ECSimpleSnow component

ECSimpleSnow is an empirical algorithm to melt snow according to the surface temperature and increase snow depth according to the precipitation that has fallen since the last time step.

Details:

Brown, R. D., Brasnett, B., & Robinson, D. (2003). Gridded North American monthly snow depth and snow water equivalent for GCM evaluation. Atmosphere-Ocean, 41(1), 1-14.

URL: https://www.tandfonline.com/doi/abs/10.3137/ao.410101

Source code in Fortran:

URL: https://github.com/permamodel/Snow_BMI_Fortran

For this Notebook

Before you begin, install:

conda install -c conda-forge pymt pymt_ecsimplesnow numpy scipy

load module



In [1]:

    
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit

# Load PyMT model(s)
import pymt.models
ec = pymt.models.ECSimpleSnow()









    



➡ models: FrostNumber, Ku, Hydrotrend, ECSimpleSnow, Cem, Waves

load example configuration and inputs



In [2]:

    
#Call setup to get default config and data files.
defaults = ec.setup('.')
print(defaults)

cfg_filename = defaults[0]

%cat $cfg_filename

initialize by using default example data



In [10]:

    
# Initialize the model with the defaults.
ec.initialize('snow_model.cfg')
ec.set_value('snow_class',2)
ec.set_value('open_area_or_not', 1)

# List input and output variable names.
print(ec.get_output_var_names())
print(ec.get_input_var_names())









    



('snowpack__depth', 'snowpack__mass-per-volume_density')
('precipitation_mass_flux', 'land_surface_air__temperature', 'precipitation_mass_flux_adjust_factor', 'snow_class', 'open_area_or_not', 'snowpack__initial_depth', 'snowpack__initial_mass-per-volume_density')

Implement the simple snow model for the first year as an example



In [12]:

    
plt.figure(figsize=[4,9])
h0 = plt.subplot(3,1,1)
h1 = plt.subplot(3,1,2)
h2 = plt.subplot(3,1,3)

h0.title.set_text('Snow Depth')
h1.title.set_text('Snow Density')
h2.title.set_text('Air Temperature')

print('Air Temperature Unit:', ec.get_var_units('land_surface_air__temperature'))
print('Snow Depth Unit:'     , ec.get_var_units('snowpack__depth'))
print('Snow Density Unit:'   , ec.get_var_units('snowpack__mass-per-volume_density'))

for i in np.arange(365):
    
    ec.update()
    
    tair  = ec.get_value('land_surface_air__temperature')    
    snd   = ec.get_value('snowpack__depth', units='m')
    rsn   = ec.get_value('snowpack__mass-per-volume_density')
    
    units = ec.get_var_units('snowpack__depth')
    
    h0.scatter(ec.time, snd, c='k')    
    h1.scatter(ec.time, rsn, c='k')
    h2.scatter(ec.time,tair, c='k')
    
    
# ec.finalize()









    



Air Temperature Unit: C
Snow Depth Unit: cm
Snow Density Unit: kg per m3

Comparison with Observations at Barrow



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