Attachment_I-PWS.pdf

ATTACHMENT I – Performance Work Statement

1.0 Background

In 2008, the National Academy of Sciences (NAS) released Observing Weather and Climate

From the Ground Up: A Nationwide Network of Networks. This NAS report provides a framework for filling gaps in the Federal Government’s meteorological, hydrologic and related environmental observing capabilities, to enable significantly improved forecasts and warnings for high-impact, local-scale weather events. The framework specifies that NWS and the Federal

Government should effectively leverage existing observing networks that are owned and operated by non-Federal parties (e.g., the states, academia, and the private sector), in addition to deploying new Federal systems. NAS has since released additional reports, including When

Weather Matters: Science and Services to Meet Critical Societal Needs, and Urban

Meteorology: Forecasting, Monitoring, and Meeting User’s Needs, which endorse the key observing systems concepts and recommendations of From the Ground Up.

In response to the NAS, the National Weather Service (NWS) began the National Mesonet

Program (NMP) in Fiscal Year 2009. The program initially served as a mechanism for purchasing data from a small number of non-Federal surface observing networks (“mesonets”) located mostly in the south-central U.S. The NMP has since evolved into NWS’s primary program for purchasing non-Federal data from a wide variety of observing networks, including surface mesonets operating in all 50 states, as well as data from networks that provide observations of wind, temperature, moisture, and related quantities, throughout the vertical extent of the atmosphere. With the ongoing expansion to new types of observing systems and platforms, the principal objective of the NMP is to contribute significantly to community efforts to implement key recommendations contained in the aforementioned NAS reports and build a comprehensive “Network of Networks.”

More recently, The Weather Research and Forecasting Innovation Act of 2017 was enacted and signed into law. Title III, Section 302 of this legislation explicitly authorizes and directs NOAA and the NWS to expand and enhance its procurement of observational data from commercial sources:

“…The strategy shall assess the range of commercial opportunities, including public-private partnerships, for obtaining surface-based, aviation-based, and space-based weather observations. The strategy shall include the expected cost-effectiveness of these opportunities as well as provide a plan for procuring data, including an expected implementation timeline, from these nongovernmental sources, as appropriate.”

The NMP is an existing NWS program that is already engaged in these activities, and it is ideally positioned and formulated to fulfill this authorization, particularly for surface-based and aviation-based observing systems.

NWS desires to continue progress toward the establishment of a Network of Networks capability that meets the needs of a broad and diverse set of constituents across the weather enterprise, by purchasing observational data and related services from a variety of non-Federal observing networks. NWS further desires to expand the number of stations from which NMP procures data, in the spirit of The Weather Act. This will enable NWS to improve forecasts and warnings for severe weather, enhance its high-resolution numerical weather prediction capabilities, and achieve effective collaboration among disparate network operators in the Network of Networks paradigm and in the spirit of The Weather Act, with the NMP as its programmatic basis.

Extending NWS’s Observing System Capabilities

The NMP enables NWS to extend the reach of its own “backbone” meteorological observing capabilities, by leveraging observations from non-Federal networks whose observing platforms are deployed at significantly closer spacing (smaller distance between platforms) than NWS’s own platforms. The NMP further facilitates access to specific types of near-surface observations not routinely gathered by NWS’s own operational systems, such as soil moisture, soil temperature, and solar radiation. In addition to tapping platforms that provide hydrometeorological observations near Earth’s surface, the NMP also provides NWS access to non-Federal observations of wind, temperature, moisture, and related quantities, throughout the vertical extent of the atmosphere, and observations from mobile platforms such as commercial vehicles and commercial aircraft. All of these various types of non-Federal platforms allow

NWS to observe hydrometeorological quantities with much greater fidelity than would otherwise be permitted with NWS’s backbone systems and platforms alone. Thus, the NWS vision for the

NMP encompasses multiple types of observing technologies, well beyond the subset of near-surface in-situ, fixed-location technologies that have historically been implied by the term

“mesonet.”

For all types of observations that are part of the broader NMP mix, NWS will leverage only those networks that aspire to national and international standards for siting, operations, and provision of high quality data that is suitable to both NWS applications and the breadth of applications of mesonet observations across the broader weather enterprise.

