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Cleaned Data
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  • Weather data quality control – "cleaning" – is fundamental to how we provide weather data
  • The availability of reliable "ground truth" is fundamental to the pricing and settling of weather risk contracts
  • This document shows how we approach the cleaning task

Data Cleaning

  • The quality of meteorological observations varies significantly
  • Missing or erroneous observations are commonplace
  • A lot of weather data available in public archives is stored in an inconsistent manner and is of low quality

Fundamentals of a proper data cleaning

  1. Organization
    • logical flow
    • data management
  2. Redundancy
    • data sources
    • testing
    • estimates
    • delivery
  3. Flexibility
    • consider the situation
    • appropriateness of tests
  4. Human interaction
    • meteorology is complicated
    • introduction of non-automated information
  5. Transparency
    • explanation of the process
    • share what has been cleaned
    • no-one likes "black boxes"
Documents and Brochures
Documents UK Germany Germany Polish
About Speedwell Cleaned Data PDF Document
Please contact us for more information.
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