India Meteorological Department (IMD) grided data to GeoTIFF

India Meteorological Department (IMD) grided data to GeoTIFF

Saswata Nandi and Pratiman Patel, 06 October 2020

2 min read.

Update [27 Feb 2021]

For latest documentation, please visit https://imdlib.readthedocs.io/en/latest/

Now, you can convert the IMD dataset to GeoTIFF using data.to_geotiff('test.tif', file_dir).

Description

IMDLIB is a python package to download and handle binary grided data from India Meteorological Department (IMD). For more information about the IMD datasets, follow the following link: http://imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html

Installation

IMDLIB can be installed via pip. It is tested for both Windows and Linux platforms with 64-bit architecture only.

pip install imdlib

Downloading data from IMD

IMDLIB is capable of downloading gridded rainfall and temperature data (min and max). Here is an example of downloading rainfall dataset from 2010 to 2018.

import imdlib as imd

# Downloading 8 years of rainfall data for India
start_yr = 2010
end_yr = 2018
variable = 'rain' # other options are ('tmin'/ 'tmax')
file_dir = (r'C:\Users\imdlib\Desktop\\') #Path to save the files
imd.get_data(variable, start_yr, end_yr, fn_format='yearwise', file_dir=file_dir)

# Opeining the downloaded dataset
data = imd.open_data(variable, start_yr, end_yr,'yearwise', file_dir)

Output:

Downloading: rain for year 2010
Downloading: rain for year 2011
Downloading: rain for year 2012
Downloading: rain for year 2013
Downloading: rain for year 2014
Downloading: rain for year 2015
Downloading: rain for year 2016
Downloading: rain for year 2017
Downloading: rain for year 2018
Download Successful !!!

Processing with xarray

ds = data.get_xarray()
ds 

Output:

<xarray.DataArray 'rain' (lat: 129, lon: 135, time: 3287)>
...
...
...
Coordinates:
  * lat      (lat) float64 6.5 6.75 7.0 7.25 7.5 ... 37.5 37.75 38.0 38.25 38.5
  * lon      (lon) float64 66.5 66.75 67.0 67.25 67.5 ... 99.25 99.5 99.75 100.0
  * time     (time) datetime64[ns] 2010-01-01 2010-01-02 ... 2018-12-31
Attributes:
    long_name:  rainfall
    units:      mm/day

Saving to GeoTIFF

import rioxarray as rio

#Set the CRS:
pr = ds.rio.set_crs("epsg:4326")

# Transpose according to GeoTIFF conventions:
pr = pr.transpose('time', 'lat', 'lon')

#Define lat/long 
pr = pr.rio.set_spatial_dims('lon', 'lat')

#Saving the file
pr.rio.to_raster(r"C:\Users\imdlib\Desktop\IMD_Rain_2010_2018.tif")
If you would like to provide any suggestions to this post. Kindly email me at pratiman_patel@hotmail.com

⇠ IMDLIB, A python package to download and handle binary grided data from India Meteorological Department (IMD)

Getting started with Python and IMDLIB ⇢