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Baranowski, P.; Krzyszczak, J.; Hoffmann, H.; Sławiński, C. |
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Title |
Multifractal properties of spatially aggregated meteorological data – a regional study |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCropM 2016, 2016-03-15 to 2016-03-17, Berlin |
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MA @ admin @ |
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4909 |
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Baranowski, P.; Krzyszczak, J.; Slawinski, C.; Hoffmann, H.; Kozyra, J.; Nieróbca, A.; Siwek, K.; Gluza, A. |
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Title |
Multifractal analysis of meteorological time series to assess climate impacts |
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Journal Article |
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2015 |
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Climate Research |
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Clim. Res. |
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65 |
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39-52 |
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Keywords |
multifractal analysis; time series; agro-meteorological parameters; detrended fluctuation analysis; daily temperature records; catalonia ne spain; fractal analysis; river-basin; precipitation; variability; patterns; trends; china |
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Abstract |
Agro-meteorological quantities are often in the form of time series, and knowledge about their temporal scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and nonstationarities. The objective of this study was to characterise scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological quantities through multifractal detrended fluctuation analysis (MFDFA). For this purpose, MFDFA was performedwith 11 322 measured time series (31 yr) of daily air temperature, wind velocity, relative air humidity, global radiation and precipitation from 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. In log-log plots of the cumulative distributions of all meteorological parameters the linear functions prevailed for high values of the response, indicating that these distributions were consistent with 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. For most of the studied meteorological parameters, the multifractality is due to different long-range correlations for small and large fluctuations. Only for precipitation does the multifractality result mainly from broad probability function. This feature may be especially valuable for assessing the effect of change in climate dynamics. |
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English |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4666 |
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Constantin, J.; Bergez, J.-E.; Raynal, H.; Hoffmann, H.; Ewert, F. |
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Title |
Impact of maize management variability modeled as decision rules on yield and Drainage at the regional scale |
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2016 |
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Berlin (Germany) |
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poster |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4913 |
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Coucheney, E.; Eckersten, H.; Jansson, P.E.; Ewert, F.; Gaiser, T.; Hoffmann, H.; Lewan, E. |
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Title |
The role of spatial patterns of soil types for data aggregation effects in crop modelling |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4902 |
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Ewert, F.; Hoffmann, H.; WP3 partners |
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Title |
Scaling up crop models for large area application |
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2015 |
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CropM; |
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Minneapolis (U.S.A.) |
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AgMIP and partners session at tripartite meetings (ASA-CSSA-SSA) at Minneapolis/USA, 2015-11-15 to 2015-11-17, Minneapolis |
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MA @ admin @ |
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2426 |
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