Flood impact on the Spanish Mediterranean coast since 1960 based on the prevailing synoptic patterns.

Abstract

In a changing climate and in social context, tools and databases with high spatiotemporal resolution are needed for increasing the knowledge on the relationship between meteorological events and flood impacts; hence, analysis of high-resolution spatiotemporal databases with detailed information on the frequency, intensity, and impact of floods is necessary. However, the methodological nature of flood databases hinders relating specific flood events to the weather events that cause them; hence, methodologies for classifying flood cases according to the synoptic patterns that generate them are also necessary. Knowing which synoptic patterns are likely to generate risk situations allows for a probabilistic approach with high spatial resolution regarding the timing of occurrence, affected area, and expected damage from floods. To achieve these objectives, we use the SMC-Flood Database, a high-resolution spatiotemporal flood database covering the 1960-2015 period for all municipalities along the Spanish Mediterranean coast. To relate floods with the synoptic conditions that generated them, we used a multivariate analysis method on the corrected daily anomalies of the surface pressure fields, 850\u202fhPa temperature, and 500\u202fhPa geopotential height, all of which were obtained from the 20th Century Reanalysis Project V2. Results show that 12 atmospheric synoptic patterns can statistically explain the 3608 flood cases that occurred in the study area between 1960 and 2015. These flood cases were classified into 847 atmospherically induced flood events. These results reduce the uncertainty during decision making because of the classification of potential risk situations. The Mediterranean Basin is a region where floods have serious socioeconomic impacts; hence, this work helps improving prevention measures and providing information for policymakers, mainly regarding land use planning and early warning systems.