Metadata

As discussed in the NAS reports referenced above, the provision of comprehensive and accurate metadata by all participating networks is key to the Network of Networks paradigm. Metadata, literally, “data about the data,” describe how raw observations are measured, processed, and disseminated as products to users. Metadata provide the context for the observation, enabling users to improve their understanding of observational error characteristics and limitations;

surgically select data that is appropriate for a particular application; and if selected, properly weight the data’s contribution to the application in question.

NWS recognizes that mesonets and non-Federal networks are often built and operated for specific applications by a diverse set of stakeholders across the weather enterprise, and as a result data and metadata standards may diverge from historical federal standards. NWS also recognizes the broad consensus across the enterprise that operators of environmental observing networks should aspire to high standards for provision of metadata, to minimize ambiguity for the underlying raw data. Given that NWS desires to extend the reach of its backbone observing capabilities via the NMP, networks aspiring for inclusion must ascribe to the highest possible industry standards for metadata and provide it via a systems approach, using established and consistent processes and protocols. The tables in Appendix A-Metdata Attribute Tables provide a sample of metadata attributes ranging in complexity from basic station location information and communications characteristics, to detailed information about siting and exposure, instrument precision, data logger algorithm characteristics, maintenance, and quality control.

Additional information on standards and processes for reporting metadata for mesonet-type observations are found in Appendix B-References.

MADIS

NOAA has developed and transitioned into operations the Meteorological Analysis and Data

Ingest System (MADIS). MADIS is an IT system that provides a pathway into NWS for data streams from many non-Federal networks, and serves as a repository for metadata information for those networks. In essence, MADIS collects non-Federal observations and their metadata in real time, and makes the information accessible to NWS field offices that use these observations in the forecast and warning process. MADIS also provides data access services for users who are external to NWS, in the broader weather enterprise, including many non-Federal partners.

NWS wishes to continue using MADIS as the primary IT conduit for NMP observations and as the repository for regularly updated and extended metadata for mesonet data sources. This PWS does not extend to operation of the core MADIS functionality itself, but only to data and services provided to the government via the MADIS pathway. MADIS will continue to be operated by

NWS as an operational system. In some circumstances, and at the direction of the Contracting

Officer’s Representative, other arrangements may be made to deliver certain data streams to particular NWS field components using means other than MADIS, as best suited to meet NWS mission needs and contractor capabilities.

Regarding any restrictions on access to Mesonet data by external users: MADIS will manage restrictions in accordance with distribution categories prescribed by participating networks.

Appendix C provides the distribution categories that have been applied to networks that have previously provided data to NWS under the auspices of the NMP.

2.0 Requirements

The contractor shall meet all Requirements defined below in sections 2.1 through 2.4, for the entire Ordering Period.

2.1 Data-Related Requirements

NWS requires the contractor to provide the following data and services as described and referenced in Section 1.0 Background:

2.1.1 In-Situ meteorological observations (wind, temperature, moisture, pressure, precipitation) from fixed-location platforms in the lowest 10 meters of the atmosphere, and where available at these observing stations, soil moisture, soil temperature, and solar radiation.

2.1.2 Temperature, moisture, wind speed and direction, and other related meteorological fields and associated parameters, through the vertical extent of the troposphere, including at multiple heights and derived with fixed-location ground-based remote sensing technologies (“vertical profilers”);

2.1.3 Vertical profiles of temperature, moisture, wind speed and direction, and related fields, on ascent and descent paths of aircraft in the vicinity of major and regional airports;

2.1.4 Road-surface temperature and related meteorological and environmental observations primarily from mobile platforms such as commercial delivery vehicles;

2.1.5 Observational data services, including collection, formatting, metadata handling, and provision to the government (via MADIS where applicable) observations that are obtained via aggregators of smaller networks of fixed-location platforms that are not directly affiliated with the NMP.

2.1.6 2.1.1 through 2.1.3 above from additional platforms and networks that are not already providing data to NWS via the NMP and in accordance with the direction of the aforementioned Weather Act.

2.2 Platform Requirements

2.2.1 The contractor shall provide section 2.1 Data-Related Requirements, in the aggregate, from non-Federal networks consistent with the description in Section

1.0 Background, and consisting of fixed and mobile platforms, as appropriate for a given network.

2.2.2 If a contactor provides any observational data from a given platform, mobile or fixed, all available observational data as defined in 2.1 Data-Related

Requirements shall be made available from that platform.

2.3 Geographical Requirements

2.3.1 Fixed platforms offered as part of the contractor’s solution shall be located in all

50 states.

