For a long time, weather forecasting was largely the domain of governments, with the National Weather Service leading the way in the United States. During the last two decades, however, the private weather forecasting industry—which includes well-known companies such as AccuWeather and many hundreds of smaller businesses—has grown up and is now estimated to be worth as much as $6 billion.

Even so, these companies largely just repackage model forecasts and incorporate data from government weather agencies. The heavy lifting, in the form of sophisticated computer models and the processing power to run them, is still done by the large ECMWF center in Europe, NOAA's National Centers for Environmental Prediction in the United States, and similar forecasting services in Canada, Japan, and elsewhere.

All of these government agencies, with staff generally in the hundreds of scientists, forecasters, and coders, collect weather data from a variety of sources, including shared satellite data along with in-situ observations from aircraft, balloon soundings, surface observations, and other sources. Then, using their own software, they "assimilate" these observations into physics-based forecast models that simulate weather conditions around the globe at various levels of the atmosphere over a 10- to 16-day period. The results from these global models are then used to predict things like the high temperature on Wednesday and whether it is likely to rain on Saturday afternoon for little Joey's birthday party.

For much of the 21st century, to the chagrin of US scientists and forecasters, the American GFS model—Global Forecasting System—has lagged behind the European ECMWF output, especially in things like five- and seven-day forecasts and tropical cyclone track forecasting. This is largely due to the fact that the ECMWF has typically had more dedicated supercomputers to run their forecast models and a much more sophisticated system to get more—and more timely—data into its forecast model as initial conditions.

A TV maker, really?

Large, multinational electronics company Panasonic now wants to crash the party. In an exclusive interview with Ars, Neil Jacobs, the chief scientist for Panasonic Weather Solutions, said the company has been running its own global model for several years on an 11,000-core supercomputer. And that PWS model, he said, has not only been outperforming the GFS model but has become competitive with the gold-standard ECMWF model. "We started the global model development in 2008 and finally got to the point where we were outperforming ECMWF by late last year," Jacobs said.

There are various ways to measure model accuracy, but one of the most widely recognized is "anomaly correlation" at the 500mb, or mid-level of the atmosphere, over a 30-day average. Higher scores are better. Recently, Jacobs said, the PWS model has scored a .926, compared to a .923 for the ECMWF and .908 for the GFS. Essentially, then, a team of five weather modelers and five software engineers, as well as about 20 meteorologists and computer modeling experts at universities under contract, claims to have beaten the best government weather forecasting centers in the world.

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

Panasonic Weather Solutions

It's an audacious claim and one many of Jacobs' colleagues are not yet ready to fully accept. "I would be careful," said Cliff Mass, a professor of atmospheric sciences at the University of Washington who closely tracks the competition between global forecast models. Mass is familiar with the Panasonic weather model. "He’s shown me some results but not a lot of results. He’s making a huge claim. If it’s true, it’s extraordinary. A private company doing global data assimilation and running a global model. It would be amazing news."

Panasonic traces its advantage to the use of weather information collected by airplanes. Back in the 1990s, during the Clinton administration, the US government asked airlines to gather in-situ weather information to prevent icing and other potentially dangerous conditions in flight. The first of these TAMDAR systems was deployed on regional airlines more than a decade ago by a company called AirDat. Panasonic Avionics acquired AirDat in 2013 and created its weather solutions unit.

The key is airplane data

AirDat and now Panasonic have continued to deploy these TAMDAR sensors on airplanes flying mostly regional routes over the continental United States and, more recently, Europe and parts of Asia. As the planes take off and land, they collect all sorts of useful data for forecast models, creating a vertical profile with wind, temperature, humidity, pressure, and other information. Historically, this kind of detailed data was only available from "soundings" captured by balloons sent twice daily into the atmosphere from various locations.

Panasonic now gathers about 3,500 of these soundings per day, and the number is growing as it adds more planes at a rate of two to three per week, Jacobs said. The original business plan was to sell this weather data to the major government meteorological centers, and Panasonic does that. But it found that by keeping some of the highest resolution data to itself, it could create a global forecast model that competed with the big boys.

Jacobs said they started with the dynamic core of the GFS model, which is freely available to the general public because it is funded by the US government. The team spent a couple of years modifying the code, adding bits and pieces of other model code. They also developed a sophisticated assimilation process, more like that of the ECMWF model, which Panasonic calls a hybrid 4D-Var and EnKF. The 4D-Var is for asymptotic observations, Jacobs said, and the EnKF is to estimate background error covariances.

"We have made a lot of additional modifications to the cloud physics, radiation model, air-ocean coupling, and especially the observation quality control," he said. "The EnKF allows us to calculate impact per observation in real time, so we can remove observations that are causing negative impact before we kick off a model run."

An independent meteorologist familiar with the Panasonic model, Ryan Maue of Weather Bell, said he was encouraged to see a private company move into actually operating its own global model. "A private company is more agile and able to test ideas than the federal government," Maue said. "While it's hard to declare a winner in any so-called model wars, or to say Panasonic is better than the GFS or ECMWF, it's clear it has a competitive model that is valuable for its customers."

Et tu, GFS?

Asked about the claim that Panasonic's forecast output is beating the GFS, a spokeswoman for the federal agency NOAA, Susan Buchanan, declined comment. "The National Weather Service doesn't comment on private weather sector products and services," she said. "We would be happy to speak to you about our models if you would like to rephrase your question and ask us specific questions about the GFS."

Both Mass and Maue said Panasonic will have to release more of its forecasts publicly if it wants to prove it's as good as, or better than, the existing global models. So far, they have only seen weeks of verification scores, not the months needed. Mass said Panasonic should offer more public samples and publish them in advance. Jacobs said he has been sharing some of his model output with GFS forecasters.

For now, Jacobs said the company is still trying to determine how best to handle its new asset. A global forecast model that is competitive with the ECMWF could be worth billions of dollars. One of the most immediate ways to capitalize is by selling its output to companies that trade in energy futures. If the ECMWF is forecasting a very cold period in 10 to 14 days over North America, but the GFS is not, how would you trade? That decision is a lot easier to make if there's a third global model coming down on the side of very cold weather.

"Right now there's a level playing field," Jacobs said. "Everyone has access to the GFS and ECMWF models. But we think having exclusive access to something your competition doesn’t have, well, that’s really going to make things pretty lopsided."