Cover Image

Forecasting precipitation in the Arctic using probabilistic machine learning informed by causal climate drivers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Panja, Madhurima, Das, Dhiman, Chakraborty, Tanujit, Ray, Arnob, Athulya, R., Hens, Chittaranjan, Dana, Syamal K., Murukesh, Nuncio, Ghosh, Dibakar
Format:	Preprint
Published:	2025
Subjects:	Atmospheric and Oceanic Physics Machine Learning Data Analysis, Statistics and Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Forecasting precipitation in the Arctic using probabilistic machine learning informed by causal climate drivers.
by: Panja, Madhurima, et al.
Published: (2025)

Pattern change of precipitation extremes in Bear Island
by: Ray, Arnob, et al.
Published: (2023)

Complexity measure of extreme events
by: Das, Dhiman, et al.
Published: (2024)

Dispersal-induced survival of predators in metacommunities due to transient chaos
by: Ghosh, Samali, et al.
Published: (2026)

Network science disentangles internal climate variability in global spatial dependence structures
by: Ray, Arnob, et al.
Published: (2025)

Regional climate risk assessment from climate models using probabilistic machine learning
by: Wan, Zhong Yi, et al.
Published: (2024)

Resetting mediated navigation of active Brownian searcher in a homogeneous topography
by: Sar, Gourab Kumar, et al.
Published: (2022)

When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges
by: Hadid, Abdenour, et al.
Published: (2024)

Seasonal forecasting using the GenCast probabilistic machine learning model
by: Antonio, Bobby, et al.
Published: (2025)

EnTransformer: A Deep Generative Transformer for Multivariate Probabilistic Forecasting
by: Pathak, Rajdeep, et al.
Published: (2026)

Solar and anthropogenic climate drivers: an updated regression model and refined forecast
by: Stefani, Frank
Published: (2026)

E-STGCN: Extreme Spatiotemporal Graph Convolutional Networks for Air Quality Forecasting
by: Panja, Madhurima, et al.
Published: (2024)

Turning Time Series into Algebraic Equations: Symbolic Machine Learning for Interpretable Modeling of Chaotic Time Series
by: Panja, Madhurima, et al.
Published: (2026)

Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution
by: Jahan, Nourin, et al.
Published: (2026)

On the Extrapolation of Generative Adversarial Networks for downscaling precipitation extremes in warmer climates
by: Rampal, Neelesh, et al.
Published: (2024)

Physics-based vs. data-driven 24-hour probabilistic forecasts of precipitation for northern tropical Africa
by: Walz, Eva-Maria, et al.
Published: (2024)

Changes in mesoscale convective system precipitation structures in response to a warming climate
by: Cui, Wenjun, et al.
Published: (2024)

An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
by: Ward-Leikis, Bryn, et al.
Published: (2025)

Refined climatologies of future precipitation over High Mountain Asia using probabilistic ensemble learning
by: Tazi, Kenza, et al.
Published: (2025)

Radar Maxima: calibrated area-based probabilistic forecasts for heavy precipitation
by: Hess, Reinhold
Published: (2025)

Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate
by: Lin, Jerry, et al.
Published: (2024)

Improving forecasts of precipitation extremes over Northern and Central Italy using machine learning
by: Grazzini, Federico, et al.
Published: (2024)

Blending machine learning and physics-based approaches for weather and climate: a typology
by: Shipway, Benjamin J, et al.
Published: (2026)

YingLong-weather: AI-Based Limited Area Models for Forecasting of Non-precipitation Surface Meteorological Variables
by: Xu, Pengbo, et al.
Published: (2024)

Revealing the drivers of turbulence anisotropy over flat and complex terrain: an interpretable machine learning approach
by: Mosso, Samuele, et al.
Published: (2025)

Advancing global sea ice prediction capabilities using a fully-coupled climate model with integrated machine learning
by: Gregory, William, et al.
Published: (2025)

Multivariate post-processing of probabilistic sub-seasonal weather regime forecasts
by: Mockert, Fabian, et al.
Published: (2024)

Spatiotemporal Forecasting of Traffic Flow using Wavelet-based Temporal Attention
by: Jakhmola, Yash, et al.
Published: (2024)

Coprime networks of the composite numbers: pseudo-randomness and synchronizability
by: Miraj, Md Rahil, et al.
Published: (2024)

Embedding machine-learnt sub-grid variability improves climate model biases
by: Giles, Daniel, et al.
Published: (2024)

Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak
by: Barman, Madhab, et al.
Published: (2025)

Neural ARFIMA model for forecasting BRIC exchange rates with long memory
by: Chakraborty, Tanujit, et al.
Published: (2025)

Spatial verification of global precipitation forecasts
by: Skok, Gregor, et al.
Published: (2024)

EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting
by: Panja, Madhurima, et al.
Published: (2026)

Leveraging deterministic weather forecasts for in-situ probabilistic temperature predictions via deep learning
by: Landry, David, et al.
Published: (2024)

SIFM: A Foundation Model for Multi-granularity Arctic Sea Ice Forecasting
by: Xu, Jingyi, et al.
Published: (2024)

A data-driven framework for dimensionality reduction and causal inference in climate fields
by: Falasca, Fabrizio, et al.
Published: (2023)

Tackling extreme urban heat: a machine learning approach to assess the impacts of climate change and the efficacy of climate adaptation strategies in urban microclimates
by: Buster, Grant, et al.
Published: (2024)

Uncertainty estimation of machine learning spatial precipitation predictions from satellite data
by: Papacharalampous, Georgia, et al.
Published: (2023)

Intelligent Shanghai Typhoon Model (ISTM): A generative probabilistic emulator for typhoon hybrid modeling
by: Niu, Zeyi, et al.
Published: (2025)