2.3.2 Mobile, ground based vehicles providing observations shall be located along roads and highways between and within population centers; Commercial aircraft shall provide data on ascents and descents near airports. Aircraft shall provide data to the full extent of the geographical domain covered by a given network.

2.3.3 If data from a given network and platform within a specific state has been previously provided to the government under the auspices of the NMP, data from that network and its platforms or substantially similar data within that state shall be provided to the government as part of the contractor’s aggregate solution.

2.4 Performance Requirements

The contractor shall:

2.4.1 Coordinate and establish relationships with networks that use standards to site and operate observation stations;

2.4.2 Maintain detailed metadata that address the attributes, formats, and standards referenced in Appendices A (Attribute Tables) and B (References);

2.4.3 Leverage existing infrastructure (MADIS), in coordination with the government, to efficiently and routinely update station observations and metadata;

2.4.4 Ensure that Individual networks shall have no less than 95.0% availability for all potential reports averaged across all stations over the period of a month, with individual reports provided with a nominal frequency of one report every 5 minutes;

2.4.5 Update metadata weekly;

2.4.6 Provide the government with physical access to a mesonet’s individual station and data processing facilities within 5 business days of the government’s request to enable the government to audit all metadata. Audits may include requests for data processing code and swap-out of sensors for independent performance testing;

2.4.7 Provide quarterly status reports to the government, describing the progress in fulfilling 2.4.1- 2.4.6, including tracking of system performance issues; and

2.4.8 Provide notification to the government when system outages of more than 1 hour occur.

2.4.9 Provide notification to the government on data distribution categories corresponding to Appendix C (Data Distribution Categories) for each network.

3.0 Transition Period

The first month of the contract will constitute as the transition period from the incumbent contractor to the contract awardee. This allows the contractor to ensure a continuity of service and provide the required data to the NWS without interruption while transitioning from the previous contract. At the conclusion of the transition period, the contractor shall be responsible for performing all requirements identified in sections 2.1, 2.2, 2.3 and 2.4.

Appendix A

Metadata Attribute Tables

Table 1. Station Attributes

Attribute Type Description Reporting Format

Station Name Official station name Character string (<= 10 characters)

Station Identifier Station identifier that uniquely identifies the station on a given network

Character string (<= 5 characters)

Geographical Coordinates Latitude and longitude (-)NN.nnn,(-)NNN.nnn Units/Format: Decimal degrees Precision: >=3 decimals Accuracy: 100m

Elevation Vertical elevation of station base (-)NNNN.n Units: Meters Precision: 0.1m Accuracy:

• -200m to 100m: 0.1m

• 101m to 7500m: 2.5m

Parameters Measured List of parameters measured Character string for each parameter or menu selection:

Temperature, Pressure, Relative Humidity (or Dew Point), Wind Speed, Wind Direction, Soil Temperature, Soil Moisture

Network Data Provider Information

Information about the network data provider

Character strings for each field.

Defined length fields for telephone numbers:

Organization name, individual contact information (person or position title, email address, phone number), emergency contact information (same fields)

Site Data Provider Information

Information about the site host Character string. Defined length fields for telephone numbers:

Organization name, individual contact information (person or position title, email address, phone number). Emergency contact information (same fields)

Distribution Restrictions Identify MADIS distribution category Character string:

1: No Distribution (ESRL/GSD Only) 2: Government, Research, Education Only 3: Full Distribution 4: NOAA Only

Table 2. Data Communication Attributes

Attribute Type Description Reporting Format

Transmission Method Means of transmission of data from field to initial central collection point

Character string or menu selection:

VHF

Internet Landline Cellular Satellite Other (specify)

Data Format Type of message used for data transmission

Character string or menu selection:

csv xml binary text other (specify)

Transmission Frequency Frequency of data transmission R/PnMnDTnHnMnS

Transmission Time Time of regular transmission of data hhmmss(Z)

Transmission Time Reference Time

Time zone within which observations are taken

±[hh][mm]

Table 3. Siting/Exposure Attributes

Vegetation Types Type of vegetation at station installation site

Character string or menu selection:

