Weather data compression

  • Does data compression affect quality?

    Lossy compression can significantly reduce file size, but it can also reduce image quality to the point of distortion, especially if the image is overly compressed.
    However, quality can be maintained when compression is carefully applied.
    One of the challenges with lossy compression is that it's irreversible..

  • How do weather stations collect data?

    Observational data collected by doppler radar, radiosondes, weather satellites, buoys and other instruments are fed into computerized NWS numerical forecast models.
    The models use equations, along with new and past weather data, to provide forecast guidance to our meteorologists..

  • How is weather data processed?

    Data Processing Begins with Quality Control
    Meteorologists at NCEI use computers to perform a basic check of all incoming data.
    The computer checks patterns in each record for issues such as spikes, flatliners, outliers, excessive ranges, and change points.
    Weather data are also checked for consistency across a region..

  • If the typical data distribution skews away from the data that was sampled when the dictionary was created, compression ratios can decrease.
    The maximum compression ratio is 90 percent.
Nov 25, 2021Hundreds of petabytes are produced annually at weather and climate forecast centers worldwide. Compression is essential to reduce storage 

Is cams data compressible?

All CAMS data are 17× compressed relative to 64-bit floats, while preserving 99% of real information.
Combined with four-dimensional compression, factors beyond 60× are achieved.
A data compression Turing test is proposed to optimize compressibility while minimizing information loss for the end use of weather and climate forecast data.

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What is a data compression Turing test?

A data compression Turing test is proposed to optimize compressibility while minimizing information loss for the end use of weather and climate forecast data.
Many supercomputing centers in the world perform operational weather and climate simulations several times per day 1.

Is cams data compressible?

All CAMS data are 17× compressed relative to 64-bit floats, while preserving 99% of real information

Combined with four-dimensional compression, factors beyond 60× are achieved

A data compression Turing test is proposed to optimize compressibility while minimizing information loss for the end use of weather and climate forecast data

Why is compression important in weather forecasting?

Hundreds of petabytes are produced annually at weather and climate forecast centers worldwide

Compression is essential to reduce storage and to facilitate data sharing

Current techniques do not distinguish the real from the false information in data, leaving the level of meaningful precision unassessed

Why is data compression important?

As false information leaves the result of data analyzes unaffected, only the real information is meaningful to analyze and should therefore be preserved in data compression

Data compression for floating-point numbers often poses a trade-off in size, precision and speed 26, 27, 28


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