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3 days ago · ML uses a lot of data to produce results, and ECMWF is all about data: we use a lot of data – tens of millions of weather observations per day – and we create a lot of data by producing weather analyses and forecasts at high resolution. Traditionally, we use physics-based methods for our computations in the Integrated Forecasting System (IFS).
3 days ago · Weathernerds ECMWF Data. Weathernerds provides weather data in a flexible, practical interface. This site is designed to give creativity and control to the forecaster so that imagery is weather feature-based rather than relying on predefined geographic maps.
Aug 30, 2024 · ECMWF is now running an experimental suite to evaluate the forecasting skill of a series of publicly available data-driven forecast models initialised by ECMWF 4D-Var analysis. ECMWF provides the output for testing and comparison purposes.
Aug 29, 2024 · ECMWF is now running an experimental suite to evaluate the forecasting skill of a series of publicly available data-driven forecast models initialised by ECMWF 4D-Var analysis. ECMWF provides the output for testing and comparison purposes.
Sep 2, 2024 · ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced...
Aug 28, 2024 · What is the OpenIFS Data Hub? One of the most pressing needs OpenIFS users face is to create initial experiment data (initial and boundary conditions) to start a model experiment. Before the Data Hub existed such initial experiment data were requested by contacting OpenIFS support via email.
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6 days ago · The ENSL employs predictors from the high-resolution ECMWF model forecast (ECMWF-HRES) data and topography data, and targets from automatic weather station observations. Four categories of predictors (synoptic-pattern related fields, surface element fields, terrain, and temporal features) are fed into ENSL.
