7
Organizational Attributes and Options for a Fully Integrated NoN that Meets Multiple National Needs

Organizational models in use today for existing mesoscale networks have evolved to meet relatively specific needs associated with the mission and goals of sponsoring entities, such as the National Weather Service (NWS), California Air Resources Board, Illinois State Water Survey, and Duke Energy Corporation. Regardless of the enterprise involved, there are common technical, logistical, and financial challenges associated with the operation of mesoscale networks. Numerous successful networks, both public and private, have surmounted such barriers, especially at local and regional levels, and also within federal agencies to some considerable degree.

Mesoscale observing networks exist to serve the needs of both owners and users of the data, who may or may not be one and the same. Because of diversity in the owner-provider combinations, there are a wide variety of organizational models in use. Successful networks continue to expand and grow, and their organizational structures evolve with those changes. This kind of flexibility is a hallmark of successful organizations in many applications.

As described in Chapter 6, a cohesive network of networks requires organization and leadership that is consistent and communicative with the full breadth of its membership in order to serve the varied interests. That is to say, almost no provider or user of mesoscale observations is too small or too large, or too simplistic or too technically sophisticated, to be served at some useful level. It follows that a NoN of the sort proposed here may require an organizational model different from those employed today, owing to its national scope and multi-sector participation, which implies the accommodation of some added complexity.



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7 Organizational Attributes and Options for a Fully Integrated NoN that Meets Multiple National Needs Organizational models in use today for existing mesoscale networks have evolved to meet relatively specific needs associated with the mission and goals of sponsoring entities, such as the National Weather Service (NWS), California Air Resources Board, Illinois State Water Survey, and Duke Energy Corporation. Regardless of the enterprise involved, there are com- mon technical, logistical, and financial challenges associated with the opera- tion of mesoscale networks. Numerous successful networks, both public and private, have surmounted such barriers, especially at local and regional levels, and also within federal agencies to some considerable degree. Mesoscale observing networks exist to serve the needs of both owners and users of the data, who may or may not be one and the same. Because of diversity in the owner-provider combinations, there are a wide variety of organizational models in use. Successful networks continue to expand and grow, and their organizational structures evolve with those changes. This kind of flexibility is a hallmark of successful organizations in many applications. As described in Chapter 6, a cohesive network of networks requires organization and leadership that is consistent and communicative with the full breadth of its membership in order to serve the varied interests. That is to say, almost no provider or user of mesoscale observations is too small or too large, or too simplistic or too technically sophisticated, to be served at some useful level. It follows that a NoN of the sort proposed here may require an organizational model different from those employed today, owing to its national scope and multi-sector participation, which implies the accommodation of some added complexity. 

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0 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP 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 compli- cated. A survey of the mesoscale networks in place today shows many dif- ferent 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 exam- ple 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 com- mand 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, ASOS, NEXRAD, Typically thought of as the backbone Public data RAWS of public meteorological networks Publicly owned, DoD, HS Public networks where information is Private data not shared for a variety of reasons Academically owned, LIDAR, Ag networks, R&D networks where the intellectual IP defined NEON property defines the data ownership Privately owned, AWS, NLDN, TV Privately owned proprietary data Private data Radar Privately owned, CWOP, MDCRS, Privately owned networks that share Public data CoCoRaHS data voluntarily

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS TABLE 7.2 Models distinguished by funding source, purpose, and cost of data access Model Government Funded Privately Funded Hybrid Purpose Publicly owned and Privately owned and Network of networks operated networks operated networks intended to assimilate installed to meet intended to generate observations from specific mission revenue and/or to as many sources as requirements facilitate operations possible Ownership/ Publicly owned and Privately owned, Multiple ownership operating costs funded with private and (often) some public funding Cost of data Marginal cost of Subscription fees Provider dependent access redistribution Examples • ASOS • AWS Weatherbug • MADIS (ESRL) • AWOS (FAA) • Weatherflow • MesoWest (Utah) • NOAA Profilers • NLDN • 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 net- works 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. KEY ATTRIBUTES OF AN IDEALIZED NETWORK OF NETWORKS A NoN requires an organizational model with qualities and charac- teristics of the successful networks mentioned above, but goes further to encompass a national, multi-purpose scope. These attributes include:

