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Paraskevi Giannakaki and Olivia Martius

Abstract

An accurate representation of synoptic-scale Rossby waves in numerical weather forecast models is very important as these waves are closely linked to weather formation at the surface. Enhanced potential vorticity (PV) gradients at the tropopause levels act as waveguides for synoptic-scale Rossby waves, so spatial errors in the waveguides imply errors in the amplification and propagation of Rossby waves. This paper focuses on evaluating the forecast representation of these waveguides and presents an object-based forecast verification tool. In both forecast and the verification data, Rossby waveguide objects are defined based on enhanced PV gradient fields on isentropic surfaces. The tool automatically pairs the complex objects, compares their properties, and assesses the number of objects without a matching partner in either the forecast or the reanalysis. In the last step, error measures are calculated for the area and the location of the objects. As proof-of-concept application of the method for the year 2008, five lead times of the Integrated Forecast System (IFS) from the ECMWF are compared with the ECMWF reanalysis dataset. The majority of the waveguide objects are found to be in the correct position, and there are no systematic positional errors; however, the forecast objects and hence the areas of enhanced PV gradients are smaller.

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Yannick Barton, Paraskevi Giannakaki, Harald von Waldow, Clément Chevalier, Stephan Pfahl, and Olivia Martius

Abstract

Temporal clustering of extreme precipitation events on subseasonal time scales is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering.

An observation-based gridded precipitation dataset of Swiss daily rainfall sums and ECMWF reanalysis datasets are used. Also used is a modified version of Ripley’s K function, which determines the average number of extreme events in a time period, to characterize temporal clustering on subseasonal time scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on subseasonal time scales during the fall season.

Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upper-level breaking Rossby wave over western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.

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