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== In climate science == In [[climate science]], the term indicates a variable that a [[computer model]] predicts by integration of a physical [[equation]], typically [[vorticity]], [[divergence]], [[temperature]], [[Atmospheric pressure#Surface pressure|surface pressure]], and [[water vapour]] concentration in atmospheric models. The term ''prognostic'' is given to some values or variables that are directly predicted by the model,<ref>{{Cite journal |last=Arcomano |first=Troy |last2=Szunyogh |first2=Istvan |last3=Wikner |first3=Alexander |last4=Hunt |first4=Brian R. |last5=Ott |first5=Edward |date=2023-04-28 |title=A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics‐Based Component |url=https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL102649 |journal=Geophysical Research Letters |language=en |volume=50 |issue=8 |doi=10.1029/2022GL102649 |issn=0094-8276|doi-access=free }}</ref> 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 [[relative humidity]], which may be a '''diagnostic variable''' obtained from the model's prognostic variables, temperature and water vapour.
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