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EN
The objective of the study was to compare the sum of actual sunshine duration in Poland, based on satellite and ground-based measurements during the period of 1983-2015. Results from the first group of data were derived from sunshine duration measurements from 44 surface synoptic stations belonging to the Polish Institute of Meteorology and Water Management (IMGW-PIB). The second group of data includes values from observations of Meteosat geostationary satellites (SARAH-2 climate data record), provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). The study showed that in Poland, values of linear correlation coefficients (r) between both datasets are high, and range between 0.80 and 0.95. Differences in daily sums of sunshine duration are low, with the prevalence of positive deviations, i.e. slightly higher values for satellite data. The largest positive deviations were found in Tarnów, Zielona Góra, and Racibórz (+0.3 h), with equivalent negative deviations in Warsaw and on Kasprowy Wierch (−0.4 h). Moreover, minor discrepancies were found for the long-term variability of the mean annual sums of actual sunshine duration. However, after 1995, the deviations were insignificant, and averaged 4 hours. Differences between both data series are caused by several factors, including an underestimation of aerosols optical depth (AOD), as well as the failure to consider the type of clouds covering the Sun’s disc. With its high spatial resolution (0.05° × 0.05°), the satellite data can be a valuable source of information, particularly in regional studies of the spatial variation of sunshine duration.
PL
W pracy analizowano skuteczność metod detekcji mgieł, opartych na danych z satelity MSG 2. Porównano metody teledetekcyjne z obserwacjami stanu pogody na stacjach synoptycznych IMGW-PIB z obszaru Polski, obejmującymi okres od października 2010 r. do marca 2011 r. Stwierdzono, że dane satelitarne pozwalają z dużym prawdopodobieństwem wskazać obszary występowania mgieł i niskich chmur Stratus. Określenie, kiedy występuje mgła, a kiedy tylko niski Stratus jest jednak bardzo trudne, a często niemożliwe, bez wykorzystania dodatkowych danych naziemnych. W tym celu można wykorzystać temperaturę punktu rosy i temperaturę powietrza mierzoną w klatce meteorologicznej. Rozróżnienie mgieł i chmur niskich jest bardzo cenne ze względów praktycznych, ponieważ mgła powoduje ograniczenie widzialności poniżej 1 km, natomiast chmura Stratus nie musi znacząco wpływać na możliwość obserwacji obiektów przy powierzchni ziemi. Metoda omówiona w pracy pozwoliła na wykrycie 50-64% zaobserwowanych mgieł. Około 25-35% sygnalizowanych przypadków wystąpienia mgły nie znalazło potwierdzenia w obserwacjach ze stacji synoptycznych (wystąpił tzw. fałszywy alarm).
EN
The study analyzed the effectiveness of mists detection methods, based on MSG satellite data. Remote sensing methods were compared with observations from synoptic stations IMGW-PIB from Poland, covering the period from October 2010 to March 2011. Satellite data allow identify areas likely occurrence of fog and low stratus clouds. Term when there is fog and low stratus soon but it is very difficult, if not impossible, without the use of additional ground-based data. For this purpose, can be use the dew point temperature and air temperature measured in meteorological cage. The distinction between fog and low clouds is very important for practical reasons, because fog reduces visibility less than 1 km, while the Stratus cloud doesn't have a significant impact on the ability to observe objects close to the ground. The method discussed in the paper made it possible to detect 5064% of observed fog. Approximately 25-35% of cases of fog signaled not confirmed in observations from synoptic stations (it was false alarm).
3
Content available remote Sea surface temperature retrieval from MSG/SEVIRI data in the Baltic Sea area
EN
The aim of the paper was to confirm the proposition that the classical SST algorithms MCSST and NLSST originally prepared for AVHRR data could also be used for Meteosat/SEVIRI data with satisfactory accuracy in the mid-latitude region, where the spatial resolution is about 7x7 km. The research was performed in the southern Baltic Sea (between 13°E 53°N and 21°E 58°N). Data were collected in all the seasons of 2007. The coefficients were found by means of regression analysis. SSTs determined on the basis of AVHRR data were used in the regression analysis instead of in situ data. A set of paired AVHRR and SEVIRI images spaced no more than 8 minutes apart were compared. The results show that the method is capable of producing sea surface temperatures with a statistical error (standard deviation) of 1°C.
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