Late start for monsoon and less rainfall, says The Weather Company

Residents and businesses alike should prepare for a late start for and less rainfall than normal during this monsoon, says a seasonal outlook from The Weather Company, an IBM Business.

El Nino, a variable that modulates the onset and strength of monsoon season, will linger for a second consecutive year, is signalling a later-than-normal and relatively quiet monsoon season in 2019.

Earlier, another private forecaster Skymet Weather had also indicated the probability of monsoon this year ending up below normal at 93 per cent of the Long-Period Average.

The long-range forecast outlook for the monsoon by the national forecaster India Met Department (IMD) is expected in a week's time.

May not weaken

“We’re currently experiencing a dry, multi-decadal phase of the Indian monsoon and haven’t seen an unusually wet season in 25 years,” said Todd Crawford, chief meteorologist at The Weather Company.

The transition to a wetter-than-normal monsoon pattern is dependent on the weakening of El Nino, an unlikely event in the coming months.

Looking ahead, El Nino, or the abnormal warming of East Equatorial Pacific with often bad tidings for the monsoon, returns for a second consecutive year causing large-sale weather patterns to change.

During an El Nino, sinking air is prevalent around near and East of India, limiting the development of thunderstorm clusters that typically plague the region in the summer.

The patterns delay the reversal of low-level winds that signal the monsoon onset. Back-to-back El Nino events are fairly uncommon, only occurring five times since 1950, Crawford said.

Data-centric society

Himanshu Goyal, India Business Leader, The Weather Company, said that as India is becoming a data-centric society, we have the ability to pro-actively make decisions aided by forecasts.

The innate correlation of weather data and consumer behaviour patterns is often under-utilised to help predict retail needs. "But more often overlooked is its impact on the back-end operations of supply chain management, product demand, pricing, inventory, and so on."

Such data at a hyper-local level can actively allow retailers to make smarter business decisions to optimise these back-end operations using the weather data and de-risk their business.

In agriculture, all the technical innovation in the agriculture technology ecosystem is now capable of leveraging data-sets to advise their clients and farmers pro-actively for better decision making.

"Our soil moisture and soil temperature data is used to build smart irrigation schedules and helps address other interventions at the hyper local farm level with a leverage on artificial intelligence and machine learning."

Complex algorithms

Forecast teams at IBM use complex algorithms and supercomputers to give businesses a most-likely weather scenario. For energy and utilities companies, they also plan the load basis the needs of power at peak heat and sudden rains to keep the grids healthy.

Later this year, IBM and The Weather Company will release its new Global High-Resolution Atmospheric Forecasting System (GRAF), claimed to be the first hourly-updating commercial weather model that offers nearly 200 per cent improvement in forecasting resolution in locations around the globe.

Today, most of the world has to settle for less accurate forecasts for predictions that cover 12- to 15-km swaths of land, too wide to capture many weather phenomena, a company spokesman said.

Traditionally, leading weather models update less frequently, only every six to 12 hours. In contrast, GRAF will provide three-kilometre resolution that updates hourly.

COMMENT NOW