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP • Have enough stability to maintain continuity. • Provide incentives to existing and new networks to share data. • Establish metadata standards and provide incentives to collect and maintain these data. • Provide benefits to members, including ease of access to more and better data. • Establish and protect data/ intellectual property rights. • Establish a process to continually perform a rolling review of gaps and requirements. • Remain flexible and evolve to meet changing conditions across sectors. • Maintain a local presence for regular contact with providers and users. LOCAL ISSUES VERSUS NATIONAL NoN OPPORTUNITIES Most existing networks inadvertently create or otherwise experience impediments that are inconsistent with overarching national needs for a mesoscale observing system. Many of these can be solved in a straight- forward manner if prevailing thought can be shifted from a strictly local reward system to a more global one. Incentives for Metadata The case for metadata was discussed in Chapter 6. Suffice it to say here that, given the need to serve multiple national needs, some powerful incen- tives will be required to generate and collect metadata. A viable business practice would be for a national coordinating organization to pay providers for metadata, according to strict specifications, in order to achieve a uni- formly high standard of compliance. For example, the Federal Highway Administrations’ Clarus program has a system in place to compensate state transportation departments for the labor involved in assembling metadata for the observations they provide to Clarus. This is a good example of what could be achieved on a broader scale of applications. The cost of incentives for metadata compliance would be a small fraction of the ongoing costs asso- ciated with acquisition, operation, and maintenance of observing systems, the majority of which will be borne by agencies, corporations, and other organi- zations that conduct “business as usual” to serve their specific missions. Filling Gaps and Avoiding Redundancies There are several examples of locations with multiple separate sur- face observing stations within a few meters of each other, all owned and

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS operated by different organizations. Sometimes this redundancy enables comparison of measurements from different networks. However, different agencies or entities may install duplicative systems, because they lack access to data from the other network, or do not trust data from sources other than their own. Another example is that of separate mesoscale networks that cover an intersecting geographic area with different sites. Often these situa- tions result from an unawareness of existing networks. This leads to a condition of “false sparsity” when the reality in some instances may be a richly observed domain, provided the assets from multiple sources are coordinated. Since expense is always a barrier, this type of organizational duplication is usually unnecessary and always undesirable. Most surface networks are implemented to meet a specific set of local requirements, without consideration of national needs. However, the effect of gaps in the weather forecast system is usually experienced remotely. For example, forecast errors may be experienced hundreds of kilometers down- wind of mountains, because the sparsity of observations in the mountains, consistent with low population density, handicaps the initial conditions in the forecast, and the effect propagates downwind. A viable business practice would be to provide incentives for investment in remotely located observing stations to improve local forecast skill. Often this will require the participation of provider organizations that are only peripherally or indirectly served. Consistent Data Collection and Archives Each network has evolved its own data collection and archive capa- bilities to meet its own needs. While hybrids such as MesoWest, Meteoro- logical Assimilation Data Ingest System, Northwest Net and others have greatly improved upon the base condition at regional scales for weather applications, these generally fall short of an accessible useable database on a national scale for all major applications. A viable business practice would set standards for and maintain a genuinely accessible and useable national database for all major applications. Core versus Context of Partner Organizations Certain organizations view mesoscale weather networks as an essen- tial part of their “core” business or competency. Other organizations require similar information for “context” in decisionmaking, but view it as much less important to their overall mission. This difference in priority is often a barrier to coordination and sharing of information. A viable business practice would offer incentives to “context providers” for meet-

