WEATHER MEANS BUSINESS
Meteorological data is a public resource that private players now want to monetise
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That’s how all weather information will be delivered in the future, if private players are allowed to have their way. The chase to control and commodify forecast data is heating up. Competition could lead to greater accuracy in predictions, but it might also corrupt the public service that has so far been free. AKSHIT SANGOMLA captures the debate
EARLY THIS year, when information and technology behemoth IBM announced that its Weather Company had created a powerful new global weather forecasting system, it evoked hope and fear at the same time. The company claims that its new Global High-Resolution Atmospheric Forecasting System, or GRAF, will provide the “most accurate local weather forecasts ever seen worldwide” and can predict something as small as thunderstorms or as fickle as tropical cyclones that keep meteorologists on their toes till making the landfall.
Every day at Weather Company’s office in Brookhaven, in US’ state of Georgia, some 600 meteorologists, data analysts and a supercomputer analyse weather-related information gathered by governments and intergovernmental agencies through their weather stations, sophisticated radars, aeroplanes and spy satellites, and feed those into GRAF. To ensure that the forecasts reflect localised and near-real-time atmospheric, land and oceanic conditions, the team also harnesses data from some 270,000 personal weather stations (PWS) run by weather enthusiasts across the world and from hundreds of millions of smartphones, whose “pressure” and “location” sensors keep relaying data even as the user is on the move, talking or taking a nap. These data are then processed by the artificial intelligence-powered GRAF to issue 12 trillion pieces of forecast information for virtually every 3 sq km patch of the globe on an hourly basis. By comparison, the best available government or intergovernmental models have a resolution of 13 sq km and can update forecasts only once in every six hours.
“The information we generate and distribute consists of observations (realtime and historical), short- and longterm, seasonal and impact-based information, such as how crop yields or power generation will be impacted by weather,” says Kevin Petty, director of science and forecast operations at IBM.
Such accurate and timely information is precious in a warming world. About 80 per cent of all businesses in the world want and buy weather forecasts to make critical business decisions, especially with regard to risk assessment. The World Meteorological Organization (WMO) estimates that the annual value
accrued from weather services by companies globally is US $100 billion. The weather industry itself is worth $7 billion and is growing by 10-15 per cent every year (see “Big data on weather”,
p34). Though IBM plans to launch GRAF towards the end of the year, it is already selling weather forecasts churned out by the Weather Company to a range of companies that include Google, Apple, Facebook, television stations around the world, insurance companies, and travel and tourism agencies.
But its increasing prowess is disturbing at a time when there is a push from several quarters to fundamentally change the way the world gathers and disseminates meteorological data. WMO, which has so far ensured that weather data generated through public agencies is shared for greater public good and for free, now wants private ventures to play a major role in weather forecasts. In June this year, for the first time WMO rolled out its open consultative process to debate the roles of private players in weather data management. “The traditional public good approach by entities like the National Meteorological and Hydrological Services (referring to government nodal meteorological department like India’s meteorological department) is not suitable for commercial suppliers, so balances need to be found that allow sharing data and products under different scenarios,” says Dimitar Ivanov, director at WMO to Down To Earth.
Speaking at the WMO congress, Louis Uccellini, Director of the US National Weather Service (NWS), said, “The demand pie for what we do is getting bigger. There is no way the public sector can supply all the information needed for
WMO wants private companies to play a greater role in forecasts, as was reflected in its Open Consultative Process in June this year to include all stakeholders on one platform
sectors including energy, agriculture, recreation, transport or health.”
The US government, whose National Oceanic and Atmospheric Administration (NOAA) is the world’s largest weather and climate data provider, also appears to be pushing for an increased role of private players in the management of weather data. Earlier this year, when Uccellini was contesting for the presidential post of WMO, he was backed by US President Donald Trump. For the past three years, Trump has also been trying to appoint Barry Myers, former CEO of private weather forecasting agency AccuWeather, as the head of NOAA. Though Myers is not a scientist, Trump has nominated him for the post thrice since 2017. The US Senate has rejected him twice, and after the third nomination Barry is waiting for the Senate to give its approval.
Myers is known for his publicly stated stand that people should pay for weather information, just the way his company’s products are being paid for. Scientists and administrators in the US, especially at NOAA, say Myers’ appointment would lead to a dilution of the scientific rigour of NOAA and its associated agencies like NWS,
whose climate research work goes far beyond forecasting. Myers may have stepped down as AccuWeather’s CEO, but his family continues to own and run the company. Besides, for the past 60 years, AccuWeather has competed with NWS, trying to undermine its work. For instance, in 2005, AccuWeather tried to push for a piece of legislation in the US Senate through Republican Senator Rick Santorum that would have restrained NWS from publishing weather forecasts, which would then be issued by private agencies. This would have limited NWS’
scope of work to only predicting
extreme weather events like hurricanes and snowstorms. The fear is if Myers becomes the administrator of NOAA, then NWS will become a subsidiary arm of AccuWeather, which would use NWS infrastructure and resources to churn out profits.
