The intense weather conditions that occurred on July 16 and 17, 2017 were the reason for further analysis and study of this event. In order for the results to have a higher confidence level, discrete spatial discrepancy data on a normal 0.125 X 0.125 grid, which are available from the European Center Meteorological Weather Forecasting (ECMWF), at the Hellenic National Meteorological Service (HNMS) were used. Thermodynamic parameters such as potential vortiticity, potential temperature, sensible and latent heat fluxes and static stability were calculated. Finally, all of the above were determined by the real picture of the weather and Eumetsat’s satellite imagery.
The warm period has always been of special interest as far as the rainfall systems and their predictability are concerned. The weather incident, not seasonally common, that took place during July 16 and 17, 2017 was a particular synoptic system case not only due to its structure, spatial and temporal evolution, but also due to the intensity and seriousness of the phenomena. The purpose of this case study is to analyze the synoptic environment of the particular system using troposphere's upper and lower maps that are daily available in Hellenic National Meteorological Service’s database by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the real-time weather data, in conjunction with the corresponding images from the Eumetsat satellites.
Nowadays there is a profound increase in the number of natural disasters attributed to extreme weather events which is significantly impeding progress towards sustainable development. To deal with a risk of an emergency threatening life or property, a weather-forecast office would use a range of forecast tools to assess the threat and provide the necessary forecasts and warnings. In this paper, using as case study the severe weather occurred in Greece on 16 and 17 July 2017, we discuss the capability of the ECMWF/EPS and the COSMO-LEPS forecasts, as also the ΕCMWF/HRES and COSMO.GR7 deterministic forecasts to provide forecasters with reliable prognostic guidance. To do so, we used these models’ consecutive runs from Friday 14-7-2017 (two days before the event) until Monday 17 -7-2017 (last day of the event). The effectiveness of these forecasts (rainfall spatiotemporal distribution and intensity) was then evaluated with the accumulated precipitation at ground (H-SAF/PR-OBS-5), with MSG products (RGB Airmass, Cloud Top Height) provided by EUMETSAT and with weather radar products.
In the present study extreme rainfall frequency analysis was performed using block maxima (BM) and peaks over threshold (POT) approaches based on daily rainfall data gathered from three meteorological stations in Greece (Larisa, Agxialos, Trikala). In the first method, 9 different probability distributions (2 and 3 parameter distributions) were fitted to the samples (that were previously checked for randomness, trends and change points in the mean) in order to estimate rainfall depths for high return periods. According to diagnostic plots and Kolmogorov-Smirnov goodness of fit test, the fitting was acceptable for all the distributions that were considered in the three stations. However, the 3-parameter distributions and more specifically GEV for Larisa and Trikala and 3-parameter Lognormal for Agxialos, had a better fitting in the extreme values and could be considered more suitable for statistical modeling in these three stations. In the POT approach a suitable threshold was selected based on plots and statistical indexes. The excesses were modeled using the Generalized Pareto (GP) and a mixed model of Poisson and GP distributions. The estimated rainfall depths in this approach show similarities between the two models, as well as with those of the 3 parameter distributions used in the BM approach.
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