Abstract. In the assessment of social impact caused by meteorological events, factors of different natures need to be considered. Not only does hazard itself determine the impact that a severe weather event has on society, but also other features related to vulnerability and exposure.The requests of data related to insurance claims received in meteorological services proved to be a good indicator of the social impact that a weather event causes, according to studies carried out by the Social Impact Research Group, created within the framework of the MEDEX project. Taking these requests as proxy data, diverse aspects connected to the impact of heavy rain events have been studied.The rainfall intensity, in conjunction with the population density, has established itself as one of the key factors in social impact studies. One of the conclusions we obtained is that various thresholds of rainfall should be applied for areas of varying populations. In this study, the role of rainfall intensity has been analysed for a highly populated urban area like Barcelona. A period without significant population changes has been selected for the study to minimise the effects linked to vulnerability and exposure modifications. First, correlations between rainfall recorded in different time intervals and requests were carried out. Afterwards, a method to include the intensity factor in the social impact index was suggested based on return periods given by intensity-durationfrequency (IDF) curves.
Abstract. In the assessment of social impact caused by meteorological events, factors of different nature need to be considered. Not only does hazard itself determine the impact that a severe weather event has on society, but also other features related to vulnerability and exposure. The requests of data related to insurance claims received in Meteorological Services proved to be a good indicator of the social impact that a weather event causes, according to studies carried out by the Social Impact Research Group, created under the frame of the MEDEX project. Taking these requests as proxy data, diverse aspects connected to the impact of heavy rain events have been studied. The rainfall intensity in conjunction with the population density has demonstrated to be one of the key factors in social impact studies. One of the conclusions we obtained is that various thresholds of rainfall should be applied for differently populated areas. In this study, the role of rainfall intensity has been analysed for a highly populated urban area like Barcelona. A period without significant population changes has been selected for the study to minimise the effects linked to vulnerability and exposure. First, correlations between rainfall recorded in different time intervals and requests have been carried out. Afterwards, a method to include the intensity factor in the social impact index has been suggested, based on return periods given by Intensity-Duration-Frequency (IDF) curves.
<div> <p><span>Future climate projections for the Mediterranean area point out to an important increase in temperature during this century, independently on the considered emission scenario. This projected increase will have a significant impact on temperature-related climate indices, such as heating and cooling degree-days, and also, the economic costs to maintain climate comfort within buildings, especially for summer. These indices are key outside temperature-based indices to evaluate the energy consumption of buildings.</span><span>&#160;</span></p> </div><div> <p><span>In this work, a very high spatial resolution database for heating (HDD) and cooling degree-days (CDD) has been performed from different temperature data: The network of automatic weather station from the Meteorological Service of Catalonia from 2006 to 2015 (138 stations in 32,000 km2), and non-automatic weather station data from 1971 to 2015. It has been taking as a baseline 15 and 18 &#176;C for HDD, and 21 and 25 &#176;C as thresholds for CDD.</span><span>&#160;</span></p> </div><div> <p><span>Data from automatic weather stations allow us to compute these indices with a high temporal accuracy (hourly or sub-hourly time scales), but they are only available with a highly-dense network for the last few 15 years. Otherwise, data from non-automatic weather stations allows us to analyse a wider temporal coverage, but only with daily-mean temperature data. Thus, in areas with a complex topography, as it is the case of Catalonia, important differences at annual scale can appear when computing HDD and CDD from daily or hourly-mean values, especially for zones prone to thermal inversion situations. Hourly data leads to increase HDD and CDD for each considered threshold. The differences among them reach annual-mean values higher than 200 &#186;C-days for heating degree-days and 150 &#186;C-days for cooling degree-days.</span><span>&#160;</span></p> </div><div> <p><span>Taking into account statistically downscaled climate projections at 1-km spatial resolution from 3 IPCC-AR5 global climate simulations forced by RCP4.5 and RCP8.5 emission scenarios, it is expected a significant decrease in HDD for the Pyrenees, up to 2000-2400 &#186;C-days in 2100, for 15 and 18 &#186;C thresholds, respectively. Meanwhile, it is projected an important increase in CDD for the Ebro Valley, up to 400-600 &#186;C-days in 2100, for 25 and 21 &#186;C thresholds, respectively.</span></p> </div><p>&#160;</p>
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