## Instead of giving a single number forecast, the India Meteorological Department must switch to a probabilistic approach

Given the current rainfall trends in June and July, the monsoon (June 1-September 30) rainfall for the country as a whole is in all likelihood to be “deficient” (defined as less than 90 per cent of LPA, the Long Period Average). The shortfall in July is 22 per cent, which is very unlikely to be made up by the rainfall in the remaining two months and prevent the imminent (meteorological) drought.

From public perception, the India Meteorological Department (IMD) failed in its forecast for which it is already drawing a lot of flak from media commentators for getting it wrong “once again.” The IMD had forecast a ‘normal’ monsoon with a total seasonal rainfall for the country as a whole at 96 / 4 per cent of the LPA. But, actually, the IMD forecast this year was pretty good and this flak unwarranted. Yes, this one sentence forecast aimed at giving a single number for the consumption of the public and politicians is definitely off the mark. But there are other significant details in the IMD’s changed and improved forecasting methodology that it has been following since 2003, which would show the IMD in better light.

**Statistical approach**

The new strategy has been to move away from a deterministic forecast of this single quantity, the India Summer Monsoon Rainfall (ISMR), to a probabilistic forecast. In fact, India is the only country which gives a quantitative long-range forecast (LRF) when long-range forecast, whether statistical or dynamical, is a highly probabilistic exercise depending very critically on the initial (summer-time) values of the meteorological variables and the models used. In the statistical approach, the variables are certain meteorological (regional and global) parameters that have been found to be statistically well-correlated to the ISMR. In the dynamical approach they are the values of physical variables themselves, such as pressure, wind velocity, etc.

A statistical approach is resorted to because the underlying physics of the monsoon is not yet fully understood for the dynamical equations to correctly represent the causative conditions for the monsoon and its evolution. Moreover, integrating these highly non-linear equations over a long period for an LRF requires high-resolution data on the variables (not easily available) and highly intensive computational exercise requiring huge high-performance computing resources. Also, because of non-linearity, small (measurement) errors in the initial conditions will diverge very quickly to yield wrong results. In fact, to date, no dynamical model has been able to simulate the monsoon over the Indian region well and accurately predict the monsoon behaviour. For example, the model from the National Centers for Environmental Prediction (NCEP) of the United States, which has been adapted for monsoon prediction by the Indian Institute of Tropical Meteorology (IITM), Pune, has forecast 104 per cent rainfall for 2012.

The statistical approach, on the other hand, depends on how robust and stable the atmospheric forcing parameters (the predictors) are. A major problem has been to identify a small set of stable and independent parameters that influences the monsoon rainfall and the bulk of its variance. In fact, there is a natural variability of the rainfall on the decadal scale that is seen from historical data. A 30-year moving average plot of the rainfall suggests that we are currently in the “below normal” epoch of this natural variability. Moreover, the predictors themselves have been found to be unstable over long periods. Many of the once strongly influencing parameters have declined in their correlations over the years. Some have, in fact, turned negative. And yet the monsoon system itself seems to be stable and has been visiting us every year without fail! The search for a minimal set of stable and strongly enforcing parameters thus remains a constant one.

**Five categories**

Therefore, instead of a single-number-fixated forecasting exercise, probabilistic forecast makes eminent sense and logic. Also, since the forecast skill of individual models has been found to be not very good, since 2007, the IMD has adopted an ensemble approach. Here the ensemble includes statistical models of its own and different dynamical models from various international organisations. This approach will also give probabilities, rather than a single definitive number, for different outcomes of the ISMR.

For this probabilistic exercise, the IMD has classified the monsoon rainfall into five categories: Deficient (less than 90 per cent of the LPA), Below Normal (90-96 per cent), Near Normal (96-104 per cent of the LPA), Above Normal (104-110 per cent) and Excess (above 110 per cent). In any statistical exercise, there will be a finite probability of the outcome being in any of these categories. The confidence with which a prediction is made depends on how well one is able to estimate these relative probabilities.

But before looking at the IMD’s 2012 forecast, let us see what the *a priori *(purely climatological) probabilities for these categories are. The climatological probability for a “Normal” monsoon (96-104 per cent) in any given year is 33 per cent and those for “Below Normal” and “Deficient” monsoon are 17 and 16 per cent respectively, which are by no means insignificant. These numbers need to be kept in mind when one looks at the actual forecast and see how much the year’s meteorological conditions change these *a priori *probabilities.

