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The time distributions of neutron and gamma events for the plutonium metal plates of different isotopic compositions in a singles and coincidence acquisition mode were measured with the Fast Neutron Multiplicity Counter (FNMC) consisting of 8 EJ-309 liquid scintillators and 8 stilbene detectors. Since time intervals between detected events depend on the source activity, estimation of 240Pu effective mass in an investigated sample was based on the calibration curve obtained by using a subset of the remaining Pu metal plates. It was demonstrated that the neutron time interval distributions can provide the evaluation of 240Pu effective mass with high accuracy. The Kolmogorov complexity (KC) and Lyapunov exponent were calculated to reveal the presence of a chaotic and non-random time series in all the measured ones.

Solar irradiance represents one of the principal phenomena of interest in geophysics and recent research, especially which concerned with renewable energy, suggests that the complexity of solar irradiance time series offers important insights into the dynamics of different geophysical systems. We examined the complexity of the daily cumulative global horizontal irradiance (kWh/m2; dGHI in further text) recorded by satellite for 32 stations on the island of La Réunion over a 35-month period (2004–2006) using Kolmogorov complexity (KC) and a recently introduced measure—Aksentijevic–Gibson complexity (AG) which is capable of quantifying the complexity of both long and short strings. Previous examinations of physical data suggest that AG could represent a useful addition to the geophysical analysis toolkit. Our results demonstrate for the first time that running KC is capable of capturing periodic patterns in data and that AG is sensitive to both global/long-scale spatial and temporal structure and local/short-range complexity fluctuations. Importantly, we report a putative weekly periodicity which might be related to environmental factors and human activity. In conclusion, we suggest that AG could represent a useful tool in the study of solar irradiation time series but also with other types of geophysical data.

Alluvial channels with sinuosity follow an altered flow behavior, contradictory to straight flows. At the interface of surface water and groundwater, seepage is a significant phenomenon occurring at the boundary of alluvial channels. The study of turbulence in seepage affected sinuous alluvial channels would thus provide us with a better insight into their hydro-morphological behavior. To address the nature of turbulence in sinuous channel with downward seepage an experimental framework was design. The paper reports the structure of turbulence in the sinuous channel for no seepage and seepage flow. With downward seepage, there is a noticeable shift of Reynolds shear stress at near-bed, which reports more momentum transport. The average streamwise and transverse turbulence intensity increased by 3.8–18.5% and 4–10.6%, respectively with downward seepage. Calculation of Kolmogorov complexity and the Kolmogorov complexity spectrum suggests higher randomness in the outer region, which can be associated with excess momentum transport. In the lower flow depth $$ \left( {{\text{z}}/{\text{h}}} = 0.2 \right)$$ , the randomness in the transverse velocities is higher in the outer region of the bend for about 25% and 38% compared to the central and inner region of the bend, respectively. With downward seepage, randomness increased especially in the outer region. This increase in randomness may report the erosive action in the outer part of the bend. Permutation entropy provided an informative measure to study the complex behavior of the transverse velocity time-series, which we found to be higher in the outer flow zone. For downward seepage, mean of entropy increased across the bend. The turbulent flow alterations and increase in randomness with seepage may be helpful to understand the flow in seepage affected sinuous alluvial channels.

This paper deals with the first analysis of the neutron and gamma time series measured with organic scintillators from plutonium samples by using information measures. Fast neutron detection with organic scintillators has been widely used for various nuclear applications and homeland security. One of the significant attributes of special nuclear materials (SNM) is the high multiplicity events in a short period of time. The time distributions of neutron and gamma-rays events for the plutonium metal plates designed as fuel plates for the Idaho National Laboratory (INL) Zero Power were measured with the Fast Neutron Multiplicity Counter (FNMC) consisting of 8 EJ-309 liquid scintillators and 8 stilbene detectors. Since the neutron correlated counts within the coincidence window of 40 ns are related to 240Pu effective mass of plutonium metal plates we investigated the randomness of the measured neutron and gamma-rays events. To access such information, we resort to complexity measures in the hope of being able to connect complexity values with the reliability of detection. That was done through (i) application of Kolmogorov complexity (KC) and its derivatives [Kolmogorov spectrum and its highest value (KCM) and running complexity (RKC)] and (ii) establishing the breaking point after which there exists a sharp drop in the running Kolmogorov complexity of the neutron and gamma-rays time series. It was found that the complexity of all the time series detected from the sample with 5, 9, 11, 13, and 15 plutonium plates had the high almost identical values of KC while the sample with 3 plates had by one-third smaller KC values than all the others. These calculations were supplemented by the Lypaunov exponents for a time series and the NIST tests. The low KC values can be addressed to the different sources of uncertainties in measuring procedure with the sample consisting of three plates., 37 pages, 12 figures