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP ing appropriate standards, thereby contributing to the broader utility of their data. Intellectual Property Rights and Data Ownership “Ownership” of the data collected by a mesoscale network can often be a barrier to its use. Prospective users may be unwilling to live with restrictions placed on redistribution or may not understand the rationale for such restrictions. On the other hand, some organizations may assume that provider “ownership” implies legal liability if data are shared or used outside their organization and then found to be missing or inaccurate. One way to finesse such objections is to release station data in real time, but only for assimilation into NoN analyses. Raw station data would remain proprietary to the provider and available on a fee-for-service basis for point-specific subscriber applications. The fabric of society is very complex in these respects, and such circumstances require individual attention. A viable business model should include legal empowerment to negotiate data access and to facilitate data restrictions on a case-by-case basis. Legal empowerment should include advocacy for and being the beneficiary of “hold harmless” legislation in the case of liability concerns. Multiple Funding Sources and Creative Solutions A common barrier likely shared by every mesoscale network is the generation and application of resources adequate to the task. This applies equally to the acquisition of new networks and/or observation systems and to the maintenance and operation of existing networks. On a federal scale, there are institutional (e.g., congressional appropriation) barriers to cost sharing or cost transfers from one agency to another and rigidly enforced restrictions associated with funding mechanisms to non-federal and non- governmental providers and users. A viable business model should have significant flexibility to effect the transfer of funds and to exchange in-kind resources with alacrity among different types of organizations. Proposed Roles of Partners The Committee has noted the wide dynamic range in the scale and sophistication of providers and users, ranging from individuals to federal agencies and Fortune 500 corporations. Somewhat independent of the overarching organization (business) model, it is useful to define four broad tiers of NoN participation (Table 7.3). While each tier is heterogeneous in its makeup, the tiers each define a typical level of technical expertise and/or mission similarity in the operation of mesonets and in the treat-

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS TABLE 7.3 Characteristic tiers for participation in the NoN Tier 1 Tier 2 Tier 3 Tier 4 Federal Agencies State and Local Corporations in Cooperative Observers Government Weather-Sensitive Agencies Weather Hobbyists, Providing Weather Enthusiasts Publicly and Information Privately Operated Services Authorities, and Districts For the public good Mainly for public Mainly enables or Mainly for public good serves business and good, education, and Serves federal industry self satisfaction missions Serves regional and local missions Local, regional, Surface meteorology National backbone national plus some soil including the most Regional backbones observation only, with costly infrastructure contribute piecewise Mainly surface minor exceptions to enhance meteorology 3-D atmospheric national mesoscale and atmospheric A shaky backbone for observations resolution composition local climate records Reasonably well Primarily surface, Distribution of Very high density maintained and soil, water, and air special observations mainly in urbanized systematically quality often limited in real areas operated networks Some upper air obs time Data often contributed High-quality Operation, Operation, to hybrid networks accessible archives maintenance, data maintenance, data access and archives access, and archives Operation, etc. highly are highly variable are highly variable variable ment and communication of datasets collected from them. This generaliza- tion doesn’t work in all aspects of all cases. For example, there are many instances of high technical expertise in lower-tier groupings that share related missions. Tier I: Federal Agencies Federal agencies are tasked with serving specific missions, the scope of which determine and limit a given agency’s infrastructure and services. Collectively, the federal agencies are at a high level of technical expertise and contribute a sizeable fraction of mesoscale meteorological and other atmospheric observations. However, the scope of the combined federal agency missions and the implied observational infrastructure fall well short

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP of the national mesoscale constituency as currently vested. A summary of federal agency infrastructure is provided in Chapter 4 and Appendix B. In the case of National Oceanic and Atmospheric Administration, its mission is focused on a suite of weather forecasts and warnings, climate monitor- ing at regional to global scales, and oceanic forecasts and monitoring. In so doing, NOAA cuts a broad and deep swath across the enterprise. As tier 1 participants, federal agencies could provide a national tech- nical and operational backbone for the NoN. NOAA is particularly well- suited to lead this effort. Where consistent with their missions, several federal agencies could provide guidance and training, and operate major observational and computational infrastructure. Especially prominent in this group are those surface-based remote sensing instruments necessary to map and profile lower tropospheric conditions with lidars, radars, and radiometric-spectroscopic systems. Each agency’s contribution would be targeted, fully consistent with its particular mission, and non-duplicative of infrastructure and services provided by other member organizations. Collectively, the agencies would benefit from infrastructure and services provided by other organizations and the benefit derived from an enhanced level of cooperation and coordination among themselves. Tier II: State and Local Government Agencies, Publicly and Privately Operated Authorities, and Districts State and local organizations make extensive use of mesoscale data. This information is critical to routine decisions for law enforcement, sur- face transportation, roadway safety, flood hazards, water and air quality monitoring and warnings, flood control, operation of dams and spillways, fire weather monitoring and prediction, avalanche control, debris flow fore- casts, drought monitoring, agricultural outlooks and warnings, etc. Most of these “public good” entities, whether operated publicly or privately, currently own, operate, and maintain mesoscale observing assets. Some are highly vested in sophisticated equipment and communications systems, such as statewide networks of surface stations, profiling systems, stream and floodway gauges, and urban scale monitoring of atmospheric pollutants, toxins, and other constituents. Usage of this information is typically local or regional, often with little or no co-benefit among various applications shar- ing common domains. While federal agencies cast a broad net of advanced monitoring systems, state-based and local-based systems collectively are far more numerous, providing spatial and temporal detail and atmospheric composition information, which is essential to many applications. The stove-piped nature of this circumstance has the effect of creating an envi- ronment of “false sparsity.” That is to say, each application may operate with datasets of questionable adequacy, density, domain size, and temporal

