Prognostic variable

<h2 id="in-climate-science">In climate science</h2>
<p>In <a href="/facts/Climate_science/bYS7FktY">climate science</a>, the term indicates a variable that a <a href="/facts/Computer_model/Re6o8vzN">computer model</a> predicts by integration of a physical <a href="/facts/Equation/pxFzLAVR">equation</a>, typically <a href="/facts/Vorticity/2oQ6eT4d">vorticity</a>, <a href="/facts/Divergence/zpwwkFoU">divergence</a>, <a href="/facts/Temperature/QyGe4gmj">temperature</a>, <a href="/facts/Atmospheric_pressure/wJLMSaVG">surface pressure</a>, and <a href="/facts/Water_vapour/DX5IUFG0">water vapour</a> concentration in atmospheric models.
</p><p>The term <i>prognostic</i> is given to some values or variables that are directly predicted by the model,<a class="footnote-ref" id="fnref:1" href="#fn:1"><sup>1</sup></a> such as temperature, water vapour, salinity, and depth in atmospheric or ocean models, i.e., variables that can be directly obtained as a model outcome. On the other hand, some other variables need to be calculated separately as derived variables, such as <a href="/facts/Relative_humidity/Nwb28VlT">relative humidity</a>, which may be a diagnostic variable obtained from the model's prognostic variables, temperature and water vapour.
</p>

<h2 id="references">References</h2>

<ol>
<li id="fn:1"><p>Arcomano, Troy; Szunyogh, Istvan; Wikner, Alexander; Hunt, Brian R.; Ott, Edward (2023-04-28). "A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics‐Based Component". Geophysical Research Letters. 50 (8). doi:10.1029/2022GL102649. ISSN 0094-8276. <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL102649" target="_blank">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL102649</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li>
</ol>

Prognostic variable open-in-new

Prognostic variable