1: Broadleaf – Evergreen (Tropical Forest) 2: Broadleaf – Deciduous Trees 3: Broadleaf and Needleleaf Trees (Mixed Forest) 4: Needleleaf – Evergreen Trees 5: Needleleaf – Deciduous Trees (Larch) 6: Broadleaf Trees with Groundcover (Savanna) 7: Groundcover Only (perennial) 8: Broadleaf Shrubs with Perennial Groundcover 9: Broadleaf Shrubs with Bare Soil 10: Dwarf Trees and Shrubs with Groundcover (Tundra) 11: Bare Soil 12: Cultivations (same parameters as for type 7) 13: Glacial (same parameters as for types 11)

Land Use / Land Cover Classification

Prevailing land use/cover of the surrounding area within which the station is located

Character string or menu selection:

1 Urban or Built-up Land 11: Residential 12: Commercial and Services 13: Industrial 14: Transportation, Communications, and Utilities 15: Industrial and Commercial Complexes 16: Mixed Urban or Built-up Land 17: Other Urban or Built-up Land 2 Agricultural Land 21: Cropland and Pasture 22: Orchards, Groves, Vineyards, Nurseries, and Ornamental Horticultural Areas 23: Confined Feeding Operations 24: Other Agricultural Land 3 Rangeland

31: Herbaceous Rangeland 32: Shrub and Brush Rangeland 33: Mixed Rangeland

4 Forest Land 41: Deciduous Forest Land 42: Evergreen Forest Land 43: Mixed Forest Land

5 Water 51: Streams and Canals 52: Lakes 53: Reservoirs 54: Bays and Estuaries

6 Wetland 61: Forested Wetland 62: Nonforested Wetland

7 Barren Land 71: Dry Salt Flats.

72: Beaches 73: Sandy Areas other than Beaches 74: Bare Exposed Rock

75: Strip Mines Quarries, and Gravel Pits 76: Transitional Areas 77: Mixed Barren Land

8 Tundra 81: Shrub and Brush Tundra 82: Herbaceous Tundra 83: Bare Ground Tundra 84: Wet Tundra 85: Mixed Tundra

9 Perennial Snow or Ice 91: Perennial Snowfields 92: Glaciers

Station Position Description

Description of station’s surroundings, with emphasis on topographic features that may influence weather at station

Character string (limited to 500 characters in web portal)

Roughness Classification Davenport classification of effective terrain roughness

Character string or menu selection:

1: Sea 2: Smooth 3: Open 4: Roughly Open 5: Rough 6: Very Rough 7: Skimming 8: Chaotic

Slope General slope (inclination from horizontal) of area surrounding station

Character string or menu selection:

Slope Class: Percent Slope 1: 0-8 2: 8-30 3: > 30 4: 0-30 5: 0-8 & > 30 6: 8-30 & > 30 7: 0-8, 8-30, > 30 8: Glacial Ice 9: Ocean/Sea

Obstructions

a. Type: Horizontal angle describing width of obstructions (first radial arm measured clockwise from true north, angle measured from first radial arm)

b. Height of obstruction above level of sensor

c. Linear distance in meters to obstructions

a. Character string or menu selection

Building (type), Tower/Mast (type), Tree (type), Fence (type), other (type)

b. NNN: degrees, 10 degree accuracy and precision

c. NNN.n: meters, 1m accuracy and 0.1m precision

d. NN.n: meters, 1m accuracy and 0.1m precision

Sensor Height Height of sensor above/below ground

NNNN.nn Units: meters Precision: 0.1m (anemometer), 0.01m for all other sensors Accuracy: 0.1m (anemometer), 0.01m for all other sensors

Sensor Height Above/Below Structure

Height of sensor above/below structure that it is installed upon

NNNN.n Units: meters Precision: 0.1m (anemometer), 0.01m for all other sensors Accuracy: 0.1m (anemometer), 0.01m for all other sensors

Sensor Structure Type of structure the sensors are installed on

Character String or menu selection:

Mast Tower Tripod Free-Standing Other (specify)

Structure Mount Type of mount the structure uses/is affixed to

Character string:

Building/Roof-Top (penetrating, Non-penetrating), Free-standing (concrete pad, guy wires)

Non-Ambient (Nature) Signal Sources

Types: Air conditioner, heat pump, vent, south-facing reflective wall (north of sensor), generator, diesel engine, man-made surfaces (asphalt, concrete)

NN.n Position: Distance (accuracy/precision:1m) and azimuth (accuracy/precision: 10 degrees) relative to true north from sensor