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS resolution amidst many other data sources, which could contribute to their objectives and to the benefit of many. State and local agencies, authorities, and districts, both public and privately operated, currently serve as regional backbones for mesoscale and urbanized area observations. The in-situ component of these assets in populated areas is truly mesoscale in its spatial density, unlike the synoptic scale focus of federally supported systems. However, large gaps in meso- scale coverage exist in less populated regions, especially in regions of com- plex terrain, where the heterogeneity of conditions is both prevalent and most likely introduces uncertainty in decision making. Federal incentives in the form of cost sharing should be provided to state and local organi- zations, which could fill critical gaps and enhance the overall quality and consistency of mesoscale monitoring. Such cost sharing, together with non- remunerative enablement services, is a critical pathway toward a national mesoscale monitoring capability. Tier III: Corporations in Weather-Sensitive Sectors and/or Providing Weather Information Services A sizeable fraction of corporate America is weather sensitive and there- fore requires weather and climate information either to remain competitive or to gain an edge on the competition. Corporations making intense use of weather data whose needs are not met from publicly available sources fall into three categories: (1) those that require specialized information and choose to build the observational and computational infrastructure to serve their exclusive purposes, (2) those who need similar information and contract for it from private weather service providers, and (3) the private weather service providers. The preponderance of applications is intrinsically microscale (e.g., vineyards and orchards), urban-scale, mesoscale, or meso- climatological, though some applications are continental in scope. The existence of a national network of networks would clearly be of net benefit to this “community” despite the fact that datasets from corporate sources often have highly specialized exposures and are associ- ated with restricted access. We believe that a carefully crafted risk-reward structure could enable the private sector to better serve its own needs, stimulate private investment, lessen restrictions on data access to others, and improve the utility and profitability of weather and climate informa- tion for all. The exploration and implementation of a structure that stimulates both public and private investment, maximizes access to mesoscale data, and adequately shields legitimate proprietary interests is squarely in the national interest. Therefore the Committee views this aspect of the weather-climate enterprise as a compelling case for a hybrid organization approach.

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP Tier IV: Cooperative Observers, and Weather Hobbyists and Enthusiasts NOAA maintains a Cooperative Observer Program, which is an impor- tant part of the climate record and therefore important to a NoN. It is dense enough to contain significant information at the mesoscale. However, most data have not been available in real time, and the observations are taken only daily, thus minimizing their utility in operational meteorology. This contrasts with the thousands of weather hobbyists and enthusiasts who operate their own professional-grade surface weather stations, often to a reasonably high standard, and report these data in real time or near real time. As reported in Chapter 2, citizen participation at group and individual levels is rapidly expanding with regional and quasi-national network cov- erage, and is usually provided free in exchange for nothing more than the ability to see their observations included in a larger program. Historically such data have been dismissed or viewed with skepticism. However, with the advent of inexpensive digital electronics, solid state sensors, and Inter- net communications, such observations are known to have real value in limited applications, especially where organized professional observations are sparse, applications can accept large uncertainty, or where especially fine spatial resolution is desired, such as urbanized areas. In an environment of nationally defined standards and accurate and complete metadata, observations of many hobbyists and enthusiasts can play an important role in serving multiple national needs at the mesoscale. Recreational activity may benefit most given the exceptional spatial density, a good frequency of such observations, and the less stringent requirements for accuracy and precision. Such observations can also serve a confirmatory role for quantitative analyses and likely would contribute to data numeri- cally assimilated for surface analyses of broader utility. Therefore, incorpo- ration of Tier IV data should be beneficial for limited network applications, provided that appropriate quality-checking is performed. ORGANIZATIONAL MODEL OPTIONS The preceding sections of this chapter present a somewhat abstract view of the organizational requirements for a successful new national mesoscale network. In the Committee’s judgment, none of the existing networks or their organizational models were envisioned to meet the needs of a multitude of national providers and users having diverse interests and requirements. Below we discuss some desired organizational characteristics that could facilitate the functions previously described in Chapter 6 and the preceding sections. Subsequently we examine a spectrum of potentially applicable models and offer some qualitative judgments on them.

