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.

We have used the Kolmogorov complexities, sample and permutation entropies to quantify the randomness degree in river flow time series of two mountain rivers in Bosnia and Herzegovina, representing the turbulent environmental fluid, for the period . In particular, we have examined the monthly river flow time series from two rivers (Miljacka and Bosnia) in mountain part of their flow and then calculated the Kolmogorov Complexity (KL) based on the Lempel-Ziv Algorithm (LZA) (Lower -KLL and Upper -KLU), Sample Entropy (SE) and Permutation Entropy (PE) values for each time series.The results indicate that the KLL, KLU, SE and PE values in two rivers are close to each other regardless of the amplitude differences in their monthly flow rates. We have illustrated the changes in mountain river flow complexity by experiments using (i) the data set for the Bosnia River and (ii) anticipated human activities and projected climate changes. We have explored the sensitivity of considered measures in dependence on the length of time series. In addition, we have divided the period 1926-1990 into three subintervals: (a) 1926 -1945, (b) 1946-1965, (c) 1966-1990, and calculated the KLL, KLU, SE, PE values for the various time series in these subintervals. It is found that during the period 1946 -1965, there is a decrease in their complexities, and corresponding changes in the SE and PE, in comparison to the period 1926-1990. This complexity loss may be primarily attributed to (i) human interventions, after the Second World War, on these two rivers because of their use for water consumption and (ii) climate change in recent time.

Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural variability of solar irradiation is being complicated by atmospheric conditions (in particular cloudiness) and orography, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the years 2013, 2014 and 2015 at 11 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use a set of novel quantitative tools: Kolmogorov complexity (KC) with its derivative associated measures and Hamming distance (HAM) and their combination to assess complexity and corresponding predictability. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. However, all of them can be classified into three groups strongly influenced by trade winds that circulate in a “flow around” regime: the windward side (trade winds slow down), the leeward side (diurnal thermally-induced circulations dominate) and the coast parallel to trade winds (winds are accelerated due to Venturi effect). We introduce Kolmogorov time (KT) that quantifies the time span beyond which randomness significantly influences predictability.

We have used the Kolmogorov complexity and sample entropy measures to estimate the complexity of the UV-B radiation time series in the Vojvodina region (Serbia) for the period 1990-2007. We have defined the Kolmogorov complexity spectrum and have introduced the Kolmogorov complexity spectrum highest value (KLM). We have established the UV-B radiation time series on the basis of their daily sum (dose) for seven representative places in this region using: (i) measured data, (ii) data calculated via a derived empirical formula and (iii) data obtained by a parametric UV radiation model. We have calculated the Kolmogorov complexity (KL) based on the Lempel-Ziv Algorithm (LZA), KLM and Sample Entropy (SE) values for each time series. We have divided the period 1990-2007 into two subintervals: (a) 1990-1998 and (b) 1999-2007 and calculated the KL, KLM and SE values for the various time series in these subintervals. It is found that during the period 1999-2007, there is a decrease in the KL, KLM, and SE, comparing to the period 1990-1998. This complexity loss may be attributed to (i) the increased human intervention in the post civil war period causing increase of the air pollution and (ii) the increased cloudiness due to climate changes.

We considered thermal environment and UV-B radiation indices in the Vojvodina region, Serbia. We derived an empirical formula for estimating the daily sum of the UV-B from global radiation and used this formula to reconstruct the UV-B radiation pattern for 1981-2008. We describe the actual climate conditions for the period 1992−2008. In addition, we applied a statistical downscaling technique on ECHAM5 outputs under the A2 scenario to assess the 2040 climate. The results indicate that a warmer and drier climate in the Vojvodina region can be expected because of the following evidence: an increase in the mean annual temperature (8.6 to 12.3%) and in the frequency of hot days (29.4 to 50%); a decrease in the mean annual precipitation (8.1 to 14.2%) and in the frequency of cold days (11.8 to 27.8%); a higher increase in the mean temperature for the colder period (24.9%) than for the hotter one (6.7%); and a reduction in precipitation during the growing season (15.7%). We have analyzed the thermal environment for the period 1992 −2008 using the wind chill index and the heat index for the winter (December to February) and summer (June to August) periods. In all places, the heat index has a tendency for growth. We determined an increase in the daily UV-B dose in an amount of 3.7% per decade. Even though there is some evidence indicating ozone stabilization, there are no signs of a significant recovery of ozone layer thickness, so it can be expected that UV-B dose levels will remain high in the future.