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Abstract:We propose novel metrics based on the Kolmogorov complexity for use in complex system behavior studies and time series analysis. We consider the origins of the Kolmogorov complexity and discuss its physical meaning. To get better insights into the nature of complex systems and time series analysis we introduce three novel measures based on the Kolmogorov complexity: (i) the Kolmogorov complexity spectrum, (ii) the Kolmogorov complexity spectrum highest value and (iii) the overall Kolmogorov complexity. The characteristics of these measures have been tested using a generalized logistic equation. Finally, the proposed measures have been applied to di erent time series originating from: a model output (the biochemical substance exchange in a multi-cell system), four di erent geophysical phenomena (dynamics of: river ow, long term precipitation, indoor Rn concentration and UV radiation dose) and the economy (stock price dynamics). The results obtained o er deeper insights into the complexity of system dynamics and time series analysis with the proposed complexity measures.

SUMMARYOne of the main problems in estimating the effects of climate change on crops is the identification of those factors limiting crop growth in a selected environment. Previous studies have indicated that considering simple trends of either precipitation or temperature for the coming decades is insufficient for estimating the climate impact on yield in the future. One reason for this insufficiency is that changes in weather extremes or seasonal weather patterns may have marked impacts.The present study focuses on identifying agroclimatic parameters that can identify the effects of climate change and variability on winter wheat yield change in the Pannonian lowland. The impacts of soil type under past and future climates as well as the effect of different CO2 concentrations on yield formation are also considered. The Vojvodina region was chosen for this case study because it is a representative part of the Pannonian lowland.Projections of the future climate were taken from the HadCM3, ECHAM5 and NCAR-PCM climate models with the SRES-A2 scenario for greenhouse gas (GHG) emissions for the 2040 and 2080 integration periods. To calibrate and validate the Met&Roll weather generator, four-variable weather data series (for six main climatic stations in the Vojvodina region) were analysed. The grain yield of winter wheat was calculated using the SIRIUS wheat model for three different CO2 concentrations (330, 550 and 1050 ppm) dependent on the integration period. To estimate the effects of climatic parameters on crop yield, the correlation coefficient between crop yield and agroclimatic indices was calculated using the AGRICLIM software. The present study shows that for all soil types, the following indices are the most important for winter wheat yields in this region: (i) the number of days with water and temperature stress, (ii) the accumulated precipitation, (iii) the actual evapotranspiration (ETa) and (iv) the water deficit during the growing season. The high positive correlations between yield and the ETa, accumulated precipitation and the ratio between the ETa and reference evapotranspiration (ETr) for the April–June period indicate that water is and will remain a major limiting factor for growing winter wheat in this region. Indices referring to negative impact on yield are (i) the number of days with a water deficit for the April–June period and (ii) the number of days with maximum temperature above 25 °C (summer days) and the number of days with maximum temperature above 30 °C (tropical days) in May and June. These indices can be seen as indicators of extreme weather events such as drought and heat waves.

ABSTRACT:We considered shifts in the Köppen climate zones and the corresponding impact on the crop yields in Serbia by comparing (1) the results of downscaling with the ECMWF Hamburg Atmospheric Model 5 (ECHAM5) and regional Eta Belgrade University (EBU)-Princeton Ocean Model (POM) model for the A1B and A2 scenarios over 2001-2030 and 2071-2100 and (2) the present climate simulations for the period 1961−1990. We analyzed the EBU-POM regional climate model complexity by calculating the corresponding metrics. The yields of winter wheat, maize and soybeans were evaluated with the Decision Support System for Agrotechnology Transfer (DSSAT) model.In the future, the Köppen climate zones of Serbia will shift in coverage percentage and altitude from the present climate simulations toward warmer and drier climate zones. The calculated climate indices feature changes in the following parameters: increases in the mean annual temperature, growing season temperature, number of growing degree days (higher than 5 ∘ C) and the frequency of tropical days; and decreases in the mean annual precipitation, growing season precipitation and frequency of frost days. Yields of crops (winter wheat, maize and soybeans) will increase on average under both scenarios, with the exception of maize in non-irrigated conditions and under the A2 scenario.