Flow dependence of forecast uncertainty in a large convection‐permitting ensemble

Puh, Matjaž ; Tempest, Kirsten I. ; Keil, Christian und Craig, George C. (2024): Flow dependence of forecast uncertainty in a large convection‐permitting ensemble. In: Quarterly Journal of the Royal Meteorological Society, Bd. 150, Nr. 765: S. 5113-5126

Abstract

The flow dependence of forecast distributions is studied using a 120-memberICON-D2 ensemble for two representative case studies of weak and strong syn-optic forcing of convection. The bootstrapping technique is used to investigatethe convergence of sampling error for a range of surface and midtropospherevariables. Convergence is generally observed for the mean and the standard devi-ation, but not for the 95th percentile, especially in strong forcing. Additionally,maps of uncertainty are introduced, which allow for a more detailed analysis ofthe spatial pattern of uncertainty and facilitate the interpretation of the sourcesand evolution of forecast uncertainty in different synoptic forcing conditions. Itis found that convection significantly increases uncertainty in model variablesand shapes the spatial uncertainty pattern, with weak forcing leading to patchyuncertainty and strong forcing resulting in a more coherent pattern due to largeconvective systems. Overall, the main result of this work is the strong connectionbetween uncertainty of forecast variables and convection, with synoptic forcingbeing crucial in determining the spatial distribution and uncertainty evolutionwithin 24 h.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Physik > Meteorologie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 530 Physik
• ISSN: 0035-9009
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 257899354