Unfortunately, the IMD has not felt it necessary to emphasise this aspect in its forecast. Apart from 2003 and 2004, when this probabilistic approach began, and more recently in 2011-2012, information on the relative probabilities for the five categories was not made public. Apart from political expediency and possible adverse influence on the market, one cannot imagine any other reason. Given the convenience of pegging stories to this single number, news reports too have ignored the other details of this year’s forecast. So the IMD itself is partly responsible for inviting criticism after this year’s forecast.

So what did this year’s forecast tell us in terms of probabilities? In the preliminary April 26 forecast, which is based on December-March data of atmospheric variables, the IMD forecast was 47 per cent probability for a “Normal” monsoon, 24 per cent for a “Below Normal” monsoon and eight per cent for a “Deficient” monsoon. In the updated June 22 forecast, which includes data up to May, a possible trend towards a poor monsoon was discernible. As compared to the April forecast, while the probability for a ‘Normal’ monsoon fell to 42 per cent, “Below Normal” shot up to 35 per cent and “Deficient” increased to15 per cent, nearly the climatological probability. Unfortunately, the IMD does not sufficiently emphasise these aspects in its press release and continues to give undue focus on that single number in spite of its changed forecast strategy. It is clear that these probabilities give sufficient insight to possible monsoon behaviour and can serve as guidance for proper planning.

But it is not clear in what form the forecast is presented to the planners and the agriculture ministry for them to take appropriate measures because the way the government’s response is being projected in media reports it would seem that it did not have any idea of the distinct possibility of a bad monsoon year. It can even be argued that the IMD totally gives up this single number forecast for the ISMR. Instead, different agencies can scientifically interpret the forecast probabilities for the different categories and take appropriate contingency measures. If this information is to be continued to be shared with the public, an exercise that began only in 1988, then the IMD must also take efforts to explain the probabilistic nuances of the forecast to the media and the public. It is high time that the IMD moved away from realpolitik to real-scientific.

*ramachandran.r@thehindu.co.in*

## Indeed, it is amazing how little weather information we get on our news. That

being said, the IMD cannot be criticized. In the interests of simplicity, it tries to

provide a concise prediction.

And anyway, what can be done even if the IMD is spot on and predicts a miserable

monsoon? Do we have any contingency planning for this case? We are still utterly

reliant on the monsoon for irrigation. Technically, the government could take

measures to combat secondary effects such as possible famine in some regions in

the wake of a weak monsoon or flood prevention measures in case a strong

monsoon is expected, but we have never seen such a thing in our country.

If we really had contingency planning, then a more detailed region-by-region

forecast with appropriate probabilities (note that any forecast is only an estimate)

would help to enforce such planning. But the lack of the latter makes the need for

the former superfluous.

## There is a forecast by our punchangam which after careful analysis of many years of data predicted for sixty years cycle and it comes true so educated can at least look into it if not try to understand it.

## Simply superb

## For general public IMD may be the butt of jokes. But, there are some aspects that need a thought. If IMD takes a pessimisitc approach and predicts a dorught or less than normal rainfal, the probability of Food stock hoarding raises. Other aspect, India is making a begining in Seasonal prediction. Any systerm will need to go through multiple trails before perfection. Third thing, there are multiple organisations in India that reserach on the weather prediction. Why only IMD is singled out always ? As the article itself says, IMD's methodology said 98% where as the so called imported model in IITM said 112% when the actual is less than 90%. So the flak should go to IITM also. Lastly, for centuries Earth sciences and IMD were neglected spots. Even within Govt, it was considred as an Ministry with no job or punishment role. Thanks to Kapil Sibbal's time beginig with 2004, the talk of modenisation came up. For the public today atleast the short range prediction is more or less accurate.

## IMD are incompetent, bumbling, Government babus who do not work for

their salary drawn. At beginning of each year they forecast "normal"

monsoon. When it does not rain one day, they forecast that it will

not rain the following day, and when it rains one day, they forecast

it will rain exactly the same way the following day. They are

charlatans and deserve no sympathy or justification for their

blunders. The author's statement "But, actually, the IMD forecast

this year was pretty good and this flak unwarranted" is without any

basis.

