Implementation of a reproducible pipeline for forecasting sea ice - snapshot
Economy, business and finance/Economic sector/Computing and information technology/Wireless technology
deep learning probabilistic sea ice forecasting outperforms dynamical models
Motivation impacts exceed local environments, populations and economies need for climate change research accurate seasonal Arctic sea ice forecasts with IceNet:
physical geography and environmental geoscience
This Research Object corresponds to the work done by Vanessa Stoeckl, and presented as a poster at EGU 2024, ESSI 2.9 "Seamless transitioning between HPC and cloud in support of Earth Observation, Earth Modeling and community-driven Geoscience approach PANGEO". - Abstract submitted and accepted at EGU: [https://doi.org/10.5194/egusphere-egu24-8343](https://doi.org/10.5194/egusphere-egu24-8343) - [Rendered Jupyter notebook](https://edsbook.org/notebooks/gallery/ac327c3a-5264-40a2-8c6e-1e8d7c4b37ef/notebook) - [Galaxy workflow showcasing the pipeline for forecasting sea ice](https://usegalaxy.eu/u/vstoeckl/w/icenet)
Implementation of a reproducible pipeline for forecasting sea ice
Stoeckl, Vanessa, Alejandro Coca-Castro, Anne Fouilloux, Björn Grüning, and Jean Iaquinta. "Implementation of a reproducible pipeline for forecasting sea ice." ROHub. Apr 09 ,2024. https://doi.org/10.24424/vpkn-k902.
Galaxy workflow on the Galaxy Europe instance. To execute it, you would need first to get an account on Galaxy Europe (free of charge) and prepare the input dataset.
Galaxy Workflow IceNet sea-ice forecasting
Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update
Poster EGU 2024 (pdf) Implementation of a reproducible pipeline for producing seasonal Arctic sea ice forecasts
Sketch used in RoHub to illustrate the Research Object created for the poster at EGU 2024.
Research Object with the Jupyter Notebook showcasing Sea ice forecasting in the Environmental Data Science book [https://edsbook.org/welcome.html](https://edsbook.org/welcome.html)
Sea ice forecasting using IceNet (Jupyter Notebook) published in the Environmental Data Science book
Economy, business and finance/Economic sector/Energy and resource/Oil and gas - upstream activities
Economy, business and finance/Economic sector/Computing and information technology/Hardware
Implementation of a reproducible pipeline for forecasting sea ice.
National Oceanic and Atmospheric Administration