Statistical Space-Time Characterization of Sub-Grid Air-Sea Exchanges Variability Including Scale Information

• Activity Number: 450 - Uncertainty Quantification for Environmental Applications
• Type: Topic Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Julie Bessac* and Adam Monahan and Nils Weitzel and Kota Endo and Hannah Christensen
• Companies: Argonne National Laboratory and University of Victoria and Universität Heidelberg and University of Victoria and University of Oxford
• Keywords: Space-time ; Sub-grid variability ; Scale-information

Abstract

We present a statistical space-time characterization of the sub-grid variability of air-sea exchanges driven by wind. Indeed many physical phenomena happen at scales below the resolution of the discretization of physics-based models, however, these phenomena interact with the resolved scales. Hence, quantifying the influence of the sub-grid scales on the resolved scales is needed to better represent the entire system. We evaluate the difference between the true turbulent fluxes and those calculated using area-averaged wind speeds. We investigate a space-time characterization of this discrepancy, conditioned on the low-resolution fields, with the view of developing a stochastic wind-flux parameterization. A locally stationary space-time statistical model is used to characterize and model this error process. The space-time structure is proposed in a scale-aware fashion meaning that the space-time correlation ranges depend on the considered resolution. The scale-aware capability enables to derive a stochastic parameterization at any given resolution and to characterize statistically the space-time structure of the error process across scales.