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European Centre for Medium-Range Weather Forecasts (ECMWF)

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RESEARCH · 1 SOURCE · The Verge AI

Microsoft publishes open-source 'Probabilistic Bias Correction' to improve 2–6 week forecasts

Microsoft researchers published a Nature paper and released open-source software called Probabilistic Bias Correction (PBC) that uses machine learning to correct systematic biases in existing weather models; the team reports PBC improved ECMWF model performance for most precipitation and temperature targets and can run on CPUs. The paper lists coauthors from MIT, ECMWF and others and the method is being tested with partners such as Rhiza Research and the Kenya Meteorological Service.

8.0

RESEARCH · 1 SOURCE · Google Research

Google Research paper shows ML improves global flood forecasts for ungauged watersheds

Google Research published a Nature paper, “Global prediction of extreme floods in ungauged watersheds,” reporting that machine learning models (including LSTM-based approaches) can materially improve global-scale flood forecasting where local streamflow data are scarce—extending forecast reliability on average from zero to five days and enabling Flood Hub to deliver up to seven-day river forecasts across reaches in over 80 countries; model evaluation was done in collaboration with ECMWF and the team has open-sourced related hydrology datasets.

8.0