Juliette Blanchet

Spatial analysis of trend in extreme daily rainfall in southern France

This paper makes a regional evaluation of trend in yearly maxima of daily rainfall in southern France, both at point and spatial scales on a regular grid of 8xa0×xa08xa0km2. In order to filter out the high variability of rainfall maxima, the current analysis is based on a non-stationary GEV modeling in which the location parameter is allowed to vary with time. Three non-stationary models are considered for each series of maxima by constraining the location parameter to vary either linearly, linearly after a given date or linearly up to a final date. Statistical criteria are used to compare these models and select the best starting or final point of putative trends. The analysis shows that, at regional scale, the best distribution of maxima involves a linear trend starting in year 1985 and that this trend is significant in half the region, including most of the mountain ranges and part of the Rhône valley. Increases in yearly maxima are considerable since they reach up more than 60xa0mm/day in 20xa0years, which is more than 40xa0% of the average maximum in this area.

Co‐Occurrence of Extreme Daily Rainfall in the French Mediterranean Region

We propose in this article a statistical framework to study local disparities in the co-occurrence of extreme rainfall in the French Mediterranean region. We employ a region-of-influence approach by studying the likelihood of the 3% largest daily rainfall to occur simultaneously at less than 50 km distance, when moving across the region. Our model uses an anisotropic max-stable process allowing us to properly represent the co-occurrence of daily extremes and including the possibility of a preferred direction of co-occurrence. We use this framework on a dense network composed of almost 900 daily stations spread over a 100,000 km2 region of southern France under a Mediterranean influence, with data back to 1948. This density allows us to study the spatial patterns in the co-occurrence of extreme rainfall at fine scale and by so to characterize the main precipitation systems leading to extremes in the region. We show in particular that concomitant extremes are the most likely along the crest line of the Massif Central, which is also the area where the magnitude of extremes is among the largest. This may be of concern for flood risk management.

Trend in the Co‐Occurrence of Extreme Daily Rainfall in West Africa Since 1950

We propose in this paper a statistical framework to study the evolution of the co-occurrence of extreme daily rainfall in West Africa since 1950. We consider two regions subject to contrasted rainfall regimes: Senegal and the central Sahel. We study the likelihood of the 3% largest daily rainfall (considering all days) in each region to occur simultaneously and, in a 20 year moving window approach, how this likelihood has evolved with time. Our method uses an anisotropic max-stable process allowing us to properly represent the co-occurrence of daily extremes and including the possibility of a preferred direction of co-occurrence. In Senegal, a change is found in the 1980s, with preferred co-occurrence along the E-50-N direction (i.e., along azimuth 50∘) before the 1980s and weaker isotropic co-occurrence afterward. In central Sahel, a change is also found in the 1980s but surprisingly with contrasting results. Anisotropy along the E-W direction is found over the whole period, with greater extension after the 1980s. The paper discusses how the co-occurrence of extremes can provide a qualitative indicator on change in size and propagation of the strongest storms. This calls for further research to identify the atmospheric processes responsible for such contrasted changes in storm properties. Plain Language Summary We propose in this paper a statistical framework to study the evolution of the co-occurrence of extreme daily rainfall in West Africa since 1950. We consider two regions subject to contrasted rainfall regimes: Senegal and the central Sahel. In Senegal, a change is found in the 1980s, with preferred co-occurrence along the E-50-N direction (i.e., along azimuth 50∘) before the 1980s and weaker isotropic co-occurrence afterward. In the central Sahel, a change is also found in the 1980s but surprisingly with contrasting results. Anisotropy along the E-W direction is found over the whole period, with greater extension after the 1980s. The paper discusses how the co-occurrence of extremes can provide a qualitative indicator on change in size and propagation of the strongest storms. This calls for further research to identify the atmospheric processes responsible for such contrasted changes in storm properties.

Toward Probabilistic Prediction of Flash Flood Human Impacts: Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance-specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle-related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time- and space-dependent human vulnerability and risk assessment for short-fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact-based predictive models for flash flood casualties using machine-learning approaches in the future.

Reconstruction of Lamb weather type series back to the eighteenth century

The Lamb weather type series is a subjective catalogue of daily atmospheric patterns and flow directions over the British Isles, covering the period 1861–1996. Based on synoptic maps, meteorologists have empirically classified surface pressure patterns over this area, which is a key area for the progression of Atlantic storm tracks towards Europe. We apply this classification to a set of daily pressure series from a few stations from western Europe, in order to reconstruct and to extend this daily weather type series back to 1781. We describe a statistical framework which provides, for each day, the weather types consistent enough with the observed pressure pattern, and their respective probability. Overall, this technique can correctly reconstruct almost 75% of the Lamb daily types, when simplified to the seven main weather types. The weather type series are described and compared to the original series for the winter season only. Since the low frequency variability of synoptic conditions is directly related to the North Atlantic Oscillation (NAO), we derive from the weather type series an NAO index for winter. An interesting feature is a larger multidecadal variability during the nineteenth century than during the twentieth century.