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS Desired Characteristics In order to successfully meet the national needs identified in this report, the organization should be capable of certain desired characteristics. 1. Effecting partnerships • The organization should be adept at coordinating, enabling, and fairly representing the full dynamic range of public and private contributions, large and small. • Issues such as ownership of data, cost and pricing of datasets, and redistribution rights need to be addressed in a flexible, consis- tent and equitable manner. • National strategies on building networks versus buying data- sets need to be evaluated across the full spectrum of potential solutions. 2. Economic scale • The organization needs to be large enough to make economic sense and to achieve certain economies of scale (e.g, large enough to coordinate and to provide core essential services), but small enough that it can remain flexible and adaptive to both users and providers needs. 3. Sustainability • The organization must be stable and have a basis for longevity in order to attract both users and providers. • The organization needs to offer incentives of various types, including but not limited to remunerative incentives, to shape an optimal and efficient NoN. • The organization must offer added value to users, who may face costs for conditioning and ease of access to certain datasets. User-valued services include consolidated datasets, uniform and complete metadata, and data quality-checking measures. Categories of Models Considered At least eight broad categories of organizational models may be con- sidered for a NoN. When we refer to these models the frame of reference is focused on those facilities and services that are required to implement the added value of the NoN, not the facilities and services currently provided by hundreds of organizations to support the current collection of largely independent networks. Implicit in this assumption is that all members will continue to serve their specific mission needs with individual networks and related infrastructure in a manner similar to current practice, but subject to new standards and practices, as previously described, to derive the collec-

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0 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP tive benefit. Only the infrastructure and services unique to NoN would be provided by a new organization (e.g, the essential core NoN services). Over time, additional responsibilities and authority could be assigned to the new organization by the NoN as deemed appropriate by the membership. The eight categories for organization considered are as follows: • Lead Federal Agency. One agency would provide and coordinate essential core services for a NoN, having received and secured a commit- ment from other agencies that have mission requirements. • Confederation of Federal Agencies. The federal government would both implement and serve a new management unit that would be governed by a confederation of agencies. The management unit might have multiple duties spread across agencies or be staffed by the agencies and seconded to the supervision of a designated lead agency. • Multi-level Government Confederation. Similar to the above but directly involving state and/or local government leadership, staffing, and funding. Owing to the large number of confederated entities, some form of representative governance would be invoked. • Government-Industry Confederation. Similar to the above differing only in the mix of partners and governance structure. • Publicly Chartered, Private Non Profit Corporation. Similar to the Corporation for Public Broadcasting, National Public Radio, and the U.S. Postal Service, this organization would be chartered and funded by the U.S. Congress for defined aspects of the broader enterprise. It would be able to receive and provide funds to public and private organizations as appropri- ate to effect the NoN mission. • Privately Chartered Non Profit Corporation. Similar to the above without a broad public mandate, but able to provide services to and receive services from publicly and privately funded organizations together with appropriate transfers of funds. • Private For-Profit Corporation. Services, such as the essential core services, provided on a for-profit contractual basis, individually and col- lectively, with both public and private customers. • Seeded Viral NoN. Essentially an extension of the current collec- tion of networks, with the added impetus to mitigate deficiencies through a consensus-building process with a standing committee. Targeted incentives would be provided by federal agencies to derive greater benefits in national- scale applications from local and regional networks. Each of these models, if adequately implemented, could improve the current state of mesoscale observations to meet multiple national needs. In principle, each has mechanisms available to it to stand a chance of improv- ing coordination and information exchange. The issue boils down to one

