Influence of trends on subseasonal temperature prediction skill
Détails
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_6CE2FB0A4E6C
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Influence of trends on subseasonal temperature prediction skill
Périodique
Quarterly Journal of the Royal Meteorological Society
ISSN
0035-9009
1477-870X
1477-870X
Statut éditorial
Publié
Date de publication
04/2022
Peer-reviewed
Oui
Volume
148
Numéro
744
Pages
1280-1299
Langue
anglais
Résumé
We developed a numerical thermodynamics laboratory called “Thermolab” to study the effects of the thermodynamic behavior of nonideal solution models on reactive transport processes in open systems. The equations of the state of internally consistent thermodynamic data sets are implemented in MATLAB functions and form the basis for calculating Gibbs energy. A linear algebraic approach is used in Thermolab to compute Gibbs energy of mixing for multicomponent phases to study the impact of the nonideality of solution models on transport processes. The Gibbs energies are benchmarked with experimental data, phase diagrams, and other thermodynamic software. Constrained Gibbs minimization is exemplified with MATLAB codes and iterative refinement of composition of mixtures may be used to increase precision and accuracy. All needed transport variables such as densities, phase compositions, and chemical potentials are obtained from Gibbs energy of the stable phases after the minimization in Thermolab. We demonstrate the use of precomputed local equilibrium data obtained with Thermolab in reactive transport models. In reactive fluid flow the shape and the velocity of the reaction front vary depending on the nonlinearity of the partitioning of a component in fluid and solid. We argue that nonideality of solution models has to be taken into account and further explored in reactive transport models. Thermolab Gibbs energies can be used in Cahn-Hilliard models for nonlinear diffusion and phase growth. This presents a transient process toward equilibrium and avoids computational problems arising during precomputing of equilibrium data.
Mots-clé
probabilistic skill, subseasonal forecasts, trend, verification
Web of science
Open Access
Oui
Financement(s)
Fonds national suisse / PP00P2_170523
Création de la notice
16/05/2022 11:29
Dernière modification de la notice
10/07/2024 7:05