Describe the diurnal variation of cloud

Assignment Help Python Programming

Reference no: EM132291653

Homework - Data fitting

Problem 1 - So far in the Monte-Carlo radiative transfer code, we have been using the isotropic scattering phase function. The figure below shows the scattering phase function of water droplet for the scattering angle between 90~160 degree.

Now, suppose that you have obtained the scattering phase function at some coarse resolution (i.e., the blue dots in the figure). Use the 1) linear, 2) Lagrange and 3) cubic spline methods to interpolate and get high-angular resolution data at every 0.5 degree.

The data needed for this problem are in the .npy file. Use the Numpy.load function to load the data.

X_low = np.load(work_path+'scattering_angle_low.npy')

Y_low = np.load(work_path+'Phase_function_low.npy')

X_high = np.load(work_path+'scattering_angle_high.npy')

Y_high = np.load(work_path+'Phase_function_high.npy')

Where the work path is the working directory where you saved the data.

Problem 2 - Assume your Monte-Carlo radiative transfer code computes the cloud reflectances ("Ref") for several values of cloud optical thickness ("Tau"). See data below.

1) Use cubic spline method the interpolate the data.

2) Use the model Ref = Tau/(a+bTau) to fit the data, where a and b are two adjustable parameters. Find the optimal values for a and b.

3) Convert the second problem to a linear fitting problem.

Tau = np.array([ 0.299, 1.29400003 , 2.28900003 , 3.28399992, 4.27899981, 5.27399969 , 6.26900005 , 7.26399994, 8.25900078 , 9.25400066, 10.2490005, 11.2440004 , 12.2390003, 13.2340002 , 14.2290001, 15.2240009 , 16.2189999 , 17.2140007 ,18.2089996 , 19.2040005 ])

Ref = np.array([ 0.17678887, 0.48721159 , 0.62823123 , 0.70785129, 0.75912076, 0.79498094, 0.82153791, 0.84198004, 0.85822612, 0.87143803, 0.8823905, 0.89163792, 0.89952338, 0.90634716, 0.91229314 , 0.91752762, 0.92218465, 0.92633438, 0.93006754, 0.93343675])

Problem 3 - The file "Cloud_Fraction.npy" contains 4 years satellite observations of the diurnal variation of cloud fraction in the Southeast Atlantic region. As you can see, the cloud fraction has a strong diurnal cycle. This is primarily because increasing solar radiation leads to stronger cloud absorption that "burns" off cloud fraction.

Based on the cloud fraction data, develop a non-linear model to describe the diurnal variation of cloud in the Southeast Atlantic region. Print out the formula of your model and list all adjustable parameters. Plot the fitting result in the same figure with the original data.

To read the cloud fraction data use the command: cf = np.load('Cloud_Fraction.npy')

Note - Need help with this assignment in python 3.

Attachment:- Assignment Files.rar

Reference no: EM132291653

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len2291653

4/23/2019 9:52:33 PM

Instructions: I need help with this assignment in python 3. I need it to be as simple as possible and well commented. I will attach all the files needed along with the description. Use the 1) linear, 2) Lagrange and 3) cubic spline methods to interpolate and get high-angular resolution data at every 0.5 degree.

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