Cover Image

Prediction of steady states in a marine ecosystem model by a machine learning technique

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mahfuz, Sarker Miraz, Slawig, Thomas
Format:	Preprint
Published:	2025
Subjects:	Atmospheric and Oceanic Physics Machine Learning 86-08, 68T07
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
by: Bonev, Boris, et al.
Published: (2025)

Democracy of AI Numerical Weather Models: An Example of Global Forecasting with FourCastNetv2 Made by a University Research Lab Using GPU
by: Khadir, Iman, et al.
Published: (2025)

Evaluation of Deep Neural Operator Models toward Ocean Forecasting
by: Rajagopal, Ellery, et al.
Published: (2023)

Bangladesh's Amplified Coastal Storm Tide Hazard from Tropical Cyclones and Rising Sea Levels in a Warming Climate
by: Qiu, Jiangchao, et al.
Published: (2023)

Spatiotemporal Predictions of Toxic Urban Plumes Using Deep Learning
by: Wang, Yinan, et al.
Published: (2024)

Multiscale Decomposition Reveals Predictable Interannual Variability and Climate Trends in Antarctic Sea Ice Loss
by: Yatsyshin, Peter, et al.
Published: (2026)

A Weather Foundation Model for the Power Grid
by: Bodnar, Cristian, et al.
Published: (2025)

Accurate typhoon intensity forecasts using a non-iterative spatiotemporal transformer model
by: Qu, Hongyu, et al.
Published: (2025)

Physics-informed neural networks for the shallow-water equations on the sphere
by: Bihlo, Alex, et al.
Published: (2021)

On the archetypal `flavours', indices and teleconnections of ENSO revealed by global sea surface temperatures
by: Monselesan, Didier P., et al.
Published: (2024)

LASSE: Learning Active Sampling for Storm Tide Extremes in Non-Stationary Climate Regimes
by: Jiang, Grace, et al.
Published: (2024)

Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators
by: Morrow, Zachary, et al.
Published: (2026)

Hurricane Impact Index for Assessing Direct and Indirect Hazards in Central America
by: Camacho, Manrique, et al.
Published: (2025)

Hybrid machine learning data assimilation for marine biogeochemistry
by: Higgs, Ieuan, et al.
Published: (2025)

Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)
by: Sonabend-W, Aaron, et al.
Published: (2026)

Artificial neural networks ensemble methodology to predict significant wave height
by: Minuzzi, Felipe Crivellaro, et al.
Published: (2025)

Simulating surface height and terminus position for marine outlet glaciers using a level set method with data assimilation
by: Hossain, M. Alamgir, et al.
Published: (2022)

Statistical Response of ENSO Complexity to Initial Condition and Model Parameter Perturbations
by: Andreou, Marios, et al.
Published: (2024)

SFY -- A lightweight, high-frequency and phase-resolving wave-buoy for coastal waters
by: Hope, Gaute, et al.
Published: (2024)

FuXi-2.0: Advancing machine learning weather forecasting model for practical applications
by: Zhong, Xiaohui, et al.
Published: (2024)

Interpolation of mountain weather forecasts by machine learning
by: Iwase, Kazuma, et al.
Published: (2023)

Temperature induced tipping in a two box ocean circulation model
by: Noory, Jasmine
Published: (2025)

FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design
by: Dunstan, Tom, et al.
Published: (2025)

Estimation of AMOC transition probabilities using a machine learning based rare-event algorithm
by: Jacques-Dumas, Valérian, et al.
Published: (2024)

Arnoldi Singular Vector perturbations for machine learning weather prediction
by: Winkler, Jens, et al.
Published: (2025)

Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data
by: Ehlers, Svenja, et al.
Published: (2023)

Improvements to the post-processing of weather forecasts using machine learning and feature selection
by: Iwase, Kazuma, et al.
Published: (2026)

FuXi Weather: A data-to-forecast machine learning system for global weather
by: Sun, Xiuyu, et al.
Published: (2024)

Stochastic Latent Transformer: Efficient Modelling of Stochastically Forced Zonal Jets
by: Shokar, Ira J. S., et al.
Published: (2023)

Inductive biases in deep learning models for weather prediction
by: Thuemmel, Jannik, 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)

Integrating mobile and fixed monitoring data for high-resolution PM2.5 mapping using machine learning
by: Xu, Rui, et al.
Published: (2025)

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

Physics-Informed Diffusion Model for Generating Synthetic Extreme Rare Weather Events Data
by: Yakout, Marawan, et al.
Published: (2026)

A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport
by: Fernández-Godino, M. Giselle, et al.
Published: (2024)

Efficient Kilometer-Scale Precipitation Downscaling with Conditional Wavelet Diffusion
by: Yi, Chugang, et al.
Published: (2025)

Generative machine learning methods for multivariate ensemble post-processing
by: Chen, Jieyu, et al.
Published: (2022)

A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics
by: Sorensen, Benedikt Barthel, et al.
Published: (2024)

Implicit Adaptive Mesh Refinement for Dispersive Tsunami Propagation
by: Berger, Marsha J., et al.
Published: (2023)

FuXi-S2S: A machine learning model that outperforms conventional global subseasonal forecast models
by: Chen, Lei, et al.
Published: (2023)