All over the world, weather forecasts are very accurate for upto 7

days. They are detailed to within 50 km locations. We have the same

equipment, but the Government babus are useless.

## If atmospheric changes in the global environment are making it difficult to read the monsoon, why not accept for the time being that the weather forecasting will be like that? Till the IMD is able to forecast it in more reliable manner, why not accept that in future the monsoon will be erratic and will be either below or above normal in most parts of India. We have to be always ready for this most likely future scenario and have in place permanent and workable plans to meet any situation. Merely increasing the expenditure on latest forecasting models would be wasteful. IMD’s can co-operate with university teachers and researchers and benefit from their involvement in this activity.

## I agree with you to a great extent. I will add one more important point to this. India being such a vast country with a number of

agro-climatic zones it is almost impossible to make one forecast ,or even predicting probabilities, for the whole country. Moreover, it is quite useless to give one forecast(or probabilities) for the whole country.Hence it will be more useful to farmers and planners if we

can divide the country in a number of agro-climatic zones and then forecast for all the regions, by taking into some spacial-temporal

techniques. It is more likely that such forecasts will be more accurate and more useful to farmers.

## Astrologers of the Panchangams can make a better prediction though that

from:
P Srinivasan
Posted on: Aug 1, 2012 at 15:15 IST

is also equally unintelligible to the common man

## Met department is no different from other bureaucratic mess that is prevalent in the country. There is virtually no research and impetus to create newer dynamic models that suit the climatic of the region. Most of the met officials are interested on "latest software" from abroad that will enable them to vacation abroad in the name of training. Whose money is it anyway!

## The first thing about any working model used for the prediction is it

has to be validated. They will be validated based on the old data.

Things are changing fast, with increased technological advancements,

global warming etc., and there by due to its after-effects. Lot more

factors need to included into the existing models in order to make them

more efficient. The idea of probabilistic methods sounds very

encouraging.

## Your attempts to hide/conceal/solemnize/politicize the failure of IMD in predicting this year's monsoon will not wash away their ineptness. Their June 22 prediction that "the probability of season rainfall to be deficient (below 90% of LPA) or excess (above 110% of LPA) is relatively low (less than 10%)." is itself way off the mark. What can you expect from an organisation that still uses 18th century instruments manned by slumbers to gather data? IMD's predictions are GIGO. Like our intelligence people, they have lost touch with outside world. They reside in their computer models.

## India economy is based on agriculture . Till now India does not have a

weather TV channel which can /forecast predict/update/inform about

monsoon season to farmer community . In the future the countries which

produce foodgrains will be economically strong.

## Finally an article that makes sense and is written in clear English.And,

It's good to see that at least some authors writing on this highly

mathematical topic have minimal sense of probability theory. Kudos to

Mr. Ramachandran for writing this excellent article.

## It is quite true that media tarnished the image of Indian Meteorological Department(IMD). I am absolutely agree with author that IMD should adopt probabilistic approach instead of statistical one. One aspect I also want to put forward is quality of data. I am not very sure that input data (from their own resources as well as outsourced one) that IMD got for their models; is standardized one and is of good quality. If you put garbage in you model, your outcome will also be garbage. Again IMD should also make people aware about their effort and procedures to generate and disseminate forecast. By doing this it will be possible to make common folk aware that no forecast is absolute and it always came with a tag of uncertainty.

## Actually the departments like meteorology department, areas of surveillance activities in home and defence ministries should initiate activities in collaboration with academic institutions instead of creating their own to model the random processes using mathematical simulation tools.The fresh blood in academic institution will provide necessary tools to predictively estimate the result.The people with designations of variety of directors etc. craving for foreign trips, personal promotion by alligning with the powers can not deliver results.If the obnoxious OFFICIAL SECRETS ACT is removed, many such incorrect results would come out.

## An excellent, knowledge abundant article. Since I am pretty familiar with the statistical appraoch for calculations, being an engineer myself, the article made a lot of sense. And looking at the numbers, I find it very plausible for a monsoon that we are experiencing right now. Wonder why the IMD is not revealing these to the general public. Thanks again for the article. I have always been wondering how the IMD comes up with these one line prediction, considering the enormous complexity of the mathematical model of the monsoon.

## It is no doubt difficult to predict the weather but our meterologists

should be cautious in their predictions and not mislead the farmers. It

looks they do this to satisfy the stock market and the political bosses.

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