ORGANIZATIONAL MODELS OF EXISTING MESOSCALE NETWORKS

While it is tempting to divide the current organizational models into two categories (public and private), the reality is somewhat more complicated. A survey of the mesoscale networks in place today shows many different organizational models. Table 7.1 provides a rough breakdown that considers ownership of the network and related data distribution. These can be broken down into three broad categories (Table 7.2).

Organizational Strengths of Today’s Mesoscale Networks

When these networks are taken as a whole and examined from a national needs standpoint, several characteristic strengths emerge:

  • They satisfy the needs of the owners/operators. None of the example networks has become obsolete or no longer serves a purpose.

  • They have a regional or local focus. Network operators working at a local level are often aware of observing systems or networks that escape notice at a higher level. One of the keys to success for networks such as Northwest Net has been their ability to tap into networks and systems that were previously unknown to a much broader constituency.

  • They are flexible and evolutionary. Many networks start out with a single purpose, but then demonstrate value in new applications and evolve to meet those needs. They are able to demonstrate support and to command funding and/or subscription revenue. The key to success for hybrid networks is their ability to evolve and expand their scope of applications as they grow.

TABLE 7.1 Models distinguished by ownership and data distribution

Type of Network

Examples

Description

Publicly owned, Public data

ASOS, NEXRAD, RAWS

Typically thought of as the backbone of public meteorological networks

Publicly owned, Private data

DoD, HS

Public networks where information is not shared for a variety of reasons

Academically owned, IP defined

LIDAR, Ag networks, NEON

R&D networks where the intellectual property defines the data ownership

Privately owned, Private data

AWS, NLDN, TV Radar

Privately owned proprietary data

Privately owned, Public data

CWOP, MDCRS, CoCoRaHS

Privately owned networks that share data voluntarily



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