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS of efficiency, effectiveness, and inclusiveness with respect to the NoN enter- prise and its operations. We asked these questions: • What degree of centralization is needed to achieve a balance? • Is a standing committee and consensus building enough? • Can a federal agency afford or be permitted to interact responsively and effectively with such a large dynamic range of public and private pro- viders and users (most of whom have applications unrelated to the mission of the federal agency)? • Can or should a for-profit corporation provide the essential facili- ties and services for critical national-scale “public good” needs? • Given the mixed history of federal agency collaboration, is it likely a comprehensive confederation could be assembled and function in the absence of centralized budget authority? • How many agencies and other organizations is it practical to con- federate for the purpose of leading and providing essential core services of the NoN? On the basis of information previously presented in this report con- cerning (1) the current breadth of investment in the mesoscale observations enterprise, (2) the changes required to markedly increase the utility of exist- ing observations, and (3) the establishment of pathways toward improved observing capabilities through diversity of investment, the Committee has reached the following judgments about which organizational options should be dismissed and which are worthy of due consideration. Organization Options Dismissed Lead Federal Agency A single federal agency has a congressionally authorized mission that is quite narrow with respect to the mesoscale observations enterprise. To obtain authorization to perform the work of a centralized authority for the NoN would be controversial at best, peripheral to core programs of the agency, and possibly prohibited by statute, and it presents difficulties with respect to the transfer of funds and other resources among many types of public and private organizations. Multi-level Government Confederation, Government-Industry Confederation Confederation at multiple levels of government is judged to be imprac- tical to implement, involving hundreds if not thousands of provider-users

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP who would somehow have to organize through representative means, such as a governing board, to lead and perform the centralized effort. A govern- ment-industry confederation, while appealing, has similar drawbacks, since industry has relatively few large players involved in mesoscale observations per se, the field being dominated by large numbers of small to medium corporations and companies with needs tailored to niche markets. In effect, this adds complexity to the multi-level government confederation. For-Profit Private Corporation The for-profit private option is judged to be an inappropriate framework to serve the whole of essential facilities and services related to national-scale “public good” needs. For-profit participation is highly valued and should be targeted where appropriate. Options Worthy of Due Consideration Confederation of Federal Agencies Approximately 10 agencies could have a significant stake in the NoN. The concatenated agency missions cut a broad swath through the NoN constituency. Agency representatives could form an effective joint manage- ment team, though historically agencies have had difficulty with decentral- ized funding authority beyond partnerships of two or three agencies. There remain difficulties associated with the transfer of funds and other resources among the many types of public and private organizations in a NoN. While many possible implementations of confederation governance can be envisioned, one example could be a board, overseeing and relying on a lead agency for day-to-day centralized services. In this example, the governing board could be similar to the Committee of Earth Observ- ing Satellites (CEOS), and the federal agency responsible for day-to-day operations could be NOAA/NWS. CEOS successfully arbitrates the vari- ous requirements of both users and providers of weather satellites and helps to provide guidance in both operations and acquisition of satellite systems. NOAA would be an obvious choice for lead agency responsibilities in this confederation. NOAA/NWS successfully operates several programs including the NEXRAD radar network and the Automated Surface Observ- ing Systems (ASOS), even though these programs are jointly owned by three federal agencies (NOAA, Federal Aviation Administration, and Department of Defense). Strengths of a confederated federal agency organization include eco- nomic scalability and the relative stability associated with exclusive or an

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS extremely high fraction of federal funding by co-sponsoring agencies. The attractiveness of this model is that federal agencies are capable of providing the continuity and longevity that successful networks require. On the other hand, recent experiences associated with Earth system observations (e.g the “Decadal Survey”) suggest questions about the stability of this model, which usually is wholly dependent on both the funding and the organiza- tional support provided by the federal agencies. Mesoscale observations have a more diverse set of funding sources, which could be used either as an argument for or against the federal confederation model. The major weakness of the confederation model lies in the likely defi- ciency of public-private partnerships, which are required for success, where success is defined as meeting the needs of the broader enterprise, not just the concatenation of the federal missions. An organization led by large agencies tends to respond best to partners of like scale. Smaller organiza- tions and individuals, which are an essential part of the broader mesoscale enterprise, could become disenfranchised and systematically withdraw from participation in the NoN. Providing a true partnership between federal agencies and state govern- ments, academia, and the commercial sector that will make up a large part of the user/provider base is a huge challenge for this model. The organi- zational culture of public and private entities is so different that friction is often inevitable. Examples do exist of successful partnerships, but these have generally been limited in scope and longevity. This model will suc- ceed only if it can overcome the cultural inertia that makes it difficult to achieve true investment in both the private and public sectors. Nonetheless, despite the debate over NOAA’s current Public/Private Partnership Policy, the National Research Council report titled Fair Weather (2003) called for more partnerships of just this sort. Seeded Viral Model (SV) The viral or organic-Wiki model is a continuation of the current patchwork of organizations and networks that make up the mesoscale observation system in place today. Instead of a central entity to oper- ate and administer to the needs of a NoN, the SV model would have networks which would come and go and rely on the community of users and operators to figure out how to collect data centrally, set standards for metadata, etc. Users would go to different organizations to look for data, much as they do today. The risk/reward ratio for such networks is high since costs are low but the data may be of uncertain value. Like Wiki encyclopedias, the model exists because there is a demand for the service, there is a lack of a (financially) competitive model to provide that service, and there is willingness to contribute to make it occur. This model

