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2024
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| Online Access: | https://doi.org/10.5281/zenodo.10681114 |
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| author | Zhao, Sen |
| author_facet | Zhao, Sen |
| contents | <p>This repository include the XRO model source code for the paper "<a href="https://doi.org/10.1038/s41586-024-07534-6" target="_blank" rel="noopener">Explainable El Niño predictability from climate mode interactions</a>" (Zhao et al. 2024, Nature). For the latest version of the XRO code, visit <a href="https://github.com/senclimate/XRO">https://github.com/senclimate/XRO</a>.</p> <h2><strong>Description</strong></h2> <p>The <strong>XRO</strong> is an e<strong>X</strong>tended nonlinear <strong>R</strong>echarge <strong>O</strong>scillator model for El Niño-Southern Oscillation (ENSO) and other modes of variability in the global oceans. It builds on the legacies of the Hasselmann stochastic climate model capturing upper ocean memory in SST variability, and the recharge oscillator model for the oscillatory core dynamics of ENSO. It constitutes a parsimonious representation of the climate system in a reduced variable and parameter space that still captures the essential dynamics of interconnected global climate variability. </p> <p>For the detailed formulation of XRO model, please refer to Methods section of our paper Zhao et al. (2024).</p> <h2><strong>Files</strong></h2> <p>code/</p> <ul> <li>XRO.py XRO model code written in python</li> <li>XRO_Cookbook.ipynb examples demonstrate how to use XRO and reproduce the analyses presented in Zhao et al. (2024). </li> <li>XRO_Cookbook.pdf printed version of XRO_Cookbook.ipynb</li> </ul> <p>data/</p> <ul> <li>indices_oras5.nc Sample data for XRO state vectors (Nino34, WWV, NPMM, SPMM, IOB, IOD, SIOD, TNA, ATL3, SASD time series) from detrended ORAS5 reanalysis from 1979-01 to 2023-10 </li> </ul> <p>LICENSE XRO model code license</p> <p>README.md XRO model readme file</p> <p>XRO_logo.png XRO model logo picture</p> <div> <h2><strong>Source</strong></h2> <div>This XRO model code is hosted at <a href="https://github.com/senclimate/XRO">https://github.com/senclimate/XRO</a>. We have designed XRO to be user-friendly, aiming to be a valuable tool not only for research but also for operational forecasting and as an educational resource in the classroom. We hope that XRO proves to be both a practical and accessible tool that enhances your research and teaching experiences. If you encounter problems in running XRO or have questions, please feel free to contact Sen Zhao (<a href="mailto:zhaos@hawaii.edu">zhaos@hawaii.edu</a>) or create issues <a href="https://github.com/senclimate/XRO/issues" target="_blank" rel="noopener">Here</a>.</div> <div> </div> <div> <h2>References</h2> <p>Kindly requested to cite our paper and the code if use the XRO model in your published works.</p> <p>Zhao, S., Jin, F.-F., Stuecker, M. F., Thompson, P. R., Kug, J.-S., McPhaden, M. J., Cane, M.A., Wittenberg, A.T., Cai, W. (2024). Explainable El Niño predictability from climate mode interactions. <em>Nature</em>. <strong>630</strong>(8018), 891-898 <a href="https://doi.org/10.1038/s41586-024-07534-6">https://doi.org/10.1038/s41586-024-07534-6</a></p> <p>Zhao, S. (2024). Extended nonlinear Recharge Oscillator (XRO) model for "Explainable El Niño predictability from climate mode interactions". Zenodo. <a href="https://doi.org/10.5281/zenodo.10681114" rel="nofollow">https://doi.org/10.5281/zenodo.10681114</a></p> </div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_10681114 |
| institution | Zenodo |
