Anticipating (weather’s) chaos; meshing government- and for-profit weather services; and the elephant in this room.

Historically, monitoring weather and issuing weather forecasts and warnings has been the province of governments. But recently, both the incentives and the means for anticipating and coping with chaotic weather are growing in scope and variety. And so are the ways and extent to which unfavorable weather can disrupt today’s society. This conjunction of technological advance, changing societal vulnerability, and higher economic stakes has triggered and nurtured the emergence of private weather services. These for-profit services are at one and the same time (1) dependent upon-, (2) supplementing-, and (3) competing with government weather services.  

Recent articles, published in two quite different publications, spotlight these trends. Perhaps surprisingly, the one, The Economist, a major news magazine reporting world events as seen through an economic lens, focuses on the emerging scientific and technical opportunity. The second, EOS, an in-house publication of the American Geophysical Union, a scientific society, draws attention instead to the broader public-policy challenges raised by the partial privatization of what once was considered a public good. This man-bites-dog aspect of the two articles makes for interesting reading, even as it reveals a truth: weather, though never a mere backdrop to global affairs, has moved from side- to center stage in 2023. For example, this summer, the isolated episodes of oppressive heat seen in years past have given way to a constant heat burden at levels compromising human health across the entire northern hemisphere. Accompanying wildfires span the globe. The usual strains on energy infrastructure (the occasional brownout in the face of air-conditioning energy demand) and agriculture (localized crop failures) have morphed into worrisome disruptions (e.g., the role of the electrical grid failure in the Lahaina fire and threatened bankruptcy of the power providers at fault).

A few highlights from the articles (which each merit a fuller read):

The science and technology section of the July 29th print edition of The Economist takes as its point of departure the recent spate of particularly-long-lived heat waves characterizing the northern hemisphere warm season, observing that the intensity, extent, and duration of these had been rather well forecast. It notes that today’s five-day weather forecast is about as accurate as a two-day forecast twenty-five years ago, in large part because of improved spatial resolution and small time-steps in today’s numerical weather-prediction models. It acknowledges the existence of fundamental limits to atmospheric predictability, citing the United Nations’ World Meteorological Organization (WMO) estimates that numerical forecasting might achieve something near this theoretical limit around 2050. The article then segues into a look at short-time-horizon, local- and regional forecasts; the economic value of these to weather-sensitive businesses, and financial sectors such as energy trading; and the accompanying rise of for-profit weather companies to meet these demands. It notes that the private-sector in some cases is downscaling government products, and in others is running its own local- and regional models and supplementing government observations with its own tailored observing networks. The article closes with a look ahead to the possibilities that artificial intelligence (AI) will offer. These range from computationally cheap and quick AI alternatives to conventional numerical weather forecasts, to improved ability to tease out the resulting impacts on societies, and on economies, at both macro- and micro levels. AI influence will extend from the short-term, localized weather predictions across the full spectrum to forecasts of global climate trends.

Along the way, The Economist takes note of an elephant in the room: does privatization benefit the rich nations (and their corporations) at the expense of the poor? A bit of the text:

Private players insist their participation is beneficial for everyone. There are far more weather stations in rich countries than poor ones (see map). “Outside of America, western Europe, Japan and Australia, and a couple of other countries, national meteorological services are lagging decades behind,” says Rei Goffer, one of’s founders. Some rich-country agencies help other countries—the Met Office, for example, works with the governments of India, South Africa and several South-East Asian countries. Even so, Mr Goffer argues, many countries simply cannot afford the sort of good-quality forecasting that might help them adapt to a changing climate.’s satellites aim to allow countries access to better weather infrastructure without having to build it from scratch.

Hmm. This brings us to:

The July EOS article, written by Bill Morris, a science writer. He provides a concise history of international cooperation in meteorology. That narrative begins by establishing the long-understood reality that meteorology/forecasting is an inherently cooperative activity, requiring that countries and peoples share their weather data. It then focuses on the WMO, and its antecedent, the International Meteorological Organization. Historically, the WMO has been the primary vehicle for accomplishing this sharing. The article’s title notes that The WMO weathered the Cold War, then asks: But can it survive capitalism?

Morris focuses on a pivotal period in this history:

WMO may have faced its greatest challenge in the 1980s, as market-oriented, conservative governments, especially the United Kingdom and the United States, put pressure on their meteorological services to recoup some of the considerable costs of gathering weather data by charging for them. This pressure coincided with the rise of private forecasting services like AccuWeather and the Weather Channel, which package government weather data for popular consumption on apps, television, and websites.

Neil Gordon was New Zealand’s representative to WMO during this period. “What was happening,” he said, “was observations from, say, France were going on international circuits into the United States to be used and ingested into weather models.… [Those data] would then go to companies like AccuWeather, who would then provide services back into France. And France was very unhappy about it. There was a risk that they would no longer send their data to the States.”

“We almost got to the point where data exchange was being shut off,” Gordon recalled.

Morris recounts a dramatic set of sessions at the Twelfth World Meteorological Congress in 1995 that produced Resolution 40, which formally acknowledged that essential meteorological data were necessary for protection of life and property and affirmed WMO commitment to the continuing free and open international sharing of such data.

Resolution 40 has held sway for some twenty years; the formal and informal WMO community has feared that to revisit it would risk its collapse. But here’s the rub. Over the ensuing decades, the capabilities and role of the private sector in providing weather services has continued to expand. This has led to a corresponding erosion of the former degree of government control. That’s because governments can proscribe private issuance of emergency warnings to the public, but they can’t insist that companies freely share any privately-obtained observations and the privately funded numerical forecasts. So far, public-private-sector cooperation continues to be the order of the day, but it’s informal, subject to change with little notice, and consists of a hodge-podge of arrangements, some involving free sharing of data, and some involving fee payment and restriction on its downstream use. In poorer countries, budget-constrained governments are tempted to rely on whatever weather information is freely available (for now) on the internet, rather than undergo the expense and effort of maintaining in-country data sets, climate records, and national weather services.

Along the way, it’s become increasingly clear the value proposition for international sharing of weather data is greatly enhanced  if oceanographic and hydrologic data are shared internationally as well. Ocean data are needed for predictions of storm surge, tracking and prediction of harmful algal blooms, and predictions of seasonal to interannual, decadal, and longer-term climate trends, and much more. Hydrologic data can be combined with precipitation forecasts to anticipate riverine flooding, and conversely, low water levels, etc. But there exists no strong tradition of data sharing in these communities.

Which brings us back to that room-filling elephant:

Both articles make it clear that international data sharing is essential to achieving the needed weather forecasts and climate outlooks. But they stop short of addressing what’s needed if rich and poor nations alike are to fully share in the benefits of such information. In particular, mere sharing of weather forecasts per se stops short of what is needed. Harnessing the value of those forecasts depends upon additional information decision support for weather-sensitive economic sectors (agriculture, energy, transportation, water resource-management, etc.), for the financial community (e.g., investors and insurers). Such decision support is a given in wealthy nations; in the rest of the world, not so much. Thus, as matters now stand, it’s likely the wealthy benefit far more from weather information coming from poorer, more-remote corners of the world than do the peoples native to those regions. The current disparity is puts cooperation on shaky grounds at best. Only if the benefits of data sharing are themselves shared fairly can collaboration be sustained. More worrisome, if left unaddressed, the current gap in benefits to haves- and have-nots will widen as artificial intelligence comes into play. Nations of the world would do well to address all this sooner rather than later (presumably, under auspices of the WMO).

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