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP is anarchic in structure and has little centralized control or assurance of its continued existence. The “seeded” aspect of the SV model are resources of federal origin to augment dominant local forces (that establish most sites) by adding moti- vation in the national interest and the broader public good. For example, incentives could be offered to encourage development in data-sparse regions in order to strengthen “remote impact” properties of the network, espe- cially as warranted by numerical weather prediction. It is easy to envision data providers voluntarily putting together a Wiki-type library of data resources to enable users to find the data they would like. Such a model would have low administrative costs. In fact, the World Meteorological Organization’s Global Atmosphere Watch has recently endorsed a European data center on this model that provides “one- stop shopping” for satellite data but without significant input of intellec- tual property. Considerable architecture is being developed that automates the search process for data and the delivery of components from various providers. Public-private partnerships are the key strength of the current system, and would be the core strength of the SV model. If one entity or organiza- tion wants data, and another has data to provide, they can usually work out a mutually agreeable arrangement. Indeed, this is the key to the suc- cessful mesoscale networks in operation today, and also the key to their continued growth. Most prospective organizations do not have the economic scale or sufficient funding to independently meet all of the requirements for NoN membership identified in this report. The lack of stable funding, combined with the ad-hoc nature of many of the existing networks, will make it dif- ficult for this model to provide for long-term stability. The organic nature of such a network parallels the life cycle of living systems that are born, thrive, founder, and die, which has advantages and also risks, especially regarding stability. Statistically speaking, a modest evolution of the current condition is among the more likely outcomes for a NoN. The SV model is suited to that description, so it behooves the mesoscale observations enterprise to consider an evolutionary path along such lines, especially as a temporary means to improve the utility of existing data and the encouragement of network gap-filling. As has been said earlier in this report, the system we have today works at a certain level, but it lacks consistent quality, cohesion, coordination, and adequate investment to meet national scale needs, which intersect but also are additive to local-scale infrastructure investments.

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS Preferred Options Private Non Profit Corporations, Either Publicly or Privately Chartered After careful consideration of many options, the Committee is of the belief that some form of hybrid non profit corporation is the best organi- zational match to the NoN circumstance. Hybrid non profits are capable of broad reach, considerable flexibility, and minimal statutory restrictions regarding interactions with a wide array of vested interests. Hybrid public- private organizations offer the best chance to establish and cement a true partnership among all levels of government and many species and sizes of organizations in the private sector. Privately chartered non profits often prosper under the rules governing 501(c) 3 organizations. This is a federal code that governs exemption from certain taxes for scientific and educa- tional activities, among many others. Several organizations related to geophysical observations and research have been created under the management of 501(c) 3 corporations. Among these organizations is the Earth Science Information Partnership (ESIP), which is sponsored by NOAA, National Aeronautics and Space Adminis- tration and United States Geological Survey (http://www.esipfed.org). Since its inception it has grown through the contributions of data and sources both from the agencies as well as from other voluntary contributors. ESIP is governed by a parent 501(c) 3 corporation, the Foundation for Earth Science, which was established in 2001 to support scientific programs and organizations that collect, process, and analyze science-based Earth science information for a broad range of users. It is dedicated to bringing the most current and reliable data and data products to bear on the environmental, economic, and social challenges. The corporation is governed by a board of directors from academia, government, and industry. Another example of a 501(c) 3 corporation is the University Corpora- tion for Atmospheric Research (UCAR), which operates several technical and scientific programs. Among these is Unidata (http://www.unidata.ucar. edu), which has been a force in atmospheric data distribution development and services. Some of the developments and services have been related to mesoscale data distribution and related networking issues. Through the UCAR 501(c) 3, Unidata was initially launched by the National Science Foundation for university-based atmospheric research applications, but now also draws support from several public agencies and some private sources for various applications, some of which are in operational meteo- rology. UCAR also operates the National Center for Atmospheric Research, which is a Federally Funded Research and Development Center (FFRDC). FFRDCs are often the principal motivation for establishment of 501(c) 3 corporations.

