What is Wrong with Our Weathermen?

What is Wrong with Our Weathermen?

Image of Cyclone Hudhud from Insat-3D

Weather forecasting in India has improved with new technology, but accuracy in predicting weather events remains elusive, adding uncertainty to the country’s economic planning. An accurate forecast is critical for – monsoon months (June to September) for more than 230 M Indian farmers to cultivate the country’s rain-fed agriculture and year-round for other weather-sensitive businesses such as transportation, energy, and construction.

Confusion of Conflicting Forecasts: The Old and New Weathermen

The 140-year-old Indian Meteorological Department projected ‘below normal monsoon’ with rainfall of 93% of the LPA in May, which was lowered further to ‘drought year’ with 88% in June version. The state-led IMD’s forecast has significantly failed to predict drought thrice over the last decade, everyone from farmers to stock market investors customarily use IMD’s predictions as the final word.

Skymet, a private forecaster with 3-years of official forecasting experience, who hit the headlines last year for accurate forecast, differs with IMD. In April, Skymet predicted ‘normal monsoon' with rainfall at 102% of the LPA. However, on August 1st, Skymet revised the forecast to 98% (within +/- 4% margin), still ‘normal’ but on negative side.

Other private forecasters, like Weather Risk and apps, like Kolkata-based Express Weather, provide multiple parameters with greater accuracy, which allow weather-sensitive businesses to plan their schedules accurately and avoid economic losses.

The Glitches in Forecasting Predictions

Even though, IMD has invested in supercomputers and weather-monitoring Doppler radars, IMD still relies on complex statistical relations based on 100-years weather data. Skymet (and new firms) has been using sophisticated weather models crunched in supercomputers and has been closer to the mark; yet, the Indian weathermen still lack the accuracy.

IMD has an imposing dense infrastructure of satellite-based systems. IMD has collaborated with ISRO on Insat-3D Advanced Weather Satellite, India’s first geostationary satellite using IMDPS. Insat-3D, equipped with leading-edge ‘Sounder’ and ‘Imager’, delivers high-quality atmospheric profiles that are at par with international quality standards, allowing data sharing with International weather agencies. In July, Insat-3D completed two years in orbit, and it’s better quality images allowed more precise forecast of cyclone Hudhuh in 2014, yet IMD has not able to capitalize on these radiance observations. Also, IMD has unable to gainfully utilize its resources; Doppler radar has time and again been encountering glitches and failed to take off fully.

What differentiate the approaches of IMD and Skymet are the probability predictions of the oceanic-atmospheric phenomena such as the IOD, El Nino, and MJO that bring major fluctuations in weather.

Currently, even though Indian weathermen might not be the leader in technology, they do have modern resources; however, these resources are not fully understood and utilized to its potential, resulting in unreliable weather forecast. 

The Importance of Technology Application

Contrary, weathermen around the world are delivering more accurate forecasting, from weather apps like AccuWeather to Global Weather Corporation, the most accurate forecast provider in 2014.

GWC’s strength of learning local conditions around the global, validating forecasts against real-time observations, and persistently focusing on automation allows GWC to deliver most accurate weather forecast anywhere in the world. GWC obtained $1 million to apply towards new ways of forecasting, which enabled GWC to improve precision and produce most accurate hyper-local forecasts.

Near-future new technologies like satellite-based weather instrument, Pyxis, announced by PlanetiQ earlier in June, with GPS signal sensors designed to penetrate storm clouds, would generate significantly improved forecasting by 2016-17, at less cost than existing systems. Pyxis is capable of monitoring the lowest layers of atmosphere where severe weather forms, using ‘microsatellite constellation’, which will produce ten times GPO-RO data with highest impact on the accuracy.

The question should be – HOW than who will get correct monsoon forecast?

The key to accurate forecast lies not only in sourcing accurately, but also processing it well. Customized data mining from global telecommunication and individual systems, and multi-processing systems are needed to create accurate local weather forecast.

The IMD’s prediction of ‘deficient monsoon’ in 2015 was proven wrong in June with 16% surplus rains and the above-normal reservoir levels countrywide. However, even Skymet’s revised forecast on August 1st is in question with weak August rainfall.

Today in India, there is an acute need for collaborative effort with public-private partnerships to use the cutting-age technologies, complicated statistical models and experimental dynamical forecasts to its best potential. IMD has imposing resources that gather huge real-time first-hand weather-related data, which is unlikely to available to private forecasters, forcing them to depend on the secondary sources of information. Yet, they seem to make more reliable weather forecasts than IMD.

Such PPP collaborations with local and foreign weather forecasting agencies as well as advance-research institutions, with persistent R&D investment and keen automation focus, will not only will improve the accuracy of weather patterns, but also can advance renewable energy forecasting – to create sustainable agriculture and a smart economy.

Photo Reference: www.wsj.com