Data assimilation for plume models

Autor: David A. Yuen, E. Bélanger, C. A. Hier Majumder, Alain Vincent, S. Derosier
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
DOI: 10.5194/npg-12-257-2005
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