Convergence of ensemble forecast distributions in weak and strong forcing convective weather regimes

Tempest, Kirsten I. ; Craig, George C. ; Puh, Matjaž und Keil, Christian (2024): Convergence of ensemble forecast distributions in weak and strong forcing convective weather regimes. In: Quarterly Journal of the Royal Meteorological Society

Abstract

The constraint of computational power and the huge number of degrees of freedom of the atmosphere means a sampling uncertainty exists in probabilistic ensemble forecasts. In our previous study, the uncertainty could be quantified, creating a convergence measure which converges proportional to in the limit of large ensemble size . This power law can then be extrapolated to determine how sampling uncertainty would decrease with larger ensemble sizes and hence find the necessary ensemble size. It is unknown, however, how the sampling uncertainty depends on different weather regimes. This study extends the previous idealised ensemble developed, by including weak and strong forcing convective weather regimes, to look at how sampling uncertainty convergence differs in each. Two -member ensembles were run, with weak and strong forcing respectively. Comparisons with a kilometre-scale weather prediction model ensured realistic weak and strong forcing regimes by comparing the rain, convective available potential energy (CAPE), convective adjustment timescale, and distribution shapes throughout the diurnal cycle. Differences in distribution shape between the regimes led to differences in the convergence measure. Large differences in spread between weak and strong forcing runs throughout the  hr period led to large differences in sampling uncertainty of the mean and standard deviation, which could be quantified according to well-known equations. The timing of these differences was case-dependent. For extreme statistics such as the quantile and for cases where there was precipitation, the moisture variables for the weak forcing case had the largest sampling uncertainty and required the most members for convergence proportional to . This was due to the tails of the weak forcing moisture variables containing the least amount of density. Different ensemble sizes will hence be required depending on whether one is in the weak or strong forcing convective weather regime.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Physik > Meteorologie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 530 Physik
• ISSN: 0035-9009
• Sprache: Englisch