Difference between revisions of "Modify start Files"
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== Using Python scripts == | == Using Python scripts == | ||
− | We have developed Python routines to easily | + | We have developed Python routines to easily modify ''start.nc'' and ''startfi.nc'' files. This requires the use of the xarray library. |
− | + | In the examples below, we modify the ''startfi.nc'' file to apply fixed (= isothermal) surface temperatures across the planet. | |
+ | |||
+ | |||
+ | * Create file ''start_archive.nc'' with ''start2archive.e'' compiled at grid resolution 64×48×32 using old file ''z2sig.def'' used previously | ||
+ | * Create files ''restart.nc'' and ''restartfi.nc'' with ''newstart.e'' compiled at grid resolution 32×24×25, using a new file ''z2sig.def'' (more details below on the choice of the ''z2sig.def''). | ||
+ | * While executing ''newstart.e'', you need to choose the answer '0 - from a file start_archive' and then press enter to all other requests. | ||
<syntaxhighlight lang="python"> | <syntaxhighlight lang="python"> |
Revision as of 15:41, 7 November 2023
Here we present a simple tutorial to change the initial conditions used in the Generic PCM.
The initial conditions are stored in the start.nc and startfi.nc netCDF files, which are read by the Generic PCM.
To modify the initial conditions, you must modify the start.nc and startfi.nc files.
Two options are available to do that:
Using newstart.e routine
A few options to do that:
- use existing topographic data for solar system objects. We have already formatted the data for most solar system objects, so please ask someone in the team if your topography map is not already here: https://web.lmd.jussieu.fr/~lmdz/planets/LMDZ.GENERIC/datagcm/surface_data/
- use your own data files
You can also derive data files by digitalizing images. See below an example:
from numpy import *
import numpy as np
import matplotlib.pyplot as mpl
import math
from PIL import Image
# Here we first digitalize a png image name "rico_topography.png"
image = Image.open('rico_topography.png') # For simplicity, we work here in a 360 longitude pixels x 180 latitude pixels
pix = image.load()
image_width, image_height = image.size
topography_data=np.zeros((image_width, image_height),dtype='f')
# Here we convert the pixels into some rules for the elevation map
for i in range(0,image_width,1):
for j in range(0,image_height,1):
if(pix[i,j][0]<1. and pix[i,j][1]<1. and pix[i,j][2]<1.):
topography_data[i,j]=5.
else:
topography_data[i,j]=0.
# Here we write the topography map into an ascii file
name_file='rico_topography.txt'
with open(name_file, 'w') as f1:
for j in range(0,image_height,1):
for i in range(0,image_width-1,1):
print("{:12.5e}".format(topography_data[i,j]),file=f1,end=' ')
print("{:12.5e}".format(topography_data[image_width-1,j]),file=f1,end='\n')
This requires the use of the PIL library, and the rico_topography.png file.
Using Python scripts
We have developed Python routines to easily modify start.nc and startfi.nc files. This requires the use of the xarray library.
In the examples below, we modify the startfi.nc file to apply fixed (= isothermal) surface temperatures across the planet.
- Create file start_archive.nc with start2archive.e compiled at grid resolution 64×48×32 using old file z2sig.def used previously
- Create files restart.nc and restartfi.nc with newstart.e compiled at grid resolution 32×24×25, using a new file z2sig.def (more details below on the choice of the z2sig.def).
- While executing newstart.e, you need to choose the answer '0 - from a file start_archive' and then press enter to all other requests.
from numpy import *
import numpy as np
import matplotlib.pyplot as mpl
import math
import xarray as xr
# 1. WE GET THE SURFACE TOPOGRAPHY DATA
nc = xr.open_dataset('surface_mars.nc',decode_times=False) # can be any netcdf file (e.g. start/startfi.nc files)
# 2. WE READ THE VARIABLES
lat=nc['latitude']
lon=nc['longitude']
albedo=nc['albedo']
thermal_inertia=nc['thermal']
elevation=nc['zMOL']
# BELOW THE VARIABLES WE WANT TO UPDATE
new_elevation = np.empty((len(lat),len(lon)))
new_thermal_inertia = np.empty((len(lat),len(lon)))
new_albedo = np.empty((len(lat),len(lon)))
# LOOP TO MODIFY THE VARIABLES
# EXAMPLE 1 - CUSTOM TOPOGRAPHY
rico_topography=np.loadtxt('rico_topography.txt') # 360 lon x 180 lat
for i in range(0,len(lat),1):
for j in range(0,len(lon),1):
if(rico_topography[i,j]>1.):
new_elevation[i,j]=rico_topography[i,j] # here you put whatever you want ; in this example, we use the topography data of rico_topography.txt
new_albedo[i,j]=0.5 # here you put whatever you want ; we put high albedo because RICO is so bright his albedo must be high
new_thermal_inertia[i,j]=2000. # here you put whatever you want
else:
new_elevation[i,j]=0. # here you put whatever you want
new_albedo[i,j]=0.2 # here you put whatever you want
new_thermal_inertia[i,j]=500. # here you put whatever you want
# EXAMPLE 2 - MARS WITH AN OCEAN
"""for i in range(0,len(lat),1):
for j in range(0,len(lon),1):
new_elevation[i,j]=max(elevation[i,j],-3.9) # here you put whatever you want ; in this example, we take the (MOLA) topography of present-day Mars and modify it to fill the topographic depressions with an ocean at an altitude of -3.9km
new_albedo[i,j]=albedo[i,j] # here you put whatever you want
new_thermal_inertia[i,j]=thermal_inertia[i,j] # here you put whatever you want"""
# SANITY CHECK PLOTS
fig1 = mpl.figure(1)
mpl.contourf(lon,lat,elevation)
mpl.xlabel('longitude (deg)')
mpl.ylabel('latitude (deg)')
mpl.show()
fig2 = mpl.figure(2)
mpl.contourf(lon,lat,new_elevation)
mpl.xlabel('longitude (deg)')
mpl.ylabel('latitude (deg)')
mpl.show()
# CREATE THE NEW NETCDF TOPOGRAPHY FILE
nc['albedo'].values = new_albedo
nc['zMOL'].values = new_elevation
nc['thermal'].values = new_thermal_inertia
nc.to_netcdf('new_topography.nc')