Aksentijevic–Gibson complexity is an original complexity measure based on the amount of change in a string or 2D array that has been successfully implemented on data from psychology to physics. The key ingredient to computing the measure is a change symmetry (CS)—a novel form of structure (also known as generalised palindrome) which represents a central or mirror symmetry based on the redundant arrangement not of symbols but of changes. This results in patterns that although globally symmetrical do not appear as such when inspected locally. We used this property to (a) affect the registration of a target, (b) prime the symmetry judgment of 2D arrays and (c) faces using 1D patterns possessing change symmetry. In Experiment 2, we applied the lock and key principle to complete the prime without showing its structure at once. In Experiments 3 and 4, we presented subjects with fast sequences of CSs such that the configuration of an individual pattern was masked by the subsequent pattern leaving only the structural “essence” of the prime symmetry. The results strongly support the contention that higher-level hidden structure of change symmetry successfully primes the symmetry perception of 2D arrays as well as facial attractiveness.

Motivated by the One Health paradigm, we found the expected changes in temperature and UV radiation (UVR) to be a common trigger for enhancing the risk that viruses, vectors, and diseases pose to human and animal health. We compared data from the mosquito field collections and medical studies with regional climate model projections to examine the impact of climate change on the spreading of one malaria vector, the circulation of West Nile virus (WNV), and the incidence of melanoma. We analysed data obtained from ten selected years of standardised mosquito vector sampling with 219 unique location-year combinations, and 10 years of melanoma incidence. Trends in the observed data were compared to the climatic variables obtained by the coupled regional Eta Belgrade University and Princeton Ocean Model for the period 1961-2015 using the A1B scenario, and the expected changes up to 2030 were presented. Spreading and relative abundance of Anopheles hyrcanus was positively correlated with the trend of the mean annual temperature. We anticipated a nearly twofold increase in the number of invaded sites up to 2030. The frequency of WNV detections in Culex pipiens was significantly correlated to overwintering temperature averages and seasonal relative humidity at the sampling sites. Regression model projects a twofold increase in the incidence of WNV positive Cx. pipiens for a rise of 0.5°C in overwintering TOctober-April temperatures. The projected increase of 56% in the number of days with Tmax ≥ 30°C (Hot Days-HD) and UVR doses (up to 1.2%) corresponds to an increasing trend in melanoma incidence. Simulations of the Pannonian countries climate anticipate warmer and drier conditions with possible dominance of temperature and number of HD over other ecological factors. These signal the importance of monitoring the changes to the preparedness of mitigating the risk of vector-borne diseases and melanoma.

In the present work, experimental investigations have been done to study the flow turbulence in an alluvial channel with and without seepage. Turbulence is generally depicted as flow randomness or irregularity. The inherent randomness of turbulence in seepage affected channel has been quantified through Kolmogorov complexity (KC) and the Kolmogorov complexity spectrum. The measures have been used in analysis of the velocity time series data of alluvial channel to compare the degree of turbulence with and without seepage. The result concludes that the value of the KC is higher with seepage flow which indicates that higher level of randomness has been observed in seepage flow. Also, the frequency analysis of velocity time series was carried out with the help of Hilbert–Huang transform, which shows that dominant time scale for seepage flow is lower, indicates increased rate of sediment transport. Spectral analysis of velocity time series also suggests more randomness in channel with seepage.

