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Monsoon Prediction Models

 6/10/2017  81

Prediction Models
Seasonal Winds System – Monsoon

Monsoon winds are periodic in nature. They are responsible for dramatic rise and fall of river waters in the months of May, June, July, August and September. 10th century Arab scholars were aware of its seasonal reversal. Edmond Halley, a British scientists, 1686, called it, Land and Sea Breeze at macro level. It is mostly an Asian Phenomenon. South, South East and East Asia collectively called Monsoon Asia, experience its vagaries. Rice planter, half bent, with saplings in his hands in the puddled fields, is a common view of Kharif season. The genuine south west monsoon showers occur over SAARC lands only. The deltaic clayey soils of Sundarbans with patterned indica rice fields ornate the monsoon lands.
Principles to ponder at:

  1. Degree of perfidiousness increases with latitude. Weather prediction turns tricky and treacherous poleward.
  2. Downpour yielded by pre-monsoon showers and monsoon winds, are inversely proportional to each other.
  3. The higher the sea surface temperatures, greater will be number of tropical cyclones, maximum, is an enigma, adding bewilderment to the surety of monsoon.
  4. Quicker is the development of Tibetan Plateau as Heat Island, smoother will be the plying of summer Jetstream, least spatio-temporal departure will be to the normal path of monsoon.
  5. More northerly is the establishment of ITCZ (Inter Tropical Convergence Zone) with the apparent movement of sun, more predictable and normal monsoon will be.

Monsoon prediction is a tedious task. National Monsoon Mission has made it an easier proposition. Dynamic modelling nearly hits bull’s eye. It scores well over the statistical modelling techniques. It holds seasonal and extended range prediction system. It also holds short and medium range prediction system. Timing of the event can be deciphered adroitly. The intensity and spatial distribution are still the part of conundrum, seeking preciseness.
There are twenty five parameters and hundreds of quadrants which play role in making monsoon a conundrum. The statistical models based on long term averages, often elude perfect decoding of the secrets of monsoon and demystifying its haphazardness.
The anomaly quotient of monsoon prediction is 32 percent.
On nine of the 17 occasions, when the Elnino struck the Pacific Ocean, it led to a drought in Indian subcontinent. The year 2009 made india see a 33 percent short fall in rains during the monsoons. 2014 and 2015 were the consecutive elnino years, has a sobriquet, GODZILLA IMPACT, India had seen twin monsoon failure in 2014. Both SW and NE monsoons registered rainfall variability. 2015 monsoon too betrayed Indians. 2016 was a LaNina year but reduced to an average monsoon year, did not see much hype, left us to coin another dictum,
“After every double Elnino, the subsequent LaNina year will appear ordinary year for replenishing the long desiccating conditions”
Year 2010 has seen more than average rainfalls but the Pacific Ocean had by then elnino conditions. Year 2017 is expected to be in same predicament. A weak elnino over SEPO (South East Pacific Ocean) has spilled no deterrent for an average monsoon.
Sine qua non:
Every elnino year will not see concomitant failure of monsoon
Every laNina year will not see concomitant over productive monsoon
A strong elnino year may have a normal monsoon
No elnino year may find failure of monsoon
There will be a sure failure of monsoon if elnino year finds abnormal warming of entire central Pacific Ocean
Indian Ocean can behave and misbehave at its own and is called, ‘dipole effect of Indian Ocean’. It may have positive and negative phases irrespective of anomalies happening in the sea surface temperatures of Pacific Ocean.
Sometimes the Indian Ocean responds to the changes taking place in Pacific Ocean and sometime it does not.

Statistical Models:

Statistical Models seek historical relationship between Indian summer monsoon rainfall and global atmospheric-oceanic parameters.
These models are considered better than dynamic models in long term forecast.
Indian meteorological department uses statistical models for long range forecasts i.e. the monthly and seasonal monsoon rainfall over the Indian sub-continent.
Statistical models have been adopted at two levels
1. Indian subcontinent
2. Regional levels (north west, central India, north east India and peninsular India)
variability percentages are calculated in terms of positive and negative deviations. Regression techniques are the basis for generalizations.
Statistical models have 8 parameters.
P1 Land surface air temperature of NW Europe (world island composite land)
P2 Equatorial pacific warm water volume (Four o clock rainfall)

P3 North Atlantic sea surface temp ( sinking seas)
P4 – Equatorial South East Indian Ocean surface (West Australian current and Indian Ocean dipole effect).

P5 – East Asia mean sea level air pressure (Kuroshio, Liman and Oyashio ocean currents)
P6 – Central pacific sea surface temperature (Tahiti)

P7 – North Atlantic mean sea level (Gulf Stream)

P8 – North central pacific wind at 1.5 km above gyres
There is a provision for retrospective modeling and prognostic modeling.

Dynamic Models

Dynamic models are able to read the possible behavioural changes in the atmospheric and oceanic parameters.
They are extremely helpful in developing simulation techniques, and can reconstruct past and future on the basis of present. Dynamic models use

  • Doppler weather reader
  • INSAT-3D series
  • Wind profilers
  • GPS sonde (a probe to know surroundings)
  • Buoys in the oceans
  • Aircrafts and advanced telecommunication system
  • Collection of data at district level

Forecasting of monsoons is done at four levels
Short range – 3days
Medium range – 4-7days
Extended range – 7-30days
Long range entire season – 6 months
Dynamic model uses 16 parameters for monsoon forecasting.
Two general predictions are done:
1. April prediction on general pattern
2. June prediction on updates
Note:
Dynamic models are meant for short term predictions and statistical models are appropriate for long term predictions.
Prudential predictions using age old epigrams and traditional knowledge are equally dexterous. Observation based facts have been epitomized into folk lore and time backed axioms:
                                               If the days are cloudy, nights are cloudless,
                                                The easterly wind blows intermittently,
                                                 Unusual things will happen that year,
                                                Rivers won’t flow, well waters will be in use.

Monsoon is strongly dealt in at the Ministry of Earth Sciences. Huge exchequers’ money is spent, space programmes with perfect monitoring have turned out to be a bliss. Delhi has turned out to be one of the 10 RSMC (Regional Specialized Meteorological Centres) of the world. There is no reason for probabilities and possibilities but there are certainties.

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