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Persistent atmospheric flow situations and temporal clustering of precipitation extremes

English title Persistent atmospheric flow situations and temporal clustering of precipitation extremes
Applicant Romppainen-Martius Olivia
Number 178751
Funding scheme Project funding (Div. I-III)
Research institution Geographisches Institut Universität Bern
Institution of higher education University of Berne - BE
Main discipline Meteorology
Start/End 01.10.2018 - 30.09.2022
Approved amount 706'810.00
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All Disciplines (2)

Climatology. Atmospherical Chemistry, Aeronomy

Keywords (4)

Rossby wave packets; precipitation extremes; temporal clustering of extremes; atmospheric blocking

Lay Summary (German)

Zeitlich gehäuftes Auftreten von Niederschlagsextremen kann zu grossen Ueberschwemmungen führen. So hat beispielsweise eine Serie von Starkniederschlägen auf der Alpensüdseite im September und Oktober 2000 zu Ueberschwemmungen im Tessin geführt. In diesem Projekt untersuchen wir welche Wetterlagen zum gehäuften Auftreten von Starkniederschlägen führen. Wir verwenden dazu statistischen Ansätzen und so-genannte Reanalyse Daten die den Zustand der Atmosphäre in den letzten 30 bis 70 Jahren abbilden.
Lay summary
Die beiden Hauptziele des Projektes sind erstens die statistische modellierung von zeitlich gehäuftem Auftregen von Niederschlagsextremen und zweitens die Prozesse welche zu einer zeitlichen Häufung führen zu verstehen und zu beschreiben. Wir untersuchen dazu Niederschläge der mittleren Breiten der Nord- und Südhemisphäre.
Wir planen folgende Hypothesen betreffend der atmosphärischen Ursachen für die Häufung von Niederschlagsextremen zu testen. 1) Wir werden die Rolle von stationären Hochdruckgebieten, sogenannten Blocks, untersuchen. Mehrere Fallstudien haben gezeigt, dass Niederschlagsextreme gehäuft stromaufwärts und stromabwärts von Blocks auftreten. 2) Wir werden die Rolle von tropischen Wellenstörungen untersuchen. Wellen aus den Tropen können die Zugbahnen von Tiefdruckgebieten in den extratropen beeinflussen und somit zu einer Häufung von Starniederschlägen beitragen.

Direct link to Lay Summary Last update: 19.11.2018

Responsible applicant and co-applicants


Project partner

Associated projects

Number Title Start Funding scheme
159905 Triggering mechanisms of synoptic-scale Rossby waves 01.09.2015 Project funding (Div. I-III)


Floods can be triggered by temporal clustering of precipitation extremes. Recent examples are the floods in England in winter 2013/2014 and the floods in Pakistan in summer 2010. An individual precipitation event might not lead to severe flooding but the rapid succession of precipitation extremes can overwhelm the run-off capacity of rivers. In recent years, statistical methods that were originally developed for medical applications have been used to identify and quantify temporal clustering of atmospheric hazards. These statistical models allow to include co-variates and test the co-variates’ influence on the temporal clustering. The co-variates represent atmospheric processes that are relevant for temporal clustering. So far these methods have been applied to analyze temporal clustering of tropical and extratropical storms and local precipitation extremes. Here we propose to extend the statistical analysis to catchment aggregated precipitation for many catchments in the northern-hemisphere midlatitudes using a novel global precipitation data set that will be released in the end of 2017, the ERA-5 reanalysis by the European Centre for Medium-Range Weather Forecasts. The analysis will also include a verification of this novel precipitation data set against independent observations. A first PhD project and 1-year of postdoc work will be dedicated to the statistical analysis of clustering. The expected outcomes are: i) a verification of ERA-5 precipitation extremes, ii) maps showing in which northern hemisphere catchments statistically significant temporal clustering is found, iii) maps showing the most significant co-variates of clustering.To identify the best set of co-variates a good understanding of the atmospheric processes that lead to temporal clustering is important. From a weather system perspective there are at least two ways how temporal clustering of precipitation can occur in the extratropics. The clustering requires the repeated passage of extratropical cyclones over the same area. First this can happen if a stationary high pressure system, a so-called block, prevents the normal eastward movement of cyclones, resulting in repeated (extreme) precipitation around the block. Second a flow configuration where a series of eastward propagating synoptic-scale wave packets are in phase can result in temporal clustering of extreme precipitation. This flow configuration has been described in case studies discussing temporal clustering. Here we propose to study this flow setting systematically. This entails first developing a methodology to objectively identify such recurrent wave packet episodes in the novel ERA-5 reanalysis data set and to describe the climatological characteristics (where, when). Second the atmospheric processes that foster such episodes will be analysed in a set of case studies and more systematically by correlating the occurrence of the recurrent wave episodes with a number of co-variates such as tropical forcing, Arctic sea ice extent and atmospheric blocking. A second PhD project and 1-year of postdoc work will be dedicated to these analyses. The expected outcomes are: i) an algorithm to objectively identify recurrent wave episodes, ii) climatological analysis of where, when and how often it occurs, iii) a detailed description of the co-variates driving these episode and iv) a statistical quantification of the co-variates. The statistical quantification of temporal clustering is an important information for insurance loss modelling but also emergency response planning (see e.g., the recent clustering of tropical cyclones in the Atlantic). This process understanding of recurrent wave episode will provide important input for the currently hotly debated question of changes in Rossby wave dynamics due to anthropogenic climate change. The methodologies developed in the project will be useful to analyze changes in extreme precipitation clustering and recurring Rossby wave patterns in past and future climates.