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Drivers of soil moisture trends in the Czech Republic between 1961 and 2012
Trnka, Miroslav ; Brázdil, Rudolf ; Balek, J. ; Semerádová, Daniela ; Hlavinka, Petr ; Možný, M. ; Štěpánek, Petr ; Dobrovolný, Petr ; Zahradníček, Pavel ; Dubrovský, Martin ; Eitzinger, Josef ; Fuchs, B. ; Svoboda, M. ; Hayes, M. ; Žalud, Zdeněk
Soil moisture dynamics and their temporal trends in the Czech Republic are forced by various drivers. Our analysis of temporal trends indicates that shifts in drought severity between 1961 and 2012 and especially in the April, May, and June period, which displayed such results as a 50% increase in drought probability during 1961–1980 in comparison to 2001–2012. We found that increased global radiation and air temperature together with decreased relative humidity (all statistically significant at p < 0.05) led to increases in the reference evapotranspiration in all months of the growing season; this trend was particularly evident in April, May, and August, when more than 80% of the territory displayed an increased demand for soil water. These changes, in combination with the earlier end of snow cover and the earlier start of the growing season (up to 20 days in some regions), led to increased actual evapotranspiration at the start of the growing season that tended to deplete the soil moisture earlier, leaving the soil more exposed to the impacts of rainfall variability. These results support concerns related to the potentially increased severity of drought events in Central Europe. The reported trend patterns are of particular importance with respect to expected climate change, given the robustness and consistency of the trends shown and the fact that they can be aligned with the existing climate model projections. Introduction
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Testing a statistical forecasting model of electric energy consumption for two regions in the Czech Republic
Rajdl, Kamil ; Farda, Aleš ; Štěpánek, Petr ; Zahradníček, Pavel
Precise forecasting of electric energy consumption is of great importance for the electric power industry. It helps system operators optimally schedule and control power systems, and even slight improvements in prediction accuracy might yield large savings or profits. For these reasons, many forecasting models based on various principles have been developed and studied. Because of energy consumption’s strong dependence on weather conditions, such models often utilize outputs from numerical weather prediction models. In this study, we present and analyse a statistical model for forecasting hourly electrical energy consumption by customers of E.ON Energie, a.s. in two regions of the Czech Republic. The aim of this model is to create hourly predictions up to several days in advance. The model uses hourly data of consumed energy from 2011–2014 and corresponding predictions of temperature and cloudiness provided by the ALADIN/ CZ model. The statistical model is based on a regression analysis applied to appropriate data samples and supplemented by several optional post-processing methods. Specifically, we use a robust linear regression algorithm to identify energy consumption’s dependence on temperature, the meteorological variable with the largest influence on consumption. Our post-processing methods focused on removing prediction bias resulting from economic situations (represented by the goss domestic product, GDP) and sudden temperature changes. We analysed the presented model from the point of view of the hourly predictions’ accuracy for 2013 and 2014. Accuracy was primarily measured by mean absolute error. It was evaluated for individual months, and the effects of individual parts of the model on accuracy value are shown. Introduction
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Köppen–Geiger climate classification by different regional climate models according to the SRES A1B scenario in the 21st century
Szabó-Takács, Beáta ; Farda, Aleš ; Zahradníček, Pavel ; Štěpánek, Petr
We investigate future climate conditions projected by six regional climate model (RCM) simulations driven by the SRES A1B emission scenario. As a diagnostic tool of climate change, we used the Köppen–Geiger climate classification as it is suitable for assessing climate change impacts on ecosystems. The analysis is based on a comparison of Köppen–Geiger climate subtypes during two future time slices (2021–2050 and 2070– 2100) with climate subtypes observed during 1961–2000. All RCMs showed expansion of the area covered by warmer climate types in the future, but the magnitude of the growth varied among RCMs. The differences stemmed from several sources, mainly boundary forcing provided by the driving global circulation models (GCMs) as well as different physical packages, resolution, and natural variability representation in individual GCMs. In general, RCMs driven by the ECHAM5-r3 GCM projected cooler climate conditions than did RCMs driven by the ARPÈGE GCM. This can be explained by two factors related to ECHAM5-r3: i) exaggerated transport of cool and moist air from the North Atlantic to Europe in summer, and ii) winter advection of cold air from the Artic owing to North Atlantic Oscillation blocking pattern alteration during solar minima as well as higher natural variability. RCM-related properties, such as physical package and spatial resolution, may also significantly affect climate predictions, although they do so to a smaller extent than does the driving GCM data.
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The change of the rain factor on the net of stations in the Czech Republic during 1961-2010
Střeštík, Jaroslav ; Rožnovský, J. ; Štěpánek, P. ; Zahradníček, P.
Precipitation totals do not express precisely the humidity conditions in the landscape. Therefore the Lang’s rain factor, constructed from monthly and annual average temperatures and precipitation totals on 267 stations in the Czech Republic during 1961-2010, has been used here. Its values are very different at different stations, the lowest they are at South Moravia and Labe lowlands. Its average for the whole territory displays a slow decrease during the 50 years, supplemented by strong fluctuations. The strongest decrease appears in the Northern boundary mountains. The same factor calculated only for summer displays stronger differences between highlands and lowlands, especially in South Moravian ones. Stronger decrease at North Moravia, especially in mountains, and very weak decrease at other parts takes place.
