Data assimilation for plume models
| Autor: | David A. Yuen, E. Bélanger, C. A. Hier Majumder, Alain Vincent, S. Derosier |
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| Přispěvatelé: | Computational Physics Group, Earth Science Division, Minnesota Supercomputing Institute, University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, Département de Physique [Montréal], Université de Montréal (UdeM), Department of Geology and Geophysics [Minneapolis], EGU, Publication |
| Rok vydání: | 2005 |
| Předmět: |
010504 meteorology & atmospheric sciences
Meteorology Prandtl number Direct numerical simulation [SDU.STU]Sciences of the Universe [physics]/Earth Sciences [SDU.ASTR] Sciences of the Universe [physics]/Astrophysics [astro-ph] 010502 geochemistry & geophysics 01 natural sciences Physics::Geophysics [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO] Physics::Fluid Dynamics symbols.namesake Quality (physics) Data assimilation Rayleigh scattering Predictability 0105 earth and related environmental sciences Mathematics [SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph] Mechanics Rayleigh number Plume [PHYS.ASTR.CO] Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO] 13. Climate action [SDU.STU] Sciences of the Universe [physics]/Earth Sciences symbols |
| Zdroj: | Nonlinear Processes in Geophysics Nonlinear Processes in Geophysics, European Geosciences Union (EGU), 2005, 12 (2), pp.257-267 |
| ISSN: | 1607-7946 1023-5809 |
| Popis: | We use a four-dimensional variational data assimilation (4D-VAR) algorithm to observe the growth of 2-D plumes from a point heat source. In order to test the predictability of the 4D-VAR technique for 2-D plumes, we perturb the initial conditions and compare the resulting predictions to the predictions given by a direct numerical simulation (DNS) without any 4D-VAR correction. We have studied plumes in fluids with Rayleigh numbers between 106 and 107 and Prandtl numbers between 0.7 and 70, and we find the quality of the prediction to have a definite dependence on both the Rayleigh and Prandtl numbers. As the Rayleigh number is increased, so is the quality of the prediction, due to an increase of the inertial effects in the adjoint equations for momentum and energy. The horizon predictability time, or how far into the future the 4D-VAR method can predict, decreases as Rayleigh number increases. The quality of the prediction is decreased as Prandtl number increases, however. Quality also decreases with increased prediction time. |
| Databáze: | OpenAIRE |
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