Speedwell Weather

• 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"