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juannat7 committed Nov 12, 2024
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4 changes: 2 additions & 2 deletions _sources/leaderboard.md
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Expand Up @@ -7,11 +7,11 @@ We showcase select variables (`t-850`, `z-500`, `q-700`) on select metrics e.g.,
Learn more about the metrics [here](https://leap-stc.github.io/ChaosBench/metrics.html) and access the complete metrics across variables [here](https://huggingface.co/datasets/LEAP/ChaosBench/tree/main/logs). Unless stated, all results are evaluated for the year 2022.

## Deterministic Models
Deterministic models make a single (control) forecast. This method is particularly sensitive to intiial condition, and is therefore not recommended for long-term chaotic prediction such as in the S2S case.
Deterministic models make a single (control) forecast. This method is particularly sensitive to initial condition, and is therefore not recommended for long-term chaotic prediction, such as in the S2S case.

<iframe src="https://htmlpreview.github.io/?https://raw.githubusercontent.com/leap-stc/ChaosBench/main/website/html/control.html" width="100%" height="600px" frameborder="0"></iframe>

## Ensemble Models
Ensemble models make multiple forecasts (members) at a time to give us a range of likely future outcomes. This (plus a well-dispersed ensemble) is particularly important for S2S forecasting.
Ensemble models make multiple forecasts (members) at a time to give us a collection of possible future outcomes. This (plus a well-dispersed ensemble) is particularly important for skillful S2S forecasting.

<iframe src="https://htmlpreview.github.io/?https://raw.githubusercontent.com/leap-stc/ChaosBench/main/website/html/ensemble.html" width="100%" height="600px" frameborder="0"></iframe>
4 changes: 2 additions & 2 deletions leaderboard.html
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Expand Up @@ -383,12 +383,12 @@ <h1>Leaderboard<a class="headerlink" href="#leaderboard" title="Link to this hea
Learn more about the metrics <a class="reference external" href="https://leap-stc.github.io/ChaosBench/metrics.html">here</a> and access the complete metrics across variables <a class="reference external" href="https://huggingface.co/datasets/LEAP/ChaosBench/tree/main/logs">here</a>. Unless stated, all results are evaluated for the year 2022.</p>
<section id="deterministic-models">
<h2>Deterministic Models<a class="headerlink" href="#deterministic-models" title="Link to this heading">#</a></h2>
<p>Deterministic models make a single (control) forecast. This method is particularly sensitive to intiial condition, and is therefore not recommended for long-term chaotic prediction such as in the S2S case.</p>
<p>Deterministic models make a single (control) forecast. This method is particularly sensitive to initial condition, and is therefore not recommended for long-term chaotic prediction, such as in the S2S case.</p>
<iframe src="https://htmlpreview.github.io/?https://raw.githubusercontent.com/leap-stc/ChaosBench/main/website/html/control.html" width="100%" height="600px" frameborder="0"></iframe>
</section>
<section id="ensemble-models">
<h2>Ensemble Models<a class="headerlink" href="#ensemble-models" title="Link to this heading">#</a></h2>
<p>Ensemble models make multiple forecasts (members) at a time to give us a range of likely future outcomes. This (plus a well-dispersed ensemble) is particularly important for S2S forecasting.</p>
<p>Ensemble models make multiple forecasts (members) at a time to give us a collection of possible future outcomes. This (plus a well-dispersed ensemble) is particularly important for skillful S2S forecasting.</p>
<iframe src="https://htmlpreview.github.io/?https://raw.githubusercontent.com/leap-stc/ChaosBench/main/website/html/ensemble.html" width="100%" height="600px" frameborder="0"></iframe>
</section>
</section>
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