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Managing the collection and dissemination of non-homogenous data from numerous, diverse, geographically scattered sources. Jim Block Chief Meteorologist Meteorlogix. Basic Principals. More data is a good thing. Forecasters need specific observations for good warnings and forecasts

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Jim Block Chief Meteorologist Meteorlogix

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Jim block chief meteorologist meteorlogix
Managing the collection and dissemination of non-homogenous data from numerous, diverse, geographically scattered sources

Jim Block

Chief Meteorologist

Meteorlogix


Basic principals
Basic Principals data from numerous, diverse, geographically scattered sources

  • More data is a good thing.

    • Forecasters need specific observations for good warnings and forecasts

    • No meteorologist ever has too much data

    • Local! Local! Local!

    • Atmospheric information has a Forensic value, as well as Meteorological and Climatological value


Basic principals1
Basic Principals data from numerous, diverse, geographically scattered sources

  • The commercial value of observations decreases over time.

    • The closer to “real-time” observations are, the more potential uses it has

  • The commercial value never goes to zero.

    • Weather data does have a Forensic and Risk Management value even years later


Basic principals2
Basic Principals data from numerous, diverse, geographically scattered sources

  • The value of atmospheric information is maximized when it is available to commercial entities.

    • There is no need for special systems or programs to distribute this additional atmospheric information

    • Standardization increases the value

    • Non-Proprietary


Basic principals3
Basic Principals data from numerous, diverse, geographically scattered sources

  • Privately funded atmospheric information systems need to protect their investment.

    • Intrinsic value of the data to the owner

    • Competitive issues need to be respected


Data management
Data Management data from numerous, diverse, geographically scattered sources

  • Non-homogeneity of data

  • Metadata

  • Timeliness

  • Format

  • Reliability


Data management1
Data Management data from numerous, diverse, geographically scattered sources

  • Non-homogeneity of data from diverse sources

    • Siteing

      • Often chosen for convenience, not representativeness

      • May present systematic errors

      • Needs to be understood and captured

    • Quality of Instruments

    • Calibration

      • How often?

      • Who does it?


Data management2
Data Management data from numerous, diverse, geographically scattered sources

  • Metadata is crucial for the effective use of non-homogenous data

    • Who collects and manages the Metadata?

    • Who double checks the accuracy?

    • How is the Metadata maintained?

    • Who will be responsible?


Data management3
Data Management data from numerous, diverse, geographically scattered sources

  • Timeliness

    • Frequency. At what observational frequency is value maximized?

      • Many instruments are capable of reporting nearly continuously

    • Availability. How frequently should observations be available?

      • ASOS has the ability to report observations every minute

      • There is a trade-off between frequency and communications bandwidth (cost)

    • Latency. How soon should observations be available?

      • Whatever the frequency, reports need to be available within 10-20% of the time between observations (e.g. Hourly METAR observations are taken within 6-12 minutes of the top of each hour, and available via the FOS within 6-12 minutes of observation)


Data management4
Data Management data from numerous, diverse, geographically scattered sources

  • Format

    • Standardization of formats is desirable

    • Inclusion of all available parameters

      • Parameters crucial to one user may be unimportant to others

    • Has to be able to deal with observations at different intervals, and different ages


Data management5
Data Management data from numerous, diverse, geographically scattered sources

  • Reliability

    • Sporadic or inconsistent reports decrease value dramatically

    • Quality Control. Has the data been checked for:

      • Reasonableness?

      • Temporal consistency?

      • Spatial consistency?

    • Will users know that QC is (or is not) being done?


Conclusion
Conclusion data from numerous, diverse, geographically scattered sources

  • Clear definition of the roles and responsibilities in the management of non-homogenous data is crucial.

  • A few standards and formats are better than many.

  • The closer to real-time data is available, the higher the value of that data.

  • The higher the value of data, the more ALL aspects of the meteorological community, government, research, and commercial, benefit.


Contact information
Contact Information data from numerous, diverse, geographically scattered sources

Jim Block

Meteorlogix

(952) 890-0609

Jim.Block@meteorlogix.com


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