| language | eng |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Extended nonlinear Recharge Oscillator (XRO) model for "Explainable El Niño predictability from climate mode interactions" Zhao, Sen El Niño-Southern Oscillation Climate Modes Interactions Seasonal Forecast Simple Climate Model <p>This repository include the XRO model source code for the paper "<a href="https://doi.org/10.1038/s41586-024-07534-6" target="_blank" rel="noopener">Explainable El Niño predictability from climate mode interactions</a>" (Zhao et al. 2024, Nature). For the latest version of the XRO code, visit <a href="https://github.com/senclimate/XRO">https://github.com/senclimate/XRO</a>.</p> <h2><strong>Description</strong></h2> <p>The <strong>XRO</strong> is an e<strong>X</strong>tended nonlinear <strong>R</strong>echarge <strong>O</strong>scillator model for El Niño-Southern Oscillation (ENSO) and other modes of variability in the global oceans. It builds on the legacies of the Hasselmann stochastic climate model capturing upper ocean memory in SST variability, and the recharge oscillator model for the oscillatory core dynamics of ENSO. It constitutes a parsimonious representation of the climate system in a reduced variable and parameter space that still captures the essential dynamics of interconnected global climate variability. </p> <p>For the detailed formulation of XRO model, please refer to Methods section of our paper Zhao et al. (2024).</p> <h2><strong>Files</strong></h2> <p>code/</p> <ul> <li>XRO.py XRO model code written in python</li> <li>XRO_Cookbook.ipynb examples demonstrate how to use XRO and reproduce the analyses presented in Zhao et al. (2024). </li> <li>XRO_Cookbook.pdf printed version of XRO_Cookbook.ipynb</li> </ul> <p>data/</p> <ul> <li>indices_oras5.nc Sample data for XRO state vectors (Nino34, WWV, NPMM, SPMM, IOB, IOD, SIOD, TNA, ATL3, SASD time series) from detrended ORAS5 reanalysis from 1979-01 to 2023-10 </li> </ul> <p>LICENSE XRO model code license</p> <p>README.md XRO model readme file</p> <p>XRO_logo.png XRO model logo picture</p> <div> <h2><strong>Source</strong></h2> <div>This XRO model code is hosted at <a href="https://github.com/senclimate/XRO">https://github.com/senclimate/XRO</a>. We have designed XRO to be user-friendly, aiming to be a valuable tool not only for research but also for operational forecasting and as an educational resource in the classroom. We hope that XRO proves to be both a practical and accessible tool that enhances your research and teaching experiences. If you encounter problems in running XRO or have questions, please feel free to contact Sen Zhao (<a href="mailto:zhaos@hawaii.edu">zhaos@hawaii.edu</a>) or create issues <a href="https://github.com/senclimate/XRO/issues" target="_blank" rel="noopener">Here</a>.</div> <div> </div> <div> <h2>References</h2> <p>Kindly requested to cite our paper and the code if use the XRO model in your published works.</p> <p>Zhao, S., Jin, F.-F., Stuecker, M. F., Thompson, P. R., Kug, J.-S., McPhaden, M. J., Cane, M.A., Wittenberg, A.T., Cai, W. (2024). Explainable El Niño predictability from climate mode interactions. <em>Nature</em>. <strong>630</strong>(8018), 891-898 <a href="https://doi.org/10.1038/s41586-024-07534-6">https://doi.org/10.1038/s41586-024-07534-6</a></p> <p>Zhao, S. (2024). Extended nonlinear Recharge Oscillator (XRO) model for "Explainable El Niño predictability from climate mode interactions". Zenodo. <a href="https://doi.org/10.5281/zenodo.10681114" rel="nofollow">https://doi.org/10.5281/zenodo.10681114</a></p> </div> </div> |
| title | Extended nonlinear Recharge Oscillator (XRO) model for "Explainable El Niño predictability from climate mode interactions" |
| topic | El Niño-Southern Oscillation Climate Modes Interactions Seasonal Forecast Simple Climate Model |
| url | https://doi.org/10.5281/zenodo.10681114 |