How I can plot Moisture Flux Divergence using python code(xarray)?

Kazi Redwan

Engr. Tufail

import xarray as xr

import numpy as np

import matplotlib.pyplot as plt

# Load the data

# Replace 'path_to_your_data' with the actual path to your netCDF files

ds = xr.open_dataset('path_to_your_data.nc')

# Extract variables (assuming the variable names are 'q', 'u', 'v')

q = ds['q']

u = ds['u']

v = ds['v']

# Calculate moisture fluxes

q_u = q * u

q_v = q * v

# Compute the divergence of the moisture flux

# Assuming regular latitude/longitude grid

# Calculate the gradient using numpy gradient which requires coordinates

lat = ds['lat'].values

lon = ds['lon'].values

# Convert lat/lon to radians for proper scaling

lat_rad = np.deg2rad(lat)

lon_rad = np.deg2rad(lon)

# Calculate dx and dy (assuming lat/lon are in degrees and uniformly spaced)

R = 6371000 # Radius of Earth in meters

dlat = np.gradient(lat_rad)

dlon = np.gradient(lon_rad)

dx = R * np.cos(lat_rad) * dlon # Distance between longitudes in meters

dy = R * dlat # Distance between latitudes in meters

# Use xarray's diff to compute finite differences (central difference)

q_u_diff_x = q_u.differentiate('lon') / dx

q_v_diff_y = q_v.differentiate('lat') / dy

# Moisture Flux Divergence

mfd = q_u_diff_x + q_v_diff_y

# Plot the result

plt.figure(figsize=(10, 6))

mfd.plot()

plt.title('Moisture Flux Divergence')

plt.xlabel('Longitude')

plt.ylabel('Latitude')

plt.show()

Kazi Redwan

Explanation:

Data Loading:

The xr.open_dataset function loads the netCDF data into an xarray.Dataset.

2. Moisture Flux Calculation:

The specific humidity is multiplied by the zonal and meridional winds to get the moisture flux components.

3. Divergence Calculation:

The spatial gradients of the moisture flux components are computed using finite differences. xarray's differentiate function calculates the derivatives.

4. Plotting:

The plot function from xarray is used to create a plot of the moisture flux divergence.

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