Records |
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 |
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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English |
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0236-8722 |
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Notes |
CropM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4728 |
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Author |
Baranowski, P.; Slawinski, C.; Krzyszczak, J. |
Title |
Short presentation of partner’s P139 involvement in CropM |
Type |
Conference Article |
Year |
2013 |
Publication |
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Keywords |
TradeM; CropM |
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MACSUR TradeM Workshop on Global Food Security Challenges – European Research approaches. Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany, 2013-11-18 to 2013-11-20 |
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no |
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MA @ admin @ |
Serial |
2294 |
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Author |
Baranowski, P.; Mazurek, W.; Pastuszka-Wozniak, J. |
Title |
Supervised classification of bruised apples on the base of hyperspectral imaging data |
Type |
Conference Article |
Year |
2013 |
Publication |
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Volume |
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Issue |
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Pages |
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Keywords |
CropM |
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10th International Conference on Agrophysics, 2013-06-05 to 2013-06-07 |
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no |
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MA @ admin @ |
Serial |
2295 |
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Author |
Baranowski, P.; Krzyszczak, J.; Slawinski, C. |
Title |
Multifractal analysis of chosen meteorological time series to assess climate impact in field level |
Type |
Conference Article |
Year |
2014 |
Publication |
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Volume |
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Pages |
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Keywords |
CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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no |
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MA @ admin @ |
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2296 |
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Author |
Baranowski, P. |
Title |
Multifractal analysis of meteorological time series to assess climate impact on chosen regions of Europe |
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Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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Volume |
5 |
Issue |
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Pages |
Sp5-4 |
Keywords |
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Abstract |
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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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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no |
Call Number |
MA @ admin @ |
Serial |
2119 |
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