About LongWeather.com


Hello!

LongWeather.com is designed to conveniently display long range weather forecasts for the coming months. We addressed it to both a wide audience and inquisitive specialists. The forecasts are based on our experience using the CFS v2 model from NOAA's NCEP. Some other ideas are still under study and implementation.

Mission

We are committed to spreading state of the art efforts in weather forecasting with everyone who needs it. Great efforts of the scientific community should contribute to the world’s development as much as possible.

Mathematical modeling is the main tool of making predictions, and long-term weather forecasting is the ultimate challenge in the Earth system modeling. At the next step, these efforts generate a huge amount of information that needs to be processed for conclusions and make practical decisions.LongWeather.com reveals some simple instruments and characteristics for help with long range weather forecasts, as well as information regarding scientific achievements and our computational experiments.

  • What is the CFS model?

    Climate Forecast System (CFS) is a kind of the atmosphere model specially created for long-term calculations, which, among other things, includes elements of modeling the ocean and the surface. The model was created and used at NOAA NCEP in version 2.

    General description of the model can be found anywhere, for example here. Scientific overview is published in Journal of Climate, 15 Mar 2014.

  • How it works

    Our main long range weather forecast is created from an ensemble of forecasts over some period. This is because every single weather model run loses sense after a few weeks of forecasting. Only a smoothed average of several simulations shows long-term trends in the Earth atmosphere, caused by global modes of atmosphere itself, ocean thermodynamics and surface state. Such information is useful in the form of deviation between forecast and typical climate conditions. It is shown for a certain location.

    We used the past 10 years’ smoothed averages as a climate dataset because people typically rarely remember past weather beyond this period.

  • Spatial coverage

    Forecast available for Europe, US, Canada, Japan, Australia, Argentina, Brazil, Chile, India, Mexico, New Zealand, Pakistan, South Africa...

  • Features and problems

    At the current project stage, there are limitations in the available computing resources, so the coverage of the Earth's territory is not yet complete.

    In tropical and high-altitude areas, the forecast may contain unrealistic deviations due to topography and random atmospheric convection.

  • Environmental policy

    We always strive to minimize computing power in our software algorithms, on both the server and the client sides.