Mapping Flood-Related Mortality in the Mediterranean Basin. Results from the MEFF v2.0 DB

Recent events in Western Attica in Greece (24 deaths in November 2017), in the Balearic Islands (13 deaths in October 2018), and in southern France (15 deaths in October 2018) show that flood-related mortality remains a major concern in Mediterranean countries facing flash floods. Over the past several years, many initiatives have arisen to create databases on flood-related mortality. An international initiative started in 2011 pooling regional and national databases on flood mortality from region and/or countries bordering the Mediterranean Sea. The MEditerranean Flood Fatality Database (MEFF DB) brings together, in 2018, six Mediterranean regions/countries: Catalonia (Spain), Balearic Islands (Spain), Southern France, Calabria (Italy), Greece, and Turkey, and covers the period 1980-2018. MEFF DB is on progress and, every year, new data are included, but for this study, we kept only the preliminary data that were geolocated and validated on 31st of December 2018. This research introduces a new step in the analysis of flood-related mortality and follows the statistical description of the MEFF DB already published. The goals of this paper are to draw the spatial distribution of flood mortality through a geographical information system (GIS) at different spatial scales: country, NUTS 3 (Nomenclature of Territorial Units for Statistics. Level 3) regions, catchment areas, and grid. A fatality rate (F: number of deaths/year/million of inhabitants) is created to help this analysis. Then, we try to relate mortality to basic (human or physical) drivers such as population density, rainfall seasonality, or rainfall frequency across the Mediterranean Basin. The mapping of F shows a negative mortality gradient between the western and the eastern parts of the Mediterranean Sea. The south of France appears to be the most affected region. The maps also highlight the seasonality of flood-related deaths with the same west-east gradient. It confirms that flood mortality follows the climatological seasonal patterns across the Mediterranean Basin. Flood-related fatalities mainly occur during the early fall season in the western part of the Mediterranean area, while the Easter Basin is affected later, in November or during the winter season. Eastern Turkey introduces another pattern, as mortality is more severe in summer. Mortality maps are then compared with factors that potentially contribute to the occurrence of flood fatalities, such as precipitation intensity (rainfall hazard), to explain geographical differences in the fatality rate. The density of a fatal event is correlated to the population density and the rainfall frequency. Conversely, the average number of deaths per event depends on other factors such as prevention or crisis managemen

Long-term precipitation in Southwestern Europe reveals no clear trend attributable to anthropogenic forcing

We present a long-term assessment of precipitation trends in Southwestern Europe (1850-2018) using data from multiple sources, including observations, gridded datasets and global climate model experiments. Contrary to previous investigations based on shorter records, we demonstrate, using new long-term, quality controlled precipitation series, the lack of statistically significant long-term decreasing trends in precipitation for the region. Rather, significant trends were mostly found for shorter periods, highlighting the prevalence of interdecadal and interannual variability at these time-scales. Global climate model outputs from three CMIP experiments are evaluated for periods concurrent with observations. Both the CMIP3 and CMIP5 ensembles show precipitation decline, with only CMIP6 showing agreement with long term trends in observations. However, for both CMIP3 and CMIP5 large interannual and internal variability among ensemble members makes it difficult to identify a trend that is statistically different from observations. Across both observations and models, our results make it difficult to associate any declining trends in precipitation in Southwestern Europe to anthropogenic forcing at this stage

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies

Long-term variability and trends in meteorological droughts in Western Europe (1851-2018)