This would not only set a precedent, but also have a cascading effect on other countries. If Myers gets appointed as NOAA’s head, it may kickstart a process to privatise the weather data industry. This will force every other agency, such as the European Space Agency (ESA) or the India Meteorological Department (IMD), to pay NOAA and other organisations for using their weatherrelated data or near-real-time satellite data that are now available for free.
With weather data under private parties, the consequent financial burden on countries would force governments and authorities to charge citizens for weather information. This would have a disastrous impact on those who are vulnerable to extreme weather events in the world that is fast warming up.
“You find yourself in a scenario where the best forecast on the planet is actually for purchase, and you’re separating the haves and have-nots when it comes to life and property,” says Neil Jacobs, acting administrator of NOAA.
Jacobs’ views highlight a grave concern that is now bothering many— whether private companies should be allowed to control a resource that was always meant to be free and issued by governments in public interest!
The technologies that have helped us understand the Earth’s climate have always gone hand in hand with the technologies that can aid in our possible annihilation. The Second World War marked the beginning of a transformation of weather observation from a collection of disparate points into a global system that began to use rocket technology and satellite technology.
In 1961, US President John F Kennedy said at the UN General Assembly: “We shall propose further cooperative efforts between all nations in weather prediction and eventually in weather control.” This footnote in political history became a transformative moment in meteorology, says Andrew Blum in his recent book The Weather Machine.
AccuWeather’s Barry Myers is slated to take over the world’s premiere weather organisation. He has stated that weather information, which is free now, must be paid by customers
It led to the formation of WMO in 1951 under the UN, and other countries gradually followed suit by starting or integrating their weather organisations (see ‘Forecast landmarks’, p32).
Over the decades, free sharing of weather data has become a cooperative effort between the weather agencies of different countries to predict cyclones, rain, heat waves and dust storms.
“We get access to data from the meteorological organisations of other countries. WMO oversees data exchange between all its member countries,” says Mrutyunjay Mohapatra, directorgeneral of IMD, which has a vast infrastructure and personnel to issue forecasts. He adds, “What has been our principle so far is that the private sector should complement our work. They
The weather forecasting systems market is projected to grow from an estimated $2.3 billion in 2019 to $3.3 billion by 2025
shouldn’t compete.”
But private organisations are already setting up infrastructures to exploit the exponential demand for customised weather data. The weather forecasting systems market—prediction systems designed to carry out atmospheric research and operational weather forecasting—is projected to grow from an estimated $2.3 billion in 2019 to $3.3 billion by 2025. Expectedly, it has spawned a new generation of start-ups to exploit this situation.
In 2004, Eduardo Saverin, an economics student at Harvard University, USA, who had a knack for predicting how weather will behave, decided to make money out of his skills. He knew global crude oil prices rise and fall with changing temperatures, rainfall and extreme events like floods, thunderstorms and cyclones. This is because the demand for products made of crude oil depends on prevailing weather conditions. The demand for fuel is the highest during peak summer and winter months. While in winter people require more oil to keep houses warm, during summer people move out on drives for vacations which increases the demand for natural gas.
The real play though is in the relative intensities of hot and cold temperatures during extremes. Taking all this into account, Saverin invested in crude oil futures—buying and selling them at exactly the right times. Futures are a type of financial derivative that derives its value from an underlying asset, such as a stock, bond, currency, index or commodity and can be traded either privately between parties or publicly at a stock exchange. Saverin earned around $300,000 in a matter of three months from his investments.
Similarly, Climacell is a start-up based in Boston, USA, with 105 employees. It is integrating data from the Internet of Things devices like mobile phones, smart vehicles, street cameras, aeroplanes and other wireless communication networks, instead of relying just on government provided sources. With this varied set of data, they claim to make hyper local forecasts based on which companies can take decisions. Climacell has till now sold forecasts to over 1,000 companies which include Ford Motors, Tata Group and events like the US Open. Ford Motors, for instance, will use Climacell’s real time forecasts to allow its autonomous vehicle fleet to escape bad weather conditions on their routes.
Climacell is also using an advanced technology, known as radio occultation, to harness weather data. In this technology, radio wave signals, sent and received by GPS satellites to their ground receivers, get refracted and slow down while travelling through the atmosphere. The bending of the signal reflects the vertical variation of refractivity which, in turn, depends on temperature, pressure and water vapour in the atmosphere. By calculating the angles by which these signals bend, scientists can reconstruct the data regarding these variables with the help of physical and mathematical models.
As private firms do not have access to detailed satellite-related data from public institutions, they are also launching their own weather satellites.