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From the 1 of 26 linked papers with an AI index.

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20242026
most citedAIFL: A Global Daily Streamflow Forecasting Model Using a Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS

1 citations · 2 across the 13 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

physics.ao-ph2024

AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score

Simon Lang, Mihai Alexe, Mariana C. A. Clare +15

Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as…

physics.ao-ph2024

GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Mihai Alexe, Eulalie Boucher, Peter Lean +11

We introduce GraphDOP, a new data-driven, end-to-end forecast system developed at the European Centre for Medium-Range Weather Forecasts (ECMWF) that is trained and initialised exc…

cs.LG2024

Hydra-LSTM: A semi-shared Machine Learning architecture for prediction across Watersheds

Karan Ruparell, Robert J. Marks, Andy Wood +5

Long Short Term Memory networks (LSTMs) are used to build single models that predict river discharge across many catchments. These models offer greater accuracy than models trained…

physics.ao-ph2024

Robustness of AI-based weather forecasts in a changing climate

Thomas Rackow, Nikolay Koldunov, Christian Lessig +9

Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics…

physics.ao-ph2024

Regional data-driven weather modeling with a global stretched-grid

Thomas Nils Nipen, HÃ¥vard Homleid Haugen, Magnus Sikora Ingstad +11

A data-driven model (DDM) suitable for regional weather forecasting applications is presented. The model extends the Artificial Intelligence Forecasting System by introducing a str…

physics.ao-ph2024

AIFS -- ECMWF's data-driven forecasting system

Simon Lang, Mihai Alexe, Matthew Chantry +13

Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artif…