No abstract

This paper investigates the potential for developing schemes that classify convective and stratiform precipitation areas using the high infrared spectral resolution of the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). Two different classification schemes were proposed that use the brightness temperature (BT) Τ 10.8 along with the brightness temperature differences (BTDs) Τ 10.8 -Τ 12.1 , Τ 8.7 -Τ 10.8 , and Τ 6.2 -Τ 10.8 as spectral parameters, which provide information about cloud parameters. The first is a common multispectral thresholding scheme used to partition the space of the spectral cloud parameters and the second is an algorithm based on the probability of convective rain (PCR) for each pixel of the satellite data. Both schemes were calibrated using as a reference convective\stratiform rain classification fields derived from 87 stations in Greece for six rainy days with high convective activity. As a result, one single infrared technique (TB 10 ) and two multidimensional techniques (BTD all and PCR) were constructed and evaluated against an independent sample of rain gauge data for four daily convective precipitation events. It was found that the introduction of BTDs as additional information to a technique works in improving the discrimination of convective from stratiform rainy pixels compared to the single infrared technique BT 10 . During the training phase, BTD all performed slightly better than BT 10 while PCR technique outperformed both threshold techniques. All techniques clearly overestimate the convective rain occurrences detected by the rain gauge network. When evaluating against the independent dataset, both threshold techniques exhibited the same performance with that of the dependent dataset whereas the PCR technique showed a notable skill degradation. As a result, BTD all performed best followed at a short distance by PCR and BT 10 . These findings showed that it is possible to apply a convective/ stratiform rain classification algorithm based on the enhanced infrared spectral resolution of MSG-SEVIRI, for nowcasting or climate purposes, despite the highly variable nature of convective precipitation.

No abstract

Our purpose in undertaking this research is to methodically map the labour market circumstances of the main immigrant groups in Greece. We classify all of the Districts of Greece into three categories (Diverse, Mixed and Unmixed) according to the ethnic composition of each District. We measure how the employment status of the immigrants varies (1) according to the ethnic group and sex of the immigrant, and (2) according to the ethnic composition and economic structure of a District. In general, the majority of immigrants exhibit lower unemployment and higher economic activity rates than the indigenous Greeks. Three immigrant groups (Albanians, Bulgarians and “Other”), which make up two‐thirds of the foreign‐born population of Greece, have lower unemployment rates than the national average, and lower rates than Greeks as well. The poorest labour market outcomes are observed in Unmixed and Mixed Districts, whereas Diverse Districts are better off. At the regional level, the most disadvantaged Geographical Department is the Ionian Islands, since it presents the highest unemployment rates for the general population for both sexes. With regard to sex‐differential unemployment across immigrant groups, we found that women exhibit higher unemployment than men in almost every ethnic group.

No abstract