Case Study 23-1: Hurricane Florence and the Private Weather Ecosystem — Who Owns the Storm?

Case Study 23-1: Hurricane Florence and the Private Weather Ecosystem — Who Owns the Storm?

Background

In September 2018, Hurricane Florence approached the Carolinas as a Category 4 storm with the potential for catastrophic flooding. Federal meteorologists at the National Hurricane Center and National Weather Service provided continuous, free, public forecasts. At the same time, dozens of private weather companies — the Weather Company (IBM), Weather Underground, ClimaCell, AccuWeather, and many others — provided competing forecasts, some free, some paywalled, all built substantially on the same publicly collected NOAA observational data.

Florence killed 54 people and caused an estimated $24 billion in damage. The hurricane season of 2018 raised, with particular urgency, questions that the weather private sector had been generating for years: in a life-threatening weather emergency, when weather information can determine whether people evacuate or shelter in place, does it matter who owns and controls weather data?

The Public Infrastructure Behind Private Forecasts

Understanding this case study requires clarity about the infrastructure involved.

What the government provides: - NEXRAD Doppler radar data: 159 stations, continuous, publicly available in real time - GOES satellite imagery: Full resolution data publicly available through NOAA portals - Radiosonde data: 900 global launch sites, data shared internationally under WMO agreements - Hurricane hunter aircraft data: NOAA and Air Force Reserve aircraft flying into hurricanes, releasing dropsondes and measuring conditions directly; data publicly available - NHC forecast track and cone of uncertainty: The official hurricane forecast, publicly available - NWS local office forecasts, watches, and warnings: The emergency warning system for specific communities

What private companies do with it: - License the public data (free from NOAA) - Apply proprietary forecasting models - Provide user-friendly interfaces (apps, websites) - Sell advertising - Sell premium data products to businesses (insurance companies, retailers, logistics firms, utilities)

The private weather industry generates approximately $15 billion annually in revenue — almost entirely built on the foundation of publicly funded observation data.

The AccuWeather Controversy

The most visible political controversy over weather data privatization involved AccuWeather and its close relationship with the Trump administration in 2017. Barry Myers, the CEO of AccuWeather, was nominated to lead NOAA — a nomination that created intense concern because AccuWeather had been lobbying for years to restrict the National Weather Service from providing free forecasts that compete with private forecasts.

AccuWeather's position, articulated in congressional testimony and lobbying documents, was that the NWS should limit its public forecasts to raw data, leaving the consumer-friendly interpretation and presentation to private companies. If adopted, this policy would have forced anyone seeking a forecast to go through a private commercial interface — potentially paywalled, potentially ad-supported, potentially optimizing for engagement rather than accuracy.

Critics pointed out that in emergency situations — hurricanes, tornadoes, flash floods — requiring people to navigate commercial services to receive warnings could be dangerous. The NWS's free, publicly accessible alerts, sent directly through the Emergency Alert System to all phones in an affected area, do not require anyone to have an internet connection, a smartphone, or a subscription to a private service.

Barry Myers ultimately withdrew his nomination in 2019, citing health reasons. The policy arguments AccuWeather raised, however, have not gone away — they recur periodically in congressional debates over NOAA's budget and the appropriate scope of government weather services.

Florence's Flooding: When Forecast Variation Matters

Hurricane Florence's most dangerous feature turned out to be not its winds but its rainfall and storm surge flooding — the storm stalled over the Carolinas for days, producing catastrophic freshwater flooding well inland from the coast.

Different forecast models handled this stalling phenomenon differently. The European Centre for Medium-Range Weather Forecasts (ECMWF) model — which uses different data assimilation and modeling approaches than the U.S. GFS model — accurately forecast Florence's stall several days in advance. The GFS model was slower to catch this behavior. Private forecasting companies using different combinations of model data produced a range of predictions.

For emergency managers deciding whether to issue mandatory evacuation orders, the range of model outputs was not academic — it was the basis for decisions that would determine whether hundreds of thousands of people were in place or in safety when the flooding began.

The case for public forecasting authority: When forecasts diverge, the public needs a clear, authoritative source. The NHC and NWS serve this role: their forecasts, backed by federal authority, form the legal basis for emergency declarations and mandatory evacuations. Private forecasts, however sophisticated, do not carry this authority. The existence of multiple competing private forecasts with different track predictions can actually create confusion and delay decision-making.

The case for private forecasting competition: Private forecasters argue that competition drives innovation — that the ECMWF model outperformed the GFS model in part because of different development approaches, and that American forecasting would be better if the public sector faced more competition. They also note that private sector forecasts for specific applications (aviation route planning, logistics routing, utility load forecasting) are often more refined for their specific purpose than general-purpose NWS products.

The Insurance Angle

Hurricane Florence's aftermath revealed another dimension of weather data privatization: the insurance industry's use of proprietary weather data to manage claims.

Several large property insurers, including State Farm and Allstate, use satellite imagery combined with weather data to assess claims without sending adjusters to every property. A homeowner submitting a storm damage claim may have their damage assessed in part by an automated system that compares pre-storm satellite imagery of their property with post-storm imagery, cross-referenced with wind speed data from proprietary models.

The accuracy of this automated assessment varies. Some homeowners receive prompt, accurate settlements. Others receive assessments that don't match the physical reality of their damage — particularly for flooding damage, which may not be visible in optical satellite imagery.

When homeowners dispute automated damage assessments, they face an information asymmetry: the insurer has access to proprietary weather data, satellite imagery, and model outputs; the homeowner has the view from their driveway. Understanding how the assessment was made, and challenging it, requires access to data that is not publicly available.

Discussion Questions

AccuWeather argued that the National Weather Service should limit its public products to raw data, leaving forecasting to private companies. Evaluate this argument. What would be gained and what would be lost by this policy change?
The chapter describes weather data as a "commons" under WMO agreements. The case study shows that private companies are building substantial commercial value on top of this commons. Is this a problem? If so, what are the appropriate policy responses?
Hurricane Florence's stalling was better forecast by the European ECMWF model than the American GFS model. The ECMWF is a European intergovernmental organization that provides data under its own access terms. Should American emergency managers be required to use only American government model output, or should they integrate the best available forecast regardless of source?
When insurance companies use proprietary weather data to assess claims without public disclosure of their methodology, is this a form of surveillance that should be regulated? What specific regulatory requirements would you propose, and who would enforce them?
Emergency weather warnings — tornado warnings, flash flood warnings, hurricane watches — are currently delivered free of charge to any phone in an affected area via the Wireless Emergency Alert (WEA) system, which does not require any app or subscription. AccuWeather has developed its own alert system and has lobbied for restrictions on competing government alerts. What does the existence of this lobbying effort tell you about how to evaluate private sector arguments for public sector service restriction?

This case study connects to Chapter 23's main text on weather privatization and to Chapter 24's discussion of how public health surveillance data is increasingly commodified.