Topography Map Map image/file of the area surrounding the station

Map scale of no less than USGS 1:25,000 showing contours of elevation differences (30m) with station centered on map. Locations of buildings, trees (with estimated height), surface cover and of installed instruments should be marked

Soil Characteristics Texture, description and quartz content of soil

Character string or menu selection:

Texture / Description / Quartz Content 1: Coarse / Loamy Sand / (0.82) 2: Medium / Silty Clay Loam / (0.10) 3: Fine / Light Clay / (0.25) 4: Coarse-Medium / Sandy Loam / (0.60) 5: Coarse-Fine / Sandy Clay / (0.52) 6: Medium-Fine / Clay Loam / (0.35) 7: Coarse-Med-Fine / Sandy Clay Loam / (0.60) 8: Organic / / (0.40) 9: Glacial Land Ice / Loamy Sand / (0.82)

Table 4. Instrument Attributes

Automatic weather station manufacturer Integrator/Manufacturer Character string or menu selection:

Campbell Scientific, Davis Instruments, Texas Weather Instruments, Aanderaa, All Weather, Coastal Environmental, Climatronics, Vaisala, Other (specify)

Automatic weather station model number Model number of unit Character string

Automatic weather station installation/commissioning date

Date that the system was officially commissioned and brought on line

YYYYMMDD

Sensor Type Type of sensor for which information is being provided

Character string or menu selection:

anemometer, temp/relative humidity, rain gauge, pressure sensor, soil sensor other (specify)

Sensor manufacturer Name of sensor manufacturer Character string or menu selection:

(see list above)

Sensor model number Sensor model number Character string

Sensor installation/commissioning date Date that the sensor was officially commissioned or replaced

YYYYMMDD

Sensor measurement/observing method Type of operation principle describing method of measurement/observation used

Character string

Sensor type of detection system Complete set of measuring instruments and other equipment assembled to carry out specified measurements

Character string

Sensor performance characteristics Operating range of sensors Character string

Sensor unit of measurement SI unit in which the variable is measured

Character string

Sensor measuring range Interval between upper and lower value limits for which variable reported

Character string

Sensor resolution Smallest change in a physical variable which will cause variation in measurement system response

Character string

• Shielding

Name of shielding type Character string or menu selection:

None Gill Stevenson Screen

Other (specify)

• Aspiration

Type of aspiration Character string or menu selection:

passive mechanical other (specify)

• Aspiration flow rate

Aspiration flow rate Flow Rate:

NN ( Units: m/s) Flow Rate Availability:

NNN (%/day)

Sensor exposure Relative to direct liquid and/or freezing moisture

Character string or menu selection:

Yes No

Table 5. Data Acquisition/Logger Attributes

Parameter averaging interval Time interval from which samples are used

NNN

Unit: seconds

Parameter type of averaging Method used to calculate average

Character string

Adjustment procedures for nominal value Adjustment applied to data

Character string

Data output Quantity delivered by instrument or system

Character string

Processing interval Time interval from which samples taken

Character string

Reported resolution Resolution of variable reported

Character string

Data-processing method, procedure, algorithm Method used Character string

Formula used to calculate the element Formula used Character string

Observing/measuring method Type of data being reported

Character string

Input source Measured or derived variable

Character string

Constants and parameter values Constants, parameters used to compute derived parameter

Character string

Atmospheric Pressure datum level Datum level to which atmospheric pressure data of the station refer;

elevation data used for

QFE/QNH

Table 6. Quality Control Attributes

Quality control procedures, algorithms Type of data quality control procedures, definitions and algorithms

Character string

Quality control flag for each parameter Description of quality control flags Character string

Processing and storage procedures Different procedures used in data reduction and data conversion

Table 7. Maintenance Attributes

Scheduled maintenance Anticipated frequency of preventive maintenance

Character string

Actual maintenance Date of maintenance performance YYYYMMDD

Actual maintenance performed Description of maintenance performed Character string

Calibration procedures Type and description of method/procedure used

Character string

Calibration frequency Anticipated frequency of calibrations Character string

Sensor Calibration Type of sensor calibrated Character string

Sensor Calibration Date/Time Date of sensor calibration YYYYMMDDThhmm

Sensor Calibration Results Performance against standard Character string

Data Logger Software Version #:

Install Date:

Character string YYYYMMDD

Hardware Firmware Version #:

Install Date:

Character string YYYYMMDD

Sensor ID Serial # Character string

Sensor Anomaly Codes Code Breakout Character string

Appendix B

References

1. IEEE Recommended Practice for Software Requirements Specifications; Software Engineering Standards Committee of the IEEE Computer Society; IEEE Standard 830- 1998, 25 June 1998.

