Just putting this here for posterity. So a few months back I had asked for 
state-wise long-period averages for the monsoon season.
So with the monsoon season over, have been able to note down the averages 
from IMD's rainfall pdf (attached).
Am also pasting it below.

*state_name 1971_2020_normal (mm)*
Andaman & Nic. 1631.7
Andhra Pradesh 521.6
Arunachal Pr. 1675.1
Assam 1479.1
Bihar 992.2
Chandigarh 844.9
Chhattisgarh 1132.2
Delhi 544.3
DN Haveli, Diu 2206.5
Goa 3007.7
Gujarat 711.9
Haryana 426
Himachal Pr. 734.4
Jammu & Kash. 549.1
Jharkhand 1022.9
Karnataka 831.8
Kerala 2018.6
Ladakh 22.3
Lakshadweep 1026.6
Madhya Pradesh 949.5
Maharashtra 994.5
Manipur 1038.8
Meghalaya 2695.3
Mizoram 1626.1
Nagaland 1038.8
Odisha 1150.2
Puducherry 418
Punjab 439.8
Rajasthan 435.6
Sikkim 1672.9
Tamil Nadu 328.4
Telangana 734.8
Tripura 1391.1
Uttar Pradesh 746.2
Uttarakhand 1162.7
West Bengal 1344.2

-shijith

On Tuesday, 20 June 2023 at 18:53:34 UTC+5:30 Shijith Kunhitty wrote:

Thanks for this Ujaval, only thing is that I'm doing this for a media 
publication, so it's important to use the same long-period averages the IMD 
uses. If it was for my personal projects, I wouldn't have minded 
calculating them myself, but have to go by official figures now :(

On Tuesday, 20 June 2023 at 17:44:41 UTC+5:30 Ujaval Gandhi wrote:

The IMD gridded rainfall data is available from 1901-2022 
https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_NetCDF.html 
<https://mailtrack.io/trace/link/b238ccfa64f789701a1ca7af3b54a5e3e24d7dcd?url=https%3A%2F%2Fwww.imdpune.gov.in%2Fcmpg%2FGriddata%2FRainfall_25_NetCDF.html&userId=8747767&signature=ce9e45137af369df>

There's a python package 'imdlib' to read and convert this data to XArray. 
I have used this in the past to process the data.
https://github.com/spatialthoughts/projects/blob/master/imd/imd_annual_average.ipynb
 
<https://mailtrack.io/trace/link/ac0912ca419d6e7594c567ca44e4d94d2efdf8a5?url=https%3A%2F%2Fgithub.com%2Fspatialthoughts%2Fprojects%2Fblob%2Fmaster%2Fimd%2Fimd_annual_average.ipynb&userId=8747767&signature=b02d82c756801e30>

You can use this to easily compute LPA and anomalies. Some sample code is 
at 
https://github.com/spatialthoughts/python-tutorials/blob/main/calculating_climate_anomaly.ipynb
 
<https://mailtrack.io/trace/link/cfd2a6f58798725326b3d4b471445867173296ea?url=https%3A%2F%2Fgithub.com%2Fspatialthoughts%2Fpython-tutorials%2Fblob%2Fmain%2Fcalculating_climate_anomaly.ipynb&userId=8747767&signature=7d2dc35e6a847df4>

I also have video tutorials and Earth Engine code for calculating LPA and 
rainfall anomaly using CHIRPS data
https://www.youtube.com/watch?v=zHUCM3XLc6k&list=PLppGmFLhQ1HJ5VhW6BZfhPX6spUcTY7SR
 
<https://mailtrack.io/trace/link/ab43838fe825ee43d84e70966800a6e7c610213d?url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DzHUCM3XLc6k%26list%3DPLppGmFLhQ1HJ5VhW6BZfhPX6spUcTY7SR&userId=8747767&signature=e72aaae20e773a90>

---
Ujaval Gandhi
Spatial Thoughts
www.spatialthoughts.com 
<https://mailtrack.io/trace/link/0144d5430bb05e91be3b03a4f2d132fbb8dfc5af?url=http%3A%2F%2Fwww.spatialthoughts.com&userId=8747767&signature=24e6baa435674ed5>



On Tue, Jun 20, 2023 at 4:17 PM dimple behal <[email protected]> wrote:

Hi Shijith,
I’m also looking for the same. Let me know if you will be able to get 
something.

On Tue, 20 Jun 2023 at 4:11 PM, Shijith Kunhitty <[email protected]> wrote:

This Q. is for people who work with weather data. I'm trying to do 
something related to the monsoon, but can't find what I'm looking for.

Now monsoons are considered normal or not by comparing it with the average  
monsoon rainfall over a 50 year period 1971-2020, which is called the 
long-period average (LPA).

Tried looking for state-wise LPAs for 1971-2020 on the IMD website, but 
couldn't find it.

The closest I got was this image 
<https://mausam.imd.gov.in/Rainfall/Normal_Rainfall_Maps/Monsoon/Monsoon_STATE_NORMAL_RAINFALLMAP_COUNTRY_INDIA_c.JPG>
 
from the IMD but it's for the period 1951-2000.

If someone could give me some leads on where to find more recent state-wise 
LPAs, I'd really appreciate it. 

-shijith



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Have a wonderful, and full of positive energy day!
*Thank you and Regards,*

*Dimple Behal*
*Urban & Regional Planner*
*Masters of Planning (Environmental Planning)*
*School of Planning and Architecture, Bhopal.*

*(An Institute of National Importance, MHRD, Government of India)*
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