Empowering weather and climate forecast
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.
