What the debate over normal or below normal monsoon forgets
An HT analysis of IMD data shows obsessing too much about the quantum of overall rainfall could miss the point about other features of the monsoon rainfall.
Private weather forecaster Skymet predicted a below normal monsoon for India on April 10. A day later, the India Meteorological Department (IMD), India’s official weather agency, predicted a normal monsoon. IMD defines a “normal” monsoon on the basis of rainfall volume’s departure from the long period average (LPA). Before 2022, LPA was the average rain in the 1961-2010 period (now it is the 1971-2020 period) and the monsoon was termed normal if it was within 10% of the LPA (now this number is 4%). IMD’s forecast on April 11 says that monsoon rain this year is likely to be 96% (with an error margin of +/-5%) of LPA.
It is still early days for these forecasts to be tested, as India’s rainy season only begins on June 1. However, an HT analysis of IMD data shows that obsessing too much about the quantum of overall rainfall could miss the point about other features of the monsoon rainfall, especially its impact on agriculture which requires timely and proportionate rain throughout the season. Here are four charts which explain this in detail.
A national normal monsoon is consistent with abnormal sub-national rains…
Last year’s monsoon saw India receive 106% rain of LPA compared to the 99% forecast made by IMD in April. In the same forecast, IMD saw “above normal” rain as the predominant possibility in the Gangetic plains. However, the region ran so dry last year that it could not make up the deficit despite heavy rain towards the end of the season. The four states of the Gangetic plains – Uttar Pradesh, Bihar, Jharkhand, and West Bengal – lagged the rest of the country in monsoon rain the most since 1901 last year. To put things in perspective, these are also some of the most important states for rice cultivation in India.
See Chart 1
…as is a normal monsoon rainfall with patches of deficient and surplus rains
If it does not rain at all in June and rains a lot in September, one can still have a normal monsoon in terms of total rainfall. While the temporal spread of the rain does not matter as far as recharging of groundwater and reservoirs is concerned, it is critical for various phases in the cropping season. For example, delayed rains can derail sowing of paddy saplings and seriously impact overall production . While wild monthly deviations within the monsoon season are rare, we have seen four of them since the 2000s when overall rainfall was more than 10% away from the 1961-2010 average for the first half of the season, but came within the 10% range by the end of the season.
See Chart 2:
Even a normal month is no guarantee of normal days
To be sure, despite the monthly deficits and surpluses, rain roughly follows monthly patterns during most monsoon seasons. Within a month, however, daily rain is more erratic. This means that monthly totals can be made up of extremely wet and extremely dry patches. For example, the departure for the cumulative rain in June and September last year took very sharp turns after a few days of surplus rain that wiped out the deficit from a preceding dry patch. Similarly, the distribution of individual days in June looked very different from the distribution in July, August, and September. This, when all the months were separated by about six percentage points in terms of departure from LPA: -1.5% in June, 5.2% in August, 11.4% in September, and 17.4% in July. As is obvious, such deviations are associated with a high risk of flooding.
See Chart 3
Both these variations can be captured in intensity of rain
As shown above, monsoon rain can be far from normal on a particular day or a particular place although the seasonal total for India is normal. Both these variations are captured by intensity of rain. As the term suggests, the intensity of rain is higher if it falls either faster or in a smaller area. IMD has defined thresholds for intensity of rain based on the amount of rain that falls in 24 hours at a station. For example, rain between 35.5 and 244.5 mm in a day is classified as heavy intensity rain; and that of more than 244.5 mm as extreme intensity rain. As expected from the discussion above, there can be surplus extreme rain even in years with deficient monsoon rain and there can be a big deficit in extreme rain even in years with normal overall monsoon. Recent trends suggest that the share of heavy and extreme intensity rain in total rain has been increasing in India, and is perhaps a symptom of the deepening climate crisis. This also means that projected or actual headline rainfall numbers will matter little as far as the relation between rains and agriculture or natural disasters is concerned.
Chart 4:
Private weather forecaster Skymet predicted a below normal monsoon for India on April 10. A day later, the India Meteorological Department (IMD), India’s official weather agency, predicted a normal monsoon. IMD defines a “normal” monsoon on the basis of rainfall volume’s departure from the long period average (LPA). Before 2022, LPA was the average rain in the 1961-2010 period (now it is the 1971-2020 period) and the monsoon was termed normal if it was within 10% of the LPA (now this number is 4%). IMD’s forecast on April 11 says that monsoon rain this year is likely to be 96% (with an error margin of +/-5%) of LPA.
