Pressure (hPa)")
  3. ax.grid()
  1. plt.plot()
  1. plt.show()

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I, the copyright holder of this work, hereby publish it under the following license:
Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

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