2. Fair Weather: Effective Partnerships in Weather and Climate Services; The National Academies; 2003.

3. Enhancing Metadata Available from MADIS for the National Mesonet; Michael F. Barth, NOAA/ESRL/GSD, Boulder, CO; and P. A. Miller and D. Helms.

4. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks;

The National Academies; 2009.

5. National Weather Service Instruction 10-1302:

http://www.weather.gov/directives/sym/pd01013002curr.pdf

6. Guide to Meteorological Instruments and Methods of Observation (WMO-No. 8):

http://www.wmo.int/pages/prog/www/IMOP/publications/CIMO-Guide/CIMO_Guide- 7th_Edition-2008.html

7. Guide on the Global Observing System (WMO-No. 488) http://www.wmo.ch/pages/prog/gcos/documents/gruanmanuals/GOS/488_Guide_200 7.pdf

8. Observing Urban Weather and Climate Using 'Standard' Stations; T. R. Oke

9. Initial Guidance to Obtain Representative Meteorological Observations at Urban Sites, Tim R. Oke http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-81/IOM-81- UrbanMetObs.pdf

10. ISO 19115-1 Environmental Information Metadata Standards:

http://www.iso.org/iso/catalogue_detail.htm?csnumber=26020 http://www.wmo.int/pages/prog/www/WDM/reports/ET-IDM-2001.html

11. UNIDATA Metadata Conventions for NetCDF Climate and Forecast (CF) Data:

http://www.unidata.ucar.edu/projects/THREDDS/GALEON/netCDFprofile-short.htm

12. Metadata Encoding Formats: OGC XML/SML – Sensor Model Language:

http://www.opengeospatial.org/standards/sensorm http://www.weather.gov/directives/sym/pd01013002curr.pdf http://www.wmo.int/pages/prog/www/IMOP/publications/CIMO-Guide/CIMO_Guide-7th_Edition-2008.html http://www.wmo.int/pages/prog/www/IMOP/publications/CIMO-Guide/CIMO_Guide-7th_Edition-2008.html http://www.wmo.ch/pages/prog/gcos/documents/gruanmanuals/GOS/488_Guide_2007.pdf http://www.wmo.ch/pages/prog/gcos/documents/gruanmanuals/GOS/488_Guide_2007.pdf http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-81/IOM-81-UrbanMetObs.pdf http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-81/IOM-81-UrbanMetObs.pdf http://www.iso.org/iso/catalogue_detail.htm?csnumber=26020 http://www.wmo.int/pages/prog/www/WDM/reports/ET-IDM-2001.html http://www.unidata.ucar.edu/projects/THREDDS/GALEON/netCDFprofile-short.htm http://www.opengeospatial.org/standards/sensorm

13. Integrated Ocean Observing System (IOOS) Data Management and Communications (DMAC) metadata standards:

http://marinemetadata.org/references/ioosdmacet http://marinemetadata.org/references/ioosdmacet

Appendix C

Data Distribution Categories

For each network that provides data to NWS via MADIS, a data rights/distribution category is assigned, indicating which users may have access to data from the network. The numbers below indicate the categories of MADIS users who have rights to data access for a given network's assigned number, and the ability to do so when logged onto the MADIS user interface. For many mesonets, this category is "4," meaning that only NOAA accesses and uses the data and it is not distributed to parties external to NOAA.

Please note: the MADIS system is a repository for many sources of data that are unrelated to the National Mesonet Program. Some sources are networks owned and operated by NOAA itself, for which the notion of data rights is not applicable (hence Category 1, "N/A").

The following Data Distribution Categories are described below:

1) N/A (discontinued category)

2) Distribution to government, research, and education organizations;

3) Public - full distribution;

4) Distribution to NOAA only.

5) Distribution to NOAA, U.S.DOT (specifically FAA, and FHWA) and NOAA or DOT specified Federally Funded Research and Development Centers only.

6) Distribution only to NOAA and other WMO Members (the “National Meteorological and

Hydrological Services” of other nations) in accordance with WMO Resolution 40.