It is still early days for these forecasts to be tested, as India’s rainy season only begins on June 1. However, an HT analysis of IMD data shows that obsessing too much about the quantum of overall rainfall could miss the point about other features of the monsoon rainfall, especially its impact on agriculture which requires timely and proportionate rain throughout the season. Here are four charts which explain this in detail.
A national normal monsoon is consistent with abnormal sub-national rains…
Last year’s monsoon saw India receive 106% rain of LPA compared to the 99% forecast made by IMD in April. In the same forecast, IMD saw “above normal” rain as the predominant possibility in the Gangetic plains. However, the region ran so dry last year that it could not make up the deficit despite heavy rain towards the end of the season. The four states of the Gangetic plains – Uttar Pradesh, Bihar, Jharkhand, and West Bengal – lagged the rest of the country in monsoon rain the most since 1901 last year. To put things in perspective, these are also some of the most important states for rice cultivation in India.
See Chart 1
{{/usCountry}}See Chart 1
{{/usCountry}}…as is a normal monsoon rainfall with patches of deficient and surplus rains
{{/usCountry}}…as is a normal monsoon rainfall with patches of deficient and surplus rains
{{/usCountry}}If it does not rain at all in June and rains a lot in September, one can still have a normal monsoon in terms of total rainfall. While the temporal spread of the rain does not matter as far as recharging of groundwater and reservoirs is concerned, it is critical for various phases in the cropping season. For example, delayed rains can derail sowing of paddy saplings and seriously impact overall production . While wild monthly deviations within the monsoon season are rare, we have seen four of them since the 2000s when overall rainfall was more than 10% away from the 1961-2010 average for the first half of the season, but came within the 10% range by the end of the season.
{{/usCountry}}If it does not rain at all in June and rains a lot in September, one can still have a normal monsoon in terms of total rainfall. While the temporal spread of the rain does not matter as far as recharging of groundwater and reservoirs is concerned, it is critical for various phases in the cropping season. For example, delayed rains can derail sowing of paddy saplings and seriously impact overall production . While wild monthly deviations within the monsoon season are rare, we have seen four of them since the 2000s when overall rainfall was more than 10% away from the 1961-2010 average for the first half of the season, but came within the 10% range by the end of the season.
{{/usCountry}}See Chart 2:
Even a normal month is no guarantee of normal days
To be sure, despite the monthly deficits and surpluses, rain roughly follows monthly patterns during most monsoon seasons. Within a month, however, daily rain is more erratic. This means that monthly totals can be made up of extremely wet and extremely dry patches. For example, the departure for the cumulative rain in June and September last year took very sharp turns after a few days of surplus rain that wiped out the deficit from a preceding dry patch. Similarly, the distribution of individual days in June looked very different from the distribution in July, August, and September. This, when all the months were separated by about six percentage points in terms of departure from LPA: -1.5% in June, 5.2% in August, 11.4% in September, and 17.4% in July. As is obvious, such deviations are associated with a high risk of flooding.
See Chart 3
Both these variations can be captured in intensity of rain
As shown above, monsoon rain can be far from normal on a particular day or a particular place although the seasonal total for India is normal. Both these variations are captured by intensity of rain. As the term suggests, the intensity of rain is higher if it falls either faster or in a smaller area. IMD has defined thresholds for intensity of rain based on the amount of rain that falls in 24 hours at a station. For example, rain between 35.5 and 244.5 mm in a day is classified as heavy intensity rain; and that of more than 244.5 mm as extreme intensity rain. As expected from the discussion above, there can be surplus extreme rain even in years with deficient monsoon rain and there can be a big deficit in extreme rain even in years with normal overall monsoon. Recent trends suggest that the share of heavy and extreme intensity rain in total rain has been increasing in India, and is perhaps a symptom of the deepening climate crisis. This also means that projected or actual headline rainfall numbers will matter little as far as the relation between rains and agriculture or natural disasters is concerned.
Chart 4:
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