National Monsoon Mission is recently in the news after the National Council of Applied Economic Research (NCAER) released a report on ‘Estimating the economic benefits of Investment in Monsoon Mission and High-Performance Computing Facilities.’
This article will provide you with relevant facts about the National Monsoon Mission, its objectives and achievements for the IAS Exam.
|Brief about National Monsoon Mission|
|Year of Launch||2012|
|Concerned Government Ministry||Ministry of Earth Sciences|
|Objective of NMM||
|Outlay of NMM||
|To complement UPSC 2022 preparation, candidates can check the following links:|
Objectives of Monsoon Mission of India
- Improvement of monsoon forecast skills with the help of partnerships between academic and research and development organizations nationally and internationally.
- Improvement of prediction skill of:
- Seasonal and Extended range predictions and
- Short and Medium range (up to two weeks) prediction.
Need for National Monsoon Mission
- Need for improved weather advisories – In India, 82 percent of rural poor live in rain-fed areas and rain-fed agriculture is a significant contributor to agricultural production.
- Indian Summer Monsoon Rainfall (ISMR) amounts to more than 80 percent of the annual rainfall in the country playing a pivotal role in food production. Hence, a mission like NMM was needed to improve assimilation and forecasting systems to predict monsoon.
Evaluation of National Monsoon Mission – NCAER Report
It was launched in 2012 with an aim to develop state-of-the-art monsoon prediction systems for short, medium and long-range forecasts.
As per the NCAER report, National Monsoon Mission will benefit 1.07 crores below poverty line (BPL) agricultural households and 523 lakh BPL fisherfolk households in the country. The other important details are:
- The monsoon mission of India will give 50 times more benefit on the investment made under it and on the high-performance Computing programs over a period of 5 years (till 2025.)
- A more accurate weather forecast led to a structural change in the production level of food grains in the last 4-5 years.
- In the irrigated districts, the production level of food grains increased in the post-monsoon-mission period.
- Rain-fed districts witnessed the increase in the production level of food grains in both pre-monsoon mission and post-monsoon mission with a significant increase in the latter.
Impact of National Monsoon Mission on Farmers
The total annual economic benefits to agricultural households, farmers and livestock owners taken together, has been calculated at Rs. 13,331 crore and the incremental benefits over the next five years are estimated to be about Rs. 48,056 crore.
The report by NCAER mentions the following impact of weather advisories on farmers:
1) Change in the agricultural practises – With the usage of weather advisories, 98 per cent of the farmers made changes to at least one of the nine critical practises and 34 per cent farmers made changes to all nine critical practises:
- Changed variety/breed
- Arranged for storage of harvest
- Early/delayed harvesting
- Changed crop
- Early/delayed sowing
- Changed schedule of ploughing/land preparation
- Changed pesticide application schedule
- Changed fertilizer application schedule
- Changed scheduled irrigation
2) Increase in income – 94 per cent of farmers who took to modifications in farm practises in the account of weather forecasts saw a decline in income losses and an increase in income.
3) Income directly proportional to the modifications in agricultural practices – The NCAER report mentions that farmers who adopted farm practises based on weather forecasts and modified the nine critical practises continuously, saw an increase in their average annual income.
4) Drastic increase in the use of weather advisories – 59 per cent farmers are reported to make use of weather forecasts twice a week.
5) Information on calamities – 55 percent of farmers received information on calamities almost every time whereas 36 percent received correct information occasionally.
Impact of National Monsoon Mission on Livestock Owners
Livestock owners undertake three practises:
- Modification of shed/shelter
- Vaccination against seasonal disease
- Fodder management
Also, Note –
- The NCAER report mentions that 76 percent of livestock owners use weather advisories and modify their practises mentioned above.
- Almost 96 percent of livestock owners were benefited using the weather advisories for the improvement of vaccination practises against seasonal diseases.
Candidates can also read National Livestock Mission on the linked page.
Impact of National Monsoon Mission on Fishermen
- Substantial reduction in the operational cost is a result of using Ocean State Forecast (OSF) – 82 percent fishermen are reported to have used weather forecasts before venturing into the sea for fishing.
- Empty trips avoided – 9606 empty trips have been avoided and Rs. 18.25 crores saved due to OSF advisories.
- Generation of additional fish catch – Fishermen benefitted from Potential Fishing Zone advisories (PFZ).
- 97 percent of those fishermen who were surveyed by the NCAER is reported to receive timely information on floods and cyclones, which helped them minimize their losses. (For information on cyclones, check the linked article.)
Achievements of National Monsoon Mission
- Seasonal prediction model is developed for monsoon at a very high resolution of 38 kms.
- Extended range prediction systems are developed for dry/wet spells, heat/cold waves etc.
- Very high resolution ensemble prediction system is developed at 12 kms in the short and medium range (up to 8 to 10 days) useful for extreme weather prediction.
- The mission used high performance computing (HPC) capability from 1 Petaflops to 10 Petaflops. Two HPC facilities are established at MoES institutes:
- Pratyush (4 Petaflops) at IITM
- Mihir (2.8 Petaflops) at NCMRWF, Noida
- “Unified Model” that is inspired by the UK Met Office has been developed for high resolution short range and medium range forecasts.
- Global Ocean Data Assimilation System (GODAS) observations used to develop data assimilation systems.