Why in the News?
According to the India Meteorological Department’s first forecast for 2025, the country may receive around 105% of the average rainfall, with a possible variation of 5% more or less.
What is the India Meteorological Department’s (IMD) forecast for the 2025 monsoon?
- Above Normal Rainfall Predicted: IMD forecasts 105% of the Long Period Average (LPA) rainfall for 2025, with a margin of ±5%. Eg: In 2024, India received 108% of LPA, which was categorized as ‘above normal’ rainfall.
- LPA Reference and Classification: The LPA for the period 1971–2020 is 87 cm. Based on this, rainfall is classified as: Above Normal: 105–110% of LPA. Eg: If the rainfall is 105% of LPA, it falls within the ‘above normal’ range.
- Improved Forecasting Methodology: Since 2021, IMD uses a multi-model ensemble system, combining global climate models with IMD’s own models, improving forecasting accuracy. Eg: Forecasts since the adoption of this system have shown improved accuracy, reducing error margins from previous years.
Why is rainfall distribution crucial for agriculture?
- Impact on Crop Growth: Uneven or poor rainfall distribution can lead to crop stress or failure. Plants depend on consistent water supply during different growth stages. Eg: In 2024, excess rainfall in Maharashtra led to the destruction of onion crops, while deficient rainfall in Punjab delayed paddy sowing, driving up food costs.
- Effect on Water Availability: Proper rainfall distribution ensures water availability throughout the growing season, which is essential for irrigation systems and groundwater recharge. Eg: If regions like Tamil Nadu receive excess rainfall while other areas like Uttar Pradesh experience drought, it can disrupt the balance, making water management challenging.
- Geographical Variability and Crop Suitability: Different crops require specific rainfall amounts at different times, so spatial distribution of rainfall is essential for crop selection and yield maximization. Eg: In 2023, Telangana and Puducherry received excess rainfall, benefiting crops like rice, but Bihar faced a below-normal monsoon, impacting food grain production.
When did IMD improve its forecasting model, and what changed?
- Improvement Began in 2021: IMD improved its forecasting model by adopting a multi-model ensemble dynamical system in 2021. Eg: Prior to 2021, IMD primarily relied on statistical models, but the new system incorporates global climate models along with IMD’s own models for better accuracy.
- Enhanced Accuracy with New Models: The introduction of the multi-model ensemble system improved forecast reliability, reducing errors in predictions. Eg: Forecasts post-2021 showed a significant improvement, with accurate predictions of rainfall in regions like Maharashtra and Tamil Nadu during the 2024 monsoon.
- Reduction in Error Margins: The new approach resulted in reduced error margins, making the first forecasts closer to actual rainfall patterns. Eg: IMD’s first forecast for the 2024 monsoon had a relatively smaller error margin, improving the predictability of rainfall distribution across India compared to previous years.
How do El Niño, La Niña, and IOD affect the monsoon?
| Weather Phenomenon | Effect on Monsoon | Example |
| El Niño | Weakens the monsoon due to warmer sea surface temperatures in the Pacific Ocean. This leads to reduced rainfall. | Eg: 2014, El Niño conditions led to below-normal rainfall, causing droughts and poor crop production in India. |
| La Niña | Strengthens the monsoon due to cooler sea surface temperatures in the Pacific Ocean, which can lead to excessive rainfall in some areas. | Eg: 2017, La Niña conditions contributed to above-normal rainfall, causing floods in some regions like Assam. |
| Indian Ocean Dipole (IOD) | Positive IOD can enhance rainfall, while a negative IOD can lead to drought conditions, especially if combined with El Niño. | Eg: 2019, a positive IOD helped in normal rainfall despite El Niño, while 2020 had a negative IOD, exacerbating the impact of weak monsoon rainfall. |
Which regions saw abnormal rainfall in 2023, and what was the impact?
- North and Northwest India: Excessive Rainfall: Heavy rainfall led to flash floods, landslides, and infrastructure damage. Eg: In Himachal Pradesh, intense rainfall triggered landslides and flash floods, resulting in at least 72 deaths and significant infrastructure damage.
- Northeast India: Glacial Lake Outburst Floods (GLOFs): Sudden release of water from glacial lakes caused severe flooding, destruction of infrastructure, and loss of life. Eg: In Sikkim, a GLOF resulted in the deaths of at least 31 people, destruction of over 270 houses, and damage to 11 bridges.
- Southern Peninsula: Deficient Rainfall: Reduced water availability affected agriculture, leading to crop stress and delayed sowing. Eg: In Tamil Nadu, deficient rainfall impacted the sowing of paddy, leading to concerns over food production.
Way forward:
- Enhance Climate Resilience: Promote water management, drought-resistant crops, and crop diversification to mitigate impacts of uneven rainfall.
- Improve Early Warning Systems: Strengthen forecasting and disaster preparedness to ensure timely responses to extreme weather events.
Mains PYQ:
[UPSC 2024] What are the causes of persistent high food inflation in India? Comment on the effectiveness of the monetary policy of the RBI to control this type of inflation.
Linakge: If the IMD’s prediction is accurate, a good monsoon could mitigate one of the key drivers of food inflation – erratic rainfall and lower agricultural output. This question asks about the causes of high food inflation; a good monsoon would work against these causes.
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