Vb Cyclones Synchronized With the Arctic‐/North Atlantic Oscillation

Abstract

Vb cyclones typically emerge in the Western Mediterranean and propagate to the Northeast into Central Europe. This paper explores the temporal characteristics of Vb cyclone occurrence based on cyclone tracks identified at the atmospheric levels of Z700 and sea level pressure, using JRA‐55 reanalysis data for the period 1959–2015. The risk of Vb occurrence was significantly high in the 1960s and has remained at a lower level since then. Vb cyclones do not occur fully randomly according to a Poisson point process. Eleven well‐separated and distinct clusters as well as 11 hiatus periods are identified, with average occurrence rates of 21.5 and 5.2 yrea −1 , respectively. During the event of Vb, the large‐scale atmospheric circulation is changed into a state favoring the development of successive Vb cyclones. Clustering is very prominent in the case of Genoan Vb cyclones in summer as well as those Vb cyclones developing over the Iberian Peninsula or the North African Coast in winter. Superposition of the polar and the subtropical jet stream over the Western Mediterranean is identified as a main feature at the onset of Vb cyclones. Vb cyclone occurrence appears to be synchronized with the Northern Atlantic Oscillation (NAO; at Z500) and Arctic Oscillation (AO; at Z1000). Clusters have occurred when both NAO and AO were negative. This relation applies to Western Mediterranean cyclones not following a Vb track as well, however to a much weaker extent. In contrast, Vb cyclone frequency was particularly low from 1988 to 1997 during a sustained positive phase of both NAO and AO.

Detecting Flood‐Rich and Flood‐Poor Periods in Annual Peak Discharges Across Europe

“…There has indeed been a clear upward step in the winter NAO index in the 1970s (Hurrell et al, 2003 Hurrell & Deser, 2009), as demonstrated, for example, by the statistical analysis of Gómez‐Martínez et al (2018) (see their Figure 7). The storm track analyses of Hofstätter and Blöschl (2019) suggest that cyclones in Europe are more generally synchronized with the NAO and the Arctic Oscillation. These shifts in precipitation then impact on flood occurrence.…”

Changing summer precipitation variability in the Alpine region: on the role of scale dependent atmospheric drivers

“…3c) highlighted are 20-year periods with particularly high ( P + 1947-1966 and 1999-2018) and low ( P − 1975-1994) interannual variability; the dashed line indicates the zero-line for the standardized indicators MFI and PER and the mean of P for the period 1901-2018 attributed to a positive phase of the Scandinavian Pattern (Comas-Bru and Hernández 2018) related to blocking over Scandinavia. Hofstätter and Blöschl (2019) showed that Scandinavian blocking is often associated with negative North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) conditions. These in turn have the potential to trigger cyclogenesis in the Western Mediterranean and persistent cyclonic circulation which frequently causes heavy rain in the Alpine region with potential for large scale flooding (Hofstätter et al 2018).…”

Assessment of spatial uncertainty of heavy rainfall at catchment scale using a dense gauge network

“…The thick lines show the median, and the shaded areas show the 10th to 90th percentile spread. servations (Contractor et al, 2015;Hofstra et al, 2010;Peleg et al, 2018;Prein and Gobiet, 2017;Tozer et al, 2012). In addition to the high resolution, the regular distribution of WEGN gauges enables generating gridded rainfall fields that are homogeneous in space and, consequently, robustly assess uncertainty in rare and extreme rainfall represented in the data.…”

“…Often, rainfall data are required as areal estimates at the scale of interest, for instance, at grid or catchment scales. Point measurements from in situ S. O and U. Foelsche: Spatial uncertainty of heavy rainfall gauge observations are spatially aggregated or interpolated to estimate the areal distribution of rainfall, and hence the accuracy of areal rainfall data is highly dependent on spatiotemporal variability in rainfall events and density of observation points (Girons Lopez et al, 2015;Hofstra et al, 2010;Villarini et al, 2008;Wood et al, 2000). This limits the understanding of fine-scale rainfall processes, particularly of extreme events (Sillmann et al, 2017).…”

“…The identification of rainfall extremes based on intensity thresholds is common practice; however, the considered spatial scale of rainfall data defines different sets of extreme events (Eggert et al, 2015), potentially affecting threshold-based early warning systems (Marra et al, 2017). Although gridded datasets have been used in a range of applications like assessments of climate change impacts or evaluation of climate models, a common caveat of using the datasets in the study of extreme rainfall is that the quality of gridded rainfall data is highly constrained by the location and density of input weather station data (Hofstra et al, 2010;Prein and Gobiet, 2017). By contrast, the quasi-regular configuration of WEGN on an approximately 1.4 km × 1.4 km grid permits robust examination of the frequency and intensity of rainfall extremes at various horizontal resolutions.…”