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Increase of annual and seasonal air temperatures in the Czech Republic during 1961-2010
Střeštík, Jaroslav ; Rožnovský, J. ; Štěpánek, P. ; Zahradníček, P.
Using the monthly means of air temperatures at 267 stations in the Czech Republic, the long-term change has been estimated at each station for the last 50 years. Annual mean temperatures for the whole country show a considerable increase, more pronounced than that for global temperature, however, supplemented by strong fluctuations from year to year. Long-term changes in air temperatures at different stations and in different regions vary. Stronger increase in air temperatures can be seen in Bohemia, whereas in Moravia temperature increase is not so significant. This difference is more pronounced in the winter, whereas in the summer, the differences are smaller and perhaps of opposite nature. This means that the continentality of the climate in Moravia increases, while in Bohemia it very slightly decreases. Long-term changes depend only marginally on the absolute values of annual mean temperatures at the respective station. The increase of autumn temperatures is considerably lower than that of other seasons.
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The change of annual and seasonal precipitation totals in the Czech Republic during 1961-2012
Střeštík, Jaroslav ; Rožnovský, J. ; Štěpánek, P. ; Zahradníček, P.
Using the monthly values of precipitation totals at 267 stations in the Czech Republic a longterm change has been estimated at each station for the last 50 years. Annual totals for the whole country display a slight increase, however, supplemented by a much stronger fluctuations from year to year. Long-term changes in annual totals at different stations and in different regions are different. In southern and western Bohemia precipitation totals increased more, in Elbe lowlands and in a large part of the Moravia, rather a small decrease in rainfall has been observed. Long-term changes depend only slightly on the total rainfall at the respective station or in the region. Summer precipitation totals increased more than annual averages, while spring precipitation totals decreased, at other times seasons the change is negligible. At the same time, the annual variation changes slightly: maximum precipitation has shifted from June to July and August.
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Quality control and homogeneity testing of daily time series of eca ECA&D
Zahradníček, Pavel ; Štěpánek, Petr ; Farda, Aleš ; Skalák, Petr
For any meaningful climate analysis, it is necessary for analysed time series to be homogeneous, which means that their variations are caused solely by variations in weather and climate (Conrad and Pollak 1950). Th us, prior to any analysis, the need to homogenize data and check their quality arises. Unfortunately, most of the climatological series that span over decades, to centuries, contain inhomogeneities caused by station relocations, exchange of observers, changes in the vicinity of the stations (e.g. urbanization), changes in instruments, observing practices (e.g. diff erent formulas for calculating daily means, diff erent observation times), etc. In this work we focused on testing the quality and homogeneity of daily data produced by ECA&D. Th is is a free available dataset of daily meteorological elements from the European Climate Assessment & Dataset (http://eca.knmi.nl/). Th is database was used to create a regular grid of EOBS points, which are oft en used to validate climate models.
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Past hydrometeorological extremes in south-western Moravia (Czech republic) derived from taxation records
Chromá, Kateřina ; Brázdil, Rudolf ; Valášek, H. ; Zahradníček, Pavel ; Dolák, L.
Historical records related to taxation at fi ve landed estates located in the south-western part of Moravia in today’s Czech Republic are employed for the study of hydrological and meteorological extremes during the 1761–1900 period. At that time, the tax system in Moravia allowed farmers to request tax relief if their crops or land were damaged by natural disaster. Th is study disclosed a total of 69 hydrometeorological events resulting in damage in the 1761–1900 period, with the highest concentration of extreme events in 1771–1799 and 1822– 1849 (together 82.6%). Of 113 extremes classifi ed, torrential rains (34.5%) and hailstorms (31.9%) were the most frequent, followed by thunderstorms, fl oods, windstorms and fl ash fl oods. June (30.4%) was the month with the highest occurrence of extreme events and July (31.0%) for classifi able extremes; in both cases their highest frequency occurred in May–August. However, the results obtained are infl uenced by uncertainties related to taxation records, such as temporal and spatial incompleteness or limitation of the vegetation period, as well as by the local occurrence of the phenomena studied, a trend demonstrated by comparison with the results of Dolák et al. (2013). Taxation records constitute a very important source of data for historical climatology and hydrology.
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Comparison of corrected and uncorrected model simulations in the perspective of climate change in the area of the Czech Republic
Štěpánek, Petr ; Farda, Aleš ; Zahradníček, Pavel ; Skalák, Petr
In recent years, simulations from various regional climate models became available for the area of the Czech Republic, thanks to several national and international projects (e.g. the EC FP6 projects CECILIA, ENSEMBLES or the national project VaV SP/1a6/108/07). Th e simulations of all the models were performed according to the IPCC A1B emission scenario with various spatial resolutions. Since models suff er from biases, the model outputs were statistically corrected using the quantile approach of M. Déqué. Aft er correction, the RCM outputs were statistically processed and analyzed, especially for air temperature and precipitation, but also for other elements (like relative humidity, wind speed and sunshine duration). In this study, the diff erences between models outputs, as well as the corrected and uncorrected results, are presented.
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