The evolution of daily extreme precipitation from 1966 to 2013 in Vojvodina Region (Serbia) was investigated. We calculated trends of ten precipitation indices and tested their corresponding significances using the Student’s t-test for seven locations. The obtained results suggest that the climate of the northern and central parts of Vojvodina region becomes wetter in terms of precipitation magnitude and frequency, reflecting the characteristic of the central European regime, while the southernmost part of the region is drier, reflecting the characteristic of the Mediterranean regime. In addition, the results indicate an increase in the amount of precipitation in short time intervals. Positive annual trends are strongly influenced by the significant increase of autumn frequency and intensity of extreme precipitation. According to the correlation between extreme precipitation indices and atmospheric teleconnection patterns, it was found that the NAO has the strongest influence on precipitation intensity indices in spring and winter, while during winter it also affects the frequency of dry conditions. The EAWR pattern has a strong influence on the statistically significant positive autumn trends.

Brain complexity and neural oscillations are of vital significance for understanding brain dynamics. Although widely used in the quantification of complex behavior of the brain, standard complexity measures are hampered by some theoretical and implementation issues which limit their applicability to the study of nonlinear brain signals. Further, they have been used for spatial analysis but are insensitive to the temporal structure of data and not applicable to short EEG segments. We demonstrated the ability of a change-based complexity measure (Aksentijevic-Gibson complexity) to analyze neural activity in both spatial and temporal domains. We examined EEG recordings from a group of adolescents with schizophrenia and an age-matched group of healthy controls. AG revealed that the spatial complexity was significantly lower in the patient group across all electrodes with the lowest complexity at the frontal area of the brain. By focusing on outer frontal regions and temporal data averaged over schizophrenia adolescents, we observed periodic drops in complexity and low-delta oscillations at the left electrode F7 and numerous irregularly placed drops at the right side (F8). Periodicity was caused by zero complexity troughs in several individuals associated with large voltage declensions and connected with hypofrontality supporting left frontal pathology. Both averaged spatial and temporal complexities of healthy and schizophrenia adolescents were significantly different from the complexities of random sequences confirming that neural activity is more regular than a true random process. As a final step, we performed the analysis of short EEG segments for the two subjects (one control, one patient) in order to search for differences in neural oscillations. The examination revealed a clear 33 Hz gamma rhythm in a healthy participant and only a fast beta rhythm of 27 Hz in a patient as well as the presence of a full range of rhythms in a healthy EEG and only theta oscillations in that of a patient. The results support the large body of work which associates schizophrenia with lowered complexity, low-frequency rhythms and the scarcity of high-frequency oscillations.

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 &ldquo, flow around&rdquo, 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.

A streamflow time series contains a large quantity of information and finding the instruments that are capable of accessing this information remains an important task. Using the Kolmogorov complexity (KC) and its derivatives, it has previously been shown that the degree of randomness in streamflow partly depends on its orographic characteristics. This paper applied a change-based complexity measure (Aksentijevic-Gibson complexity – AG) to investigate the spatiotemporal regularities of monthly streamflow of seven rivers from Bosnia and Herzegovina for a period of 1965–1986, and evaluate their hydrological effects. A unique advantage of this complexity measure is its ability to quantify large-scale complexity and to zoom in on low-level structure and detect patterns that are normally inaccessible. Ten time series created from the seven rivers were examined and temporal and structural complexity profiles of different streamflows and annual periodicities associated with bimodal/mixed flow regimes were obtained. The AG complexity can be employed as a standard instrument for the analysis of hydrological data and it holds the promise of uncovering patterns and rhythms in the data that cannot be captured by KC and other complexity measures.

