10 May 2023
 | 10 May 2023
Status: this preprint is currently under review for the journal HESS.

Synoptic weather patterns conducive to compound extreme rainfall-wave events in the NW Mediterranean

Marc Sanuy, Juan Carlos Peña, Sotiris Assimenidis, and José Antonio Jiménez

Abstract. The NW Mediterranean coast is an area at high risk of impacts generated by extreme rainstorms and coastal (wave) storms, which generally result in flash floods, coastal erosion, and flooding along a highly urbanised territory. In many cases, these storms occur simultaneously, and compound events can increase the local impacts (when they occur in the same place) or accumulate the impact throughout the territory (when they occur in different locations). In both cases, multivariate and spatially compound events represent a challenge for risk management because they can overwhelm the capacity of emergency services. In this study, we analysed the prevailing atmospheric conditions during the occurrence of different types of extreme episodes to produce the first classification of synoptic weather patterns (SWPs) conducive to compound events (heavy rainfall and storm waves) in the Spanish NW Mediterranean. For this purpose, we developed a methodological framework by combining an objective synoptic classification method based on principal component analysis and k-means clustering with a Bayesian Network to characterise the nonlinear relationships between SWPs and different variables characterising storms. This method was applied to a dataset of 562 storm events recorded over 30 years, of which 112 were compound. The obtained SWPs were grouped into three main types, of which the Cut-Off was dominant in terms of multivariate event occurrence and was also the situation under which the most severe compound events occurred. The position and depth of the upper-level cold air pools and surface lows affect the relative weight and spatial distribution of the terrestrial (rain) and maritime (waves) components. Finally, the Bayesian Network allowed for a quantitative assessment of the obtained SWP classification by measuring the prediction skill of the target storm variables (i.e. daily precipitation or maximum wave height). Reasonably good skill results were obtained using the SWP as a predictor when accompanied by an additional variable capturing seasonality and event duration. These findings contribute to the overall understanding of compound terrestrial-maritime phenomena in the study area and may assist in the development of effective risk management strategies.

Marc Sanuy et al.

Status: open (until 05 Jul 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Marc Sanuy et al.


Total article views: 240 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
193 44 3 240 15 0 0
  • HTML: 193
  • PDF: 44
  • XML: 3
  • Total: 240
  • Supplement: 15
  • BibTeX: 0
  • EndNote: 0
Views and downloads (calculated since 10 May 2023)
Cumulative views and downloads (calculated since 10 May 2023)

Viewed (geographical distribution)

Total article views: 229 (including HTML, PDF, and XML) Thereof 229 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 08 Jun 2023
Short summary
The work presents the first classification of weather types associated to compound events of extreme rainfall and coastal storms (waves). The upper level low resulted in the main general configuration conducive to extreme compound events in NW Mediterranean conditions. We used objective classification methods coupled with a Bayesian Network to assess the non-linear relationships between the obtained weather types and other variables characterizing the events and their local magnitudes.