Extreme weather events caused over
casualties in the past 20 years.
times the people killed in German traffic in the same period.
times the number of casualties in the Bosnian war.
To predict just the weather in Europe, around
observations must be processed. Every day!
times the number of observations a person could read in a day (assuming 10 per minute).
Degrees of freedom are a measure for the complexity of statistics. Our high-resolution prediction model has almost
DoF in a single simulation.
times the degrees of freedom a person could update manually in one day (assuming 5 per minute).
The company Graphcore has used the MAELSTROM dataset on the emulation of gravity wave drag parametrisation for performance tests with their Intelligence Processing Units (IPUs). See Graphcore's blog here.
What data scientist do can be pretty abstract to non-datanerds. We felt we would like to give everybody some feeling for how important it is to understand and predict weather and climate better, but also how difficult it is. Finally, however, what awesome possibilities a combination of high performance computing and machine learning put in our hands! Have a look and tell us what you think!
Hello machine learning and weather & climate scientists! Learn about the first versions of our machine learning tools and solutions, including architectures and loss functions. Get the results of a survey of customized machine learning solutions here.
We're excited to have reached a big milestone end of August: a series of datasets went public.
Dataset for energy production forecast
Dataset for 2m temperature downscaling
Dataset for ensemble predictions
Datasets for 2m temp. and precipitation short-range forecasts
Dataset to emulate radiation
Feedback and comments will be much appreciated.