Climate change has different manifestations in various regions all over the world. Such changes strongly affect ecosystem services, environmental and agricultural stability. Soils play a crucial role in the complex system that generates climate change. However, the nature and structure of response of different soils to climate change is still distant to be interpreted. Bearing in mind that climate simulations can help us to comprehend soil balance in the future, we defined the purpose of this study: to project temporal and spatial changes of temperature and moisture in four different soils under A1B scenario for the periods 2021–2050 and 2071–2100 with respect to the period 1961–1990. For this analysis climate data obtained by the ECHAM5 model simulations, dynamically downscaled by the coupled regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model), were used. The 43 sites in Vojvodina region (Serbia) were analyzed for pedological parameters and climate elements. The projected changes at the end of 21st century (2071–2100) can be summarized as follows: (i) increase in the mean annual soil temperature up to 3.5 °C in the surface layer 0–10 cm and up to 1.8 °C in average for 0–200 cm depth and decrease in the mean soil moisture up to 0.039 kg kg − 1 in the subsurface layer 40–100 cm and up to 0.019 kg kg − 1 in average for 0–200 cm depth, which corresponds to decrease of 16% and 7%, respectively; (ii) Chernozerms proved to be more sensitive to temperature increase in contrast to water affected soils (Fluvisols, Gleysols and Vertisols) that showed the lowest susceptibility; (iii) Chernozems also showed higher sensitivity to moisture loss than Cambisols, Arenosols and Umbrisols that showed the lowest susceptibility; and (iv) it was assumed that predicted changes in soil temperature and moisture will cause significant changes in soil respiration, release of CO 2 , soil processes, agriculture, biodiversity and ecosystem functioning.

The purpose of this paper was to choose an appropriate information dissimilarity measure for hierarchical clustering of daily streamflow discharge data, from twelve gauging stations on the Brazos River in Texas (USA), for the period 1989&ndash, 2016. For that purpose, we selected and compared the average-linkage clustering hierarchical algorithm based on the compression-based dissimilarity measure (NCD), permutation distribution dissimilarity measure (PDDM), and Kolmogorov distance (KD). The algorithm was also compared with K-means clustering based on Kolmogorov complexity (KC), the highest value of Kolmogorov complexity spectrum (KCM), and the largest Lyapunov exponent (LLE). Using a dissimilarity matrix based on NCD, PDDM, and KD for daily streamflow, the agglomerative average-linkage hierarchical algorithm was applied. The key findings of this study are that: (i) The KD clustering algorithm is the most suitable among others, (ii) ANOVA analysis shows that there exist highly significant differences between mean values of four clusters, confirming that the choice of the number of clusters was suitably done, and (iii) from the clustering we found that the predictability of streamflow data of the Brazos River given by the Lyapunov time (LT), corrected for randomness by Kolmogorov time (KT) in days, lies in the interval from two to five days.

We considered temporal and spatial variations to the thermal and moisture regimes of the most common RSGs (Reference Soil Groups) in Serbia under the A1B scenario for the 2021–2050 and 2071–2100 periods, with respect to the 1961–1990 period. We utilized dynamically downscaled global climate simulations from the ECHAM5 model using the coupled regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model). We analysed the soil temperature and moisture time series using simple statistics and a Kolmogorov complexity (KC) analysis. The corresponding metrics were calculated for 150 sites. In the future, warmer and drier regimes can be expected for all RSGs in Serbia. The calculated soil temperature and moisture variations include increases in the mean annual soil temperature (up to 3.8 °C) and decreases in the mean annual soil moisture (up to 11.3%). Based on the KC values, the soils in Serbia are classified with respect to climate change impacts as (1) less sensitive (Vertisols, Umbrisols and Dystric Cambisols) or (2) more sensitive (Chernozems, Eutric Cambisols and Planosols).

