PhD project of Jorge de Heuvel, part of project A1 of Waves to Weather.
In this project we investigate the amplification of forecast errors in atmospheric models. More specifically, we are interested in how errors that originate from the convective scale project onto larger atmospheric scales. Our diagnostic framework is based on the tendency equation for potential vorticity (PV) errors developed in Baumgart et al. (2018, 2019).
The prevalent perspective on upscale error growth is spectral analysis. Using spectral analysis, however, important local spatial information is completely lost, which contains valuable information. Therefore, we develop a novel approach to characterize upscale error growth for individual local PV errors. With a feature-based perspective we can make use of the spatial information and disentangle the contributions and physical processes driving the error growth of individual error features. This allows for a local and flow-dependent analysis of upscale error growth. More specifically, we can analyse the influences of convective weather regimes on error growth.
References
- *Baumgart, M. A., M. Riemer, V. Wirth, F. Teubler, and S.T. Lang, 2018: Potential-vorticity dynamics of forecast errors: A quantitative case study, Mon. Wea. Rev., 146, 1405-1425
- *Baumgart, M. A., M. Riemer, G. Craig, P. Ghinassi, T. Selz, and V. Wirth, 2019: Quantitative view on processes governing the error growth from the convective to the planetary scale in simulations with a stochastic convection scheme, Mon. Wea. Rev., 147, 1713-1731