80 lines
1.8 KiB
Python
80 lines
1.8 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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### Properties ###
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steps = 100
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# Data
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T_data = np.array([265, 255, 245, 235, 225, 215])
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il_data = np.array([75, 60, 45, 30, 15, 0])
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albedo_data = np.array([0.15, 0.25, 0.35, 0.45, 0.55, 0.65])
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# Ice latitude
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m1, b1 = np.polyfit(T_data, il_data, 1)
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def calc_ice_latitude(T):
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return m1 * T + b1
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# Planetary albedo
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m2, b2 = np.polyfit(T_data, albedo_data, 1)
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def calc_albedo(T):
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return np.clip(m2 * T + b2, 0, 1)
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### Constants and Data ###
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epsilon = 1
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sigma = 5.67E-8 # W/m2 K4
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### Energy balance equation ###
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def calc_temperature(albedo, L):
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return pow((L * (1 - albedo)) / (4 * epsilon * sigma), 1/4)
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### Iteration step ###
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def iterate(L, initial_albedo, steps):
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T = calc_temperature(initial_albedo, L)
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for i in range(steps):
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albedo = calc_albedo(T)
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new_T = calc_temperature(albedo, L)
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T = new_T
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return T, albedo
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### Loop ###
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l_range_bounds = [ 1200, 1600 ]
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current_albedo = 0.15
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temp_down = []
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l_range_down = []
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L = l_range_bounds[1]
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while L > l_range_bounds[0]-1:
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T, current_albedo = iterate(L, current_albedo, steps)
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temp_down.append(T)
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L = L - 10
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l_range_down.append(L)
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current_albedo = 0.65
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temp_up = []
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l_range_up = []
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L = l_range_bounds[0]
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while L < l_range_bounds[1]+1:
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T, current_albedo = iterate(L, current_albedo, steps)
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temp_up.append(T)
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L = L + 10
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l_range_up.append(L)
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### Input ###
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# L, albedo, nIters = input("").split()
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# L, albedo, nIters = [ float(L), float(albedo), int(nIters) ]
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# T, albedo = iterate(L, albedo, nIters)
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# print(T, " ", albedo)
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### Plot hysteresis ###
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plt.plot(l_range_down, temp_down, label="Cooling")
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plt.plot(l_range_up, temp_up, label="Warming")
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plt.xlabel("Solar Constant (L)")
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plt.ylabel("Equilibrium Temperature (K)")
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plt.legend()
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plt.show() |