Matthew Chantry

According to our database, Matthew Chantry authored at least 17 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AIFL: A Global Daily Streamflow Forecasting Model Using Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS.

Maria Luisa Taccari, Kenza Tazi, Oisín M. Morrison, Andreas Grafberger, Juan Colonese, Corentin Carton de Wiart, Christel Prudhomme, Cinzia Mazzetti, Matthew Chantry, Florian Pappenberger

CoRR, February, 2026

2025

On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling.

Paula Harder, Christian Lessig, Matthew Chantry, Francis Pelletier, David Rolnick

CoRR, December, 2025

High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid.

Even Marius Nordhagen, Håvard Homleid Haugen, Aram Farhad Shafiq Salihi, Magnus Sikora Ingstad, Thomas Nils Nipen, Ivar Ambjørn Seierstad, Inger-Lise Frogner, Mariana Clare, Simon Lang, Matthew Chantry, Peter Dueben, Jørn Kristiansen

CoRR, November, 2025

RainShift: A Benchmark for Precipitation Downscaling Across Geographies.

Paula Harder, Luca Schmidt, Francis Pelletier, Nicole Ludwig, Matthew Chantry, Christian Lessig, Alex Hernández-García, David Rolnick

CoRR, July, 2025

End-to-end data-driven weather prediction.

Anna Allen, Stratis Markou, Will Tebbutt, James Requeima, Wessel P. Bruinsma, Tom R. Andersson, Michael Herzog, Nicholas D. Lane, Matthew Chantry, J. Scott Hosking, Richard E. Turner

Nat., 2025

2024

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

Mihai Alexe, Eulalie Boucher, Peter Lean, Ewan Pinnington, Patrick Laloyaux, Anthony McNally, Simon Lang, Matthew Chantry, Chris Burrows, Marcin Chrust, Florian Pinault, Ethel Villeneuve, Niels Bormann, Sean Healy

CoRR, 2024

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

Karan Ruparell, Robert J. Marks, Andy Wood, Kieran M. R. Hunt, Hannah L. Cloke, Christel Prudhomme, Florian Pappenberger, Matthew Chantry

CoRR, 2024

Robustness of AI-based weather forecasts in a changing climate.

Thomas Rackow, Nikolay Koldunov, Christian Lessig, Irina Sandu, Mihai Alexe, Matthew Chantry, Mariana Clare, Jesper Sören Dramsch, Florian Pappenberger, Xabier Pedruzo-Bagazgoitia, Steffen Tietsche, Thomas Jung

CoRR, 2024

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

Thomas Nils Nipen, Håvard Homleid Haugen, Magnus Sikora Ingstad, Even Marius Nordhagen, Aram Farhad Shafiq Salihi, Paulina Tedesco, Ivar Ambjørn Seierstad, Jørn Kristiansen, Simon Lang, Mihai Alexe, Jesper Sören Dramsch, Baudouin Raoult, Gert Mertes, Matthew Chantry

CoRR, 2024

Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications.

Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, Ryan Lagerquist

CoRR, 2024

Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators.

Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Boedecker, Carsten F. Dormann, Florian Pappenberger, Gianpaolo Balsamo

CoRR, 2024

Data driven weather forecasts trained and initialised directly from observations.

Anthony McNally, Christian Lessig, Peter Lean, Eulalie Boucher, Mihai Alexe, Ewan Pinnington, Matthew Chantry, Simon Lang, Chris Burrows, Marcin Chrust, Florian Pinault, Ethel Villeneuve, Niels Bormann, Sean Healy

CoRR, 2024

2023

WeatherBench 2: A benchmark for the next generation of data-driven global weather models.

Stephan Rasp, Stephan Hoyer, Alexander Merose, Ian Langmore, Peter W. Battaglia, Tyler Russell, Alvaro Sanchez-Gonzalez, Vivian Yang, Rob Carver, Shreya Agrawal, Matthew Chantry, Zied Ben Bouallegue, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha

CoRR, 2023

2022

A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts.

Lucy Harris, Andrew T. T. McRae, Matthew Chantry, Peter D. Düben, Tim N. Palmer

CoRR, 2022

2021

RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

RainBench: Towards Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

CoRR, 2020

2019

Accelerating High-Resolution Weather Models with Deep-Learning Hardware.

Sam Hatfield, Matthew Chantry, Peter D. Düben, Tim N. Palmer

Proceedings of the Platform for Advanced Scientific Computing Conference, 2019