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Author Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P.
Title Statistical modelling of agrometeorological time series by exponential smoothing Type Journal Article
Year 2016 Publication International Agrophysics Abbreviated Journal International Agrophysics
Volume 30 Issue 1 Pages 57-65
Keywords exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather
Abstract (up) Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.
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ISSN 0236-8722 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4728
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Author Baranowski, P.
Title Multifractal analysis of meteorological time series to assess climate impact on chosen regions of Europe Type
Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 5 Issue Pages Sp5-4
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Abstract (up) Over the last decades modelling of climate change through the analysis of empirical meteorological data has become of great interest. The standard approach gives satisfactory results only in the climatic zones with extreme dynamics of climate change, thus there is need to develop and apply more subtle methods such as fractal analysis and chaotic evolution analysis of the atmospheric system. The scaling analysis of meteorological time series is complicated because of the presence of localized trends and nonstationarities. The objective of this study was to characterize scaling properties (i.e. statistical self-similarity) of the daily air temperature, wind velocity, relative air humidity, global radiation and precipitation through multifractal detrended fluctuation analysis on data from 31 years for stations located in Finland, Germany, Poland and Spain. The empirical singularity spectra indicated their multifractal structure. The richness of the studied multifractals was evaluated by the width of their spectrum, indicating considerable differences in dynamics and development. The log-log plots of the cumulative distributions of all the studied absolute and normalized meteorological parameters tended to linear functions for high values of the response, indicating that these distributions were consistent with the power law asymptotic behaviour. Additionally, we investigated the type of multifractality that underlies the q-dependence of the generalized Hurst exponent, by analysing the corresponding shuffled and surrogate time series. The results suggest that MFDFA is valuable for assessing the change of climate dynamics. No Label
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Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK
Notes Approved no
Call Number MA @ admin @ Serial 2119
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Author Krzyszczak, J.R.; Baranowski, P.; Sławiński, C.
Title CO2 flux measurements in the vegetation period of winter wheat in Lubelskie province Type Conference Article
Year 2014 Publication Abbreviated Journal
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Abstract (up) The assessment of net ecosystem exchange and respiration of ecosystem of terrestrial ecosystems is necessary to improve our knowledge about carbon cycle in nature. Here we present measurements of CO2 fluxes for a winter wheat temperate climate ecosystem (buckwheat in the previous years) located in the Lubelskie province (eastern Poland) using a closed dynamic chamber system over a 2013 vegetation season. Measurements of carbon dioxide emission from soils and its assimilation by plants were carried out on a typical for Lubelskie highland arable land located in the Stany Nowe (N50o49’17.0555”, E22o16’28.51”, height 243m above sea level) using the set of two chambers (transparent and dark). Carbon dioxide fluxes have been measured by EGM-4 PP Systems sensor during fixed stages of the plant growing season. During the experiment carbon emission from soil ranged from 151 to 764 mg C·m-2·h-1 and its assimilation by plants ranged from -148 (emission) to 1585 mg C·m-2·h-1. We found substantial differences in emission and assimilation of carbon in the winter wheat ecosystem. This, along with other measurements (meteorological factors and soil and plant parameters) carried out in the Stany Nowe can be used as a high quality data to verify various models of  emission of greenhouse gases. The chamber technique occurs to be  a useful tool for determining carbon dioxide exchange between ecosystem surface and the atmosphere.
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Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
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Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5064
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Author Baranowski, P.; Krzyszczak, J.R.; Sławiński, C.F.
Title Self-similarity analysis of chosen agro-meteorological time series Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
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Abstract (up) The most usual records of observable agro-meteorological quantities are in the form of time series and the knowledge about their scaling properties is fundamental for  transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated because of  the presence of localized trends and nonstationarities. The objective of this study was to characterize scaling properties (i.e. statistical self-similarity) of the  chosen agro-meteorological quantities through multifractal detrended fluctuation analysis (MFDFA). The MDFA analysis was performed  for time series of the air temperature, wind velocity and relative air humidity (at the height of 2 m above the  active surface) as well as the soil temperature (at 10 cm depth in the soil). The studied data were hourly interval, 12 years’ time series from the agro-meteorological station in Felin, near Lublin, Poland. The empirical singularity spectra  indicated their multifractal structure. The richness of the studied multifractals was evaluated by the width of their spectrum, indicating their considerable differences in dynamics and development. The log-log plots of the cumulative distributions of all the studied absolute and normalized meteorological parameters tended to linear functions for high values of the response  indicating that these distributions were consistent with the power law asymptotic behaviour. Additionally, we investigated the type of multifractality, that underlies the q-dependence of the generalized Hurst exponent, by analyzing the corresponding shuffled and surrogate time series. For majority of studied quantities, the multifractality was due to different long-range correlation for small and large fluctuations.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5124
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Author Bojar, W.; Knopik, L.; Żarski, J.; Sławiński, C.; Baranowski, P.; Żarski, W.
Title Impact of extreme climate changes on the forecasted agriculture production Type Journal Article
Year 2014 Publication Acta Agrophysica Abbreviated Journal Acta Agrophysica
Volume 21 Issue 4 Pages 415-431
Keywords agricultural economics; agriculture; climate change; crop production; integrating assessments
Abstract (up) The paper presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie and Lubelskie Regions, based on statistical databases and literature review. Some specific features of the regions, with special consideration for the predicted extreme climate changes, are also included. Next, some statistically significant dependencies between the climatic parameters and yields of selected important crops in the abovementioned regions were worked out on the basis of empirical survey conducted in the University of Technology and Life Sciences, Bydgoszcz, and the Institute of Agrophysics in Lublin. Creating an appropriate method of forecasting long series of ten days without precipitation was necessary to find the desired dependencies. Third, some efforts were taken to make integrated assessments of forecast agricultural outputs influenced by climate extreme phenomena on the basis of the yield-precipitation relations obtained and on the data coming from wide area model regional outputs such as prices of farmland and produce.
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Language English Summary Language Original Title
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Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4619
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