Date:
Wed, 10/01/202412:00-13:30
Location:
Danciger B Building, Seminar room
Lecturer: Dr. Ofer Shamir
Abstract:
A key feature of the tropical wavenumber-frequency spectrum is its meridional parity distributions, i.e., the power distribution between its symmetric and antisymmetric components. Satellite observations and reanalysis data provide ample evidence of a salient symmetric bias in the tropical spectrum, evident across different dynamical variables and pressure levels. This talk will focus on the effects of triad interactions, which take place during inverse (upscale) turbulent energy cascade in the Tropics. We show that triad interactions provide a mechanism for internally generated symmetric variability, where any small-scale parity bias, symmetric or antisymmetric, leads to symmetric biases at large spatial scales. Yet, quantifying their contribution to the observed parity distribution, compared to natural variability, necessitates the identification of a background spectrum, which is an open challenge. This work presents a new approach for estimating the background spectrum. We show that at sufficiently small spatial scales (< 2000 km) and high frequencies (> 90 cpd), the Earth’s infrared spectrum can be accurately captured by a stochastically forced energy balance climate model. The model has the desired property that it is statistically homogeneous and isotropic, and hence the explained variability is purely random and cannot be attributed to waves.
Abstract:
A key feature of the tropical wavenumber-frequency spectrum is its meridional parity distributions, i.e., the power distribution between its symmetric and antisymmetric components. Satellite observations and reanalysis data provide ample evidence of a salient symmetric bias in the tropical spectrum, evident across different dynamical variables and pressure levels. This talk will focus on the effects of triad interactions, which take place during inverse (upscale) turbulent energy cascade in the Tropics. We show that triad interactions provide a mechanism for internally generated symmetric variability, where any small-scale parity bias, symmetric or antisymmetric, leads to symmetric biases at large spatial scales. Yet, quantifying their contribution to the observed parity distribution, compared to natural variability, necessitates the identification of a background spectrum, which is an open challenge. This work presents a new approach for estimating the background spectrum. We show that at sufficiently small spatial scales (< 2000 km) and high frequencies (> 90 cpd), the Earth’s infrared spectrum can be accurately captured by a stochastically forced energy balance climate model. The model has the desired property that it is statistically homogeneous and isotropic, and hence the explained variability is purely random and cannot be attributed to waves.