We analyzed long-term variability and trends in meteorological droughts across Western Europe using the Standardized Precipitation Index (SPI). Precipitation data from 199 stations spanning the period 1851-2018 were employed, following homogenisation, to derive SPI-3 and SPI-12 series for each station, together with indices on drought duration and severity. Results reveal a general absence of statistically significant long-term trends in the study domain, with the exception of significant trends at some stations, generally covering short periods. The largest decreasing trends in SPI-3 (i.e. increasing drought conditions) were found for summer in the British and Irish Isles. In general, drought episodes experienced in the last two or three decades have precedents during the last 170 years, emphasising the importance of long records for assessing change. The main characteristic of drought variability in Western Europe is its strong spatial diversity, with regions exhibiting a homogeneous temporal evolution. Notably, the temporal variability of drought in Western Europe is more dominant than long-term trends. This suggests that long-term drought trends cannot be confirmed in Western Europe using precipitation records alone. This study provides a long-term regional assessment of drought variability in Western Europe, which can contribute to better understanding of regional climate change during the past two centuries.This work was supported by the research projects PCIN-2015-220 and CGL2017- 82216-R financed by the Spanish Commission of Science and Technology and FEDER, IMDROFLOOD financed by the WaterWorks 2014 co-funded call of the European Commission, CROSSDRO financed by the AXIS (Assessment of Cross(X) – sectorial climate Impacts and pathways for Sustainable transformation) JPI-Climate co-funded call of the European Commission, INDECIS, which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR), FCT (PT) with co-funding by the European Union (Grant 690462), Irish Research Council COALESCE grant 2019/43

The complex and spatially diverse patterns of hydrological droughts across Europe

This study presents a new data set of gauged streamflow (N = 3,224) for Europe spanning the period 1962–2017. The Monthly Streamflow of Europe Dataset (MSED) is freely available at http://msed.csic.es/. Based on this data set, changes in the characteristics of hydrological drought (i.e., frequency, duration, and severity) were assessed for different regions of Europe. Due to the density of the database, it is possible to delimit spatial patterns in hydrological droughts trend with the greatest detail available to date. Results reveal bidirectional changes in monthly streamflow, with negative changes predominating over central and southern Europe, while positive trends dominate over northern Europe. Temporally, two dominant patterns were noted. The first pattern corresponds to a consistent downward trend in all months, evident for southern Europe. A second pattern was noted over central and northern Europe and western France, with a predominant negative trend during warm months and a positive trend in cold months. For hydrological drought events, results suggest a positive trend toward more frequent and severe droughts in southern and central Europe and conversely a negative trend over northern Europe. This study emphasizes that hydrological droughts show complex spatial patterns across Europe over the past six decades, implying that hydrological drought behavior in Europe has a regional character. Accordingly it is challenging to adopt “efficient” strategies and policies to monitor and mitigate drought impacts at the continental level

On the visual detection of non-natural records in streamflow time series: challenges and impacts

Large datasets of long-term streamflow measurements are widely used to infer and model hydrological processes. However, streamflow measurements may suffer from what users can consider anomalies, i.e. non-natural records that may be erroneous streamflow values or anthropogenic influences that can lead to misinterpretation of actual hydrological processes. Since identifying anomalies is time consuming for humans, no study has investigated their proportion, temporal distribution, and influence on hydrological indicators over large datasets. This study summarizes the results of a large visual inspection campaign of 674 streamflow time series in France made by 43 evaluators, who were asked to identify anomalies falling under five categories, namely, linear interpolation, drops, noise, point anomalies, and other. We examined the evaluators' individual behaviour in terms of severity and agreement with other evaluators, as well as the temporal distributions of the anomalies and their influence on commonly used hydrological indicators. We found that inter-evaluator agreement was surprisingly low, with an average of 12 % of overlapping periods reported as anomalies. These anomalies were mostly identified as linear interpolation and noise, and they were more frequently reported during the low-flow periods in summer. The impact of cleaning data from the identified anomaly values was higher on low-flow indicators than on high-flow indicators, with change rates lower than 5 % most of the time. We conclude that the identification of anomalies in streamflow time series is highly dependent on the aims and skills of each evaluator, which raises questions about the best practices to adopt for data cleaning.</p

Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM) model developed by Meteo-France was used. This study was done in the Gardon catchment (545 km(2)) in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R-2 values increasing from 0.61 to 0.72