TABLE 7.2 Models distinguished by funding source, purpose, and cost of data access


Government Funded

Privately Funded



Publicly owned and operated networks installed to meet specific mission requirements

Privately owned and operated networks intended to generate revenue and/or to facilitate operations

Network of networks intended to assimilate observations from as many sources as possible

Ownership/operating costs

Publicly owned and funded

Privately owned, with private and (often) some public funding

Multiple ownership

Cost of data access

Marginal cost of redistribution

Subscription fees

Provider dependent


  • ASOS

  • AWOS (FAA)

  • NOAA Profilers

  • AWS Weatherbug

  • Weatherflow

  • NLDN


  • MesoWest (Utah)

  • Northwest Net

  • MDCRS (aircraft observations

  • Clarus (FHWA)

NOTE: NLDN – National Lightning Detection Network

  • They have been able to bootstrap themselves into existence. Using the energy and enthusiasm of the participants, these networks don’t require a pre-existing hierarchy or organization to start or to grow.

  • They encourage voluntary participation. Many of the hybrid networks include observations or networks from organizations or individuals who have funded systems themselves and want nothing more than to see the information used more widely. Many of these observations would be expensive to fund otherwise, so this kind of leveraged participation is a big multiplier.

It is important to note that these characteristic strengths share a “grass roots” theme, and, to be successful, existing networks have incorporated many of these characteristics. What could, and probably should, be viewed as a weakness is that many networks are principally composed of surface meteorological observations, often lacking a vertical dimension component.


A NoN requires an organizational model with qualities and characteristics of the successful networks mentioned above, but goes further to encompass a national, multi-purpose scope. These attributes include:

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