Python Forum

Dear all, I have two dataset, both of which contains precipitation rate. However, one of the dataset (ldasin) requires computation in order to get the hourly precipitation rate and plot them. Basically, it needs to be computed in this manner: ldasin.RAINC(time=time) + (time=time) ldasin.RAINNC - ldasin.RAINC (time=time-1) - ldasin.RAINNC(time=time-1). Afterwards, it can the be used in the ldasin_avg in order to get the mean. I've only ever tried the formula in GRADS and it worked since I can just directly input the timestep.

Thank you!

Below is the code that I used.

%matplotlib inline
import xarray as xr
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

ldasin = xr.open_mfdataset('/home/ES403/MODEL/WRF-HYDRO/TEMPLATE/FORCING/*wrfout*', concat_dim='Time')

supp_precip = xr.open_mfdataset('/home/ES403/MODEL/WRF-HYDRO/TEMPLATE/FORCING/*PRECIP*', concat_dim='Time')

ldasin_avg = ldasin.RAINRATE.mean(dim=('south_north','west_east'))*3600
supp_avg = supp_precip.precip_rate.mean(dim=('south_north','west_east'))*3600
fig, axes = plt.subplots(ncols=1,figsize=(12, 6))
plt.suptitle('Hyetograph of the WRF and supplied precipitation',fontsize=24)
ldasin_avg.plot(label='WRF', color='black', linestyle='-')
supp_avg.plot(label='GSMaP', color='blue', linestyle='-')
plt.legend()
plt.show()