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2022_bano_deepesd_gmd

Repository supporting the results presented in the manuscript on Downscaling Multi-Model Climate Projection Ensembles with Deep Learning (DeepESD): Contribution to CORDEX EUR-44

https://github.com/santandermetgroup/2022_bano_deepesd_gmd

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Committers with academic emails
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.1%) to scientific vocabulary

Keywords

cordex deep-learning
Last synced: 7 months ago · JSON representation

Repository

Repository supporting the results presented in the manuscript on Downscaling Multi-Model Climate Projection Ensembles with Deep Learning (DeepESD): Contribution to CORDEX EUR-44

Basic Info
  • Host: GitHub
  • Owner: SantanderMetGroup
  • License: other
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 926 KB
Statistics
  • Stars: 1
  • Watchers: 10
  • Forks: 2
  • Open Issues: 0
  • Releases: 1
Topics
cordex deep-learning
Created almost 4 years ago · Last pushed over 3 years ago
Metadata Files
Readme License Zenodo

README.md

DOI

Downscaling Multi-Model Climate Projection Ensembles with Deep Learning (DeepESD): Contribution to CORDEX EUR-44

This repository contains the material and guidelines to reproduce the results presented in the manuscript entitled Downscaling Multi-Model Climate Projection Ensembles with Deep Learning (DeepESD): Contribution to CORDEX EUR-44, submitted to Geoscientific Model Development journal (https://doi.org/10.5194/gmd-2022-57). Authors and corresponding ORCID can be found in the zenodo.json file.

2022BanoDeepESD_GMD.ipynb is a Jupyter notebook based on R containing the code necessary to replicate the results.

environment.yml contains the versions of the python and R libraries employed to reproduce the results of the manuscript. A conda environment with the appropriate versions can be created by typing:

bash mamba env create -n deep-esd --file environment.yml

Owner

  • Name: Santander Meteorology Group (UC-CSIC)
  • Login: SantanderMetGroup
  • Kind: organization
  • Location: Santander

a multidisciplinary approach to weather & climate

GitHub Events

Total
  • Fork event: 1
Last Year
  • Fork event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 47
  • Total Committers: 4
  • Avg Commits per committer: 11.75
  • Development Distribution Score (DDS): 0.617
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
jorgebanomedina j****a@g****m 18
jesusff J****z@u****s 11
zequihg50 e****a@u****s 10
Antonio S. Cofino c****a@g****m 8
Committer Domains (Top 20 + Academic)
unican.es: 2

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 0
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • jorgebanomedina (1)
  • cofinoa (1)
Top Labels
Issue Labels
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Dependencies

environment.yml conda
  • cdo 1.9.10
  • jupyter 1.0.0
  • jupyter_nbextensions_configurator 0.4.1
  • jupyterhub 1.4.2
  • jupyterlab 3.1.4
  • nbgitpuller 0.10.1
  • notebook 6.4.2
  • python 3.9.*
  • r-base >=3.6.1,<4
  • r-climate4r.udg 0.2.4
  • r-climate4r.value 0.0.2
  • r-downscaler 3.3.2
  • r-downscaler.keras 1.0.0
  • r-ggplot2 3.3.3
  • r-gridextra 2.3
  • r-irkernel 1.2
  • r-loader 1.7.1
  • r-loader.2nc 0.1.1
  • r-loader.java 1.1.1
  • r-magrittr 2.0.1
  • r-rcolorbrewer 1.1_2
  • r-tensorflow 2.6.0
  • r-transformer 2.1.0
  • r-value 2.2.2
  • r-visualizer 1.6.0
  • tensorflow 2.6.*