How to Download and Convert IMD Gridded Binary Weather Data

You can download IMD data using Python ide (pycharm) or you can use the Python plugin of QGIS.

In this tutorial, we use QGIS (View and cite related Research)

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Step 1: Set Windows Execution Policy

  1. From the start menu search ‘Windows PowerShell’
  2. Right Click on it and ‘Run as administrator ‘
  3. In the console type or copy and paste the following command and press Enter
Set-ExecutionPolicy Unrestricted

Now type ‘A’ and press Enter.

Step 2: Run ‘Python Console’ in QGIS

  1. Open QGIS and in the plugins option click on ‘Python Console’.
  2. Open editor

Step 3: Command for downloading the data

Note:

  1. This command will download the data for the whole India (you can change the X and Y values for the desired location)
  2. The default resolution is 0.25 for rain and 1 for tmin and tmax (you can change it as per your requirement)
  3. For different parameters change the variable from ‘rain’ to ‘tmin’ or ‘tmax’.
  4. Change the start year and end year as per your requirement, currently, it is 2011-2021.
import imdlib as imd
import numpy as np
import pandas as pd
""" 
# install imdlib python library
# you should be connected to internet for downloading the data
#-9999 value is for no data in saved csv file
# This code will download the imd data first and then convert the data to csv file
if you have data already downloaded then create folder named rain/tmax/tmin inside any folder and 
copy yearly data files in the respective folder and rename yearly data file as year name i.e 1951.GRD 1952.GRD etc and 
comment the line imd.get_data(variable,start_yr) and run the code it will convert the binary .GRD data into csv file
"""
start_yr = 2011 # give starting year from which you want to download/convert data: 1901 ownwards for rainfall, 1951 for tmax and tmin
end_yr = 2021 # give ending year upto which you want to download/convert data
variable = 'rain' # give variable name (rain for rainfall, tmax or tmin for min or max temperature)
file_format = 'yearwise' # other option (None), which will assume deafult imd naming convention
imd.get_data(variable, start_yr, end_yr, fn_format='yearwise', file_dir='E:/data/') # download IMD data: just change path as per your requirement
file_dir = 'E:/data/' # this path should be same as mentioned in previous line
data = imd.open_data(variable, start_yr, end_yr,'yearwise', file_dir) # this will open the data downloaded and saved in the location mentioned in previous line
if variable == 'rain':
    grid_size = 0.25 # grid spacing in deg
    y_count = 129 # no of grids in y direction
    x_count = 135 # no of grids in x direction
    x = 66.5 # starting longitude taken from control file (.ctl)
    y = 6.5 # starting latitude taken from control file (.ctl)
elif variable == 'tmax' or variable == 'tmin':
    grid_size = 1 # grid spacing in deg
    y_count = 31 # no of grids in y direction
    x_count = 31 # no of grids in x direction
    x = 67.5 # starting longitude taken from control file (.ctl)
    y = 7.5 # starting latitude taken from control file (.ctl)
#print(grid_size,x_count, y_count, x, y)
data
data.shape
np_array = data.data
#print(np_array[0,0,0])
#xr_objecct = data.get_xarray()
#type(xr_objecct)
#xr_objecct.mean('time').plot()
years_no = (end_yr - start_yr) + 1
#print(years_no)
day = 0
for yr in range(0,years_no):
    f = open("E:/data/"+str(start_yr+yr)+"_"+str(variable)+".csv",'w') # just change the path where you want to save csv file
    if ((start_yr+yr) % 4 == 0) and ((start_yr+yr) % 100 != 0):  # check for leap year
        days = 366
        count = yr + days
    elif ((start_yr+yr) % 4 == 0) and ((start_yr+yr) % 100 == 0) and ((start_yr+yr) % 400 == 0):
        days = 366
        count = yr + days
    else:
        days = 365
        count = yr + days
    day = day + days
    f.write("X,Y,")
    for d in range(0, days):
        f.write(str(d+1))
        f.write(",")
    f.write("\n")
    #print(np_array[364,0,0])
    for j in range(0, y_count):
        for i in range(0, x_count):
            f.write(str((i * grid_size) + x))
            f.write(",")
            f.write(str((j * grid_size) + y))
            f.write(",")
            time = 0
            for k in range(day-days, day):
                val = np_array[k,i,j]
                if val == 99.9000015258789 or val == -999:
                    f.write(str(-9999))
                    f.write(",")
                else:
                    f.write(str(val))
                    f.write(",")
            f.write("\n")
    print("File for " + str(start_yr + yr) + "_" + str(variable) + " is saved")
print("CSV conversion successful !")

Easier Method: Download IMD weather data using Google Colab

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