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 OBSERVING WEATHER AND CLIMATE FROM THE GROUND UP Privately chartered non profits, such as 501(c) 3 corporations, must rely on the strength and influence of their governing board and the moti- vation of the sponsoring agencies themselves to succeed in satisfying a national-scale mandate that spans various public and private sectors. This is a fundamental distinction between privately and publicly chartered non profits, the latter having a clear national mandate and direct access to con- gressional funding. Corporation for Environmental Monitoring (CEM) In this model, a congressionally chartered, non profit corporation would be created to manage and operate a NoN. For the sake of example, this hypothetical corporation will be referred to as CEM. CEM would be modeled after existing publicly chartered corporations such as National Public Radio (NPR), the Corporation for Public Broadcasting (CPB), or the U.S. Postal Service. In the case of CPB, a board of directors sets policy and establishes programming priorities. The President of the United States appoints each member, who, after confirmation by the Senate, serves a 6 year term. The board, in turn, appoints the president and chief execu- tive officer, who then names the other corporate officers. CPB governance includes both users and providers. As a publicly chartered corporation, CEM would collect revenue from users of a NoN and apply these to offset operational expenses. Federal funds would be used to facilitate the establishment and provision of essen- tial core services and to support performance incentives associated with the NoN, for example in the generation of metadata. Additional activities may be supported as required, including NoN design studies, evolving imple- mentation strategies, and enablement services to new networks as created by the agencies and other providers. The CEM role described is analogous to the CPB model. The CPB is allocated money from Congress and then uses that money to fund its member stations and organizations for a variety of purposes, including the production of content, upgrades to existing facilities, and development of new technologies. Another example is NPR, which performs functions strongly related to CPB and directly serves a national network of radio stations. NPR oper- ates as a non profit business that produces both news and entertainment products for its member stations and charges the stations fees that support the operation. Thus, with a limited federal subsidy, NPR is able to operate independently of the federal government and still serve its member organi- zations. NPR does not build or operate radio stations. Similarly, under this proposal, CEM would not build or operate observing networks.

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 ORGANIZATIONAL ATTRIBUTES AND OPTIONS A strength of a publicly chartered non profit corporation is that the organization is ideally positioned to effect a true public-private partnership. In principle, it can be responsive to user/provider organizations of all types and sizes. It has a federal government mandate, but it is not tightly bound by statutes, regulations, or relatively narrow agency missions in the breadth or the sectors of the community served. It constitutes a vehicle of conve- nience, through which the federal agencies can better accomplish some of their goals and objectives for the greater public good. An organization such as CEM would be at least partly self-supporting, and as such it should have the stability required to endure. However, as a publicly chartered corporation, some federal subsidy to CEM would be required on an annual basis. If this subsidy were ever eliminated, it could have a detrimental effect on the organization. For example, the U.S. Postal Service could not survive without a federal subsidy, even though it raises a considerable amount of revenue. The hypothetical CEM model provides all the necessary characteristics needed. It is easy to envision this hybrid non profit corporation, formed for the expressed purpose of coordinating the operation of environmental monitoring networks, collecting data, charging users of those observations for their use, and using the fees to fund the data collection. Federal, state, and local governmental initiatives could expand the NoN and offer incen- tives to others for the provision of additional observations that are carefully targeted to fill critical national needs. A RECOMMENDED ORGANIZATIONAL MODEL Recommendation: The United States should establish a robust and economically viable organizational structure to effect the national implementation of a multi-purpose environmental observing network at the mesoscale. It may be preferable for this organization to take the form of a publicly chartered, private non profit corporation. A hybrid public-private organizational model would stimulate both public and private participation over a wide, dynamic range of investment and applications; maximize access to mesoscale data; and effect a synergism between the public good and proprietary interests.