We examine the threshold of the influence of the tunneling nanotubes (TNTs) on the cell-to-cell communication integrity. A deterministic model is introduced with the Michaelis-Menten dynamics and the intercellular exchange of substance. The influence of TNTs are considered as a functional perturbation of the main communication and treated as the matrix nearness problems. We analyze communication integrity in terms of the \emph{pseudospectra} of the exchange, to find the \emph{distance to instability}. The threshold of TNTs influence is computed for Newman-Gastner and Erd\H{o}s-R\'enyi gap junction (GJ) networks., Comment: 6 pages, 4 figures

With the development of mathematics as well as natural sciences and with the improvement of the human cognitive level, a new discipline dealing with complexity of different and complex natural systems has been recognized. Therefore, several complexity measures have been developed. Complexity measures provided to scientific community new insights into environmental processes that cannot be discovered by the traditional mathematical methods. Spatial distribution of heavy metals and radionuclides (HM&RN further) is formed by acting natural processes as well as human activities. Despite the fact that this distribution plays an important role in environmental processes, it has not been analyzed with deserving attention. The usual way to present the results obtained by some measurements having an objective to describe environmental properties is by creating a map of spatial distributions of some chosen quantities or indices. Attempts to introduce some quantitative measure, which characterizes measured areal distribution (and corresponding map) of physical quantity, cannot be frequently encountered in scientific community. In this paper, we invested an effort to introduce some numerical indices as a new measure which can describe spatial distributions of physical quantity based on the complexity computed by the Lempel–Ziv algorithm (LZA) or Lempel–Ziv complexity (LZC).

Understanding and measuring complexity is one of the emerging fields in physics and science more generally. The original impetus was given by Shannon's information theory which quantifies disorder and uncertainty by means of relative probabilities of different outcomes and arrangements of symbols. Next came Kolmogorov complexity (KC) which defines complexity as the length of the shortest description/algorithm needed to describe a string. Since this measure is non-computable it is calculated approximately by means of the Lempel–Ziv algorithm (LZA). KC has been used widely in different branches of physics and other sciences to provide overall estimates of the randomness of data structures, especially time series. Here, we consider the information measure Aksentijevic–Gibson complexity (AG), which defines complexity as amount of change at all levels of a pattern, and compare its performance with KC. We argue that KC and AG in their current implementations are complementary in that they focus on different aspects of complexity—with the former providing efficient omnibus complexity estimates for long time series in different sciences and the latter precisely indexing data structure and locating regions of complexity change. The complementarity of these two measures was demonstrated on one deterministic (logistic equation), and four measured time series: physical (Rn-222 concentration), hydrological (streamflow), meteorological (atmospheric noise) and economic (yield rate) time series, which in further text will be denoted as logistic, Radon, Rio Brazos, random and Imlek, respectively. In addition, we examine spatial transformations of a famous painting in order to demonstrate the sensitivity of AG complexity to spatial information. Finally, we discuss possible applications of the measure in different areas of science.

Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural intermittency of solar irradiation is mainly triggered by atmospheric turbulent conditions, radiative transfer, optical properties of cloud and aerosol, moisture and atmospheric stability, orographic and thermal forcing, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the period 2011&ndash, 2015, at 32 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use the tools of non-linear dynamics: the intermittency and chaos analysis, the largest Lyapunov exponent, Sample entropy, the Kolmogorov complexity and its derivatives (Kolmogorov complexity spectrum and its highest value), and spatial weighted Kolmogorov complexity combined with Hamming distance to assess complexity and corresponding predictability. Finally, we have clustered the Kolmogorov time (that quantifies the time span beyond which randomness significantly influences predictability) for daily cumulative solar irradiation for all stations. We show that under the record-breaking 2011&ndash, 2012 La Nina event and preceding a very strong El-Nino 2015&ndash, 2016 event, the predictability of daily incident solar energy over La R&eacute, union is affected.

Analysis of daily streamflow variability in space and time is important for water resources planning, development, and management. The natural variability of streamflow is being complicated by anthropogenic influences and climate change, which may introduce additional complexity into streamflow records. To address the complexity in streamflow, daily discharge data recorded during the period 1989–2016 at twelve gauging stations on Brazos River in Texas (USA) were used to derive a set of novel quantitative tools: Kolmogorov complexity (KC) and its derivative-associated measures to assess complexity, and Lyapunov time (LT) to assess predictability. It was found that all daily discharge series exhibited long memory with an increasing down-flow tendency, while the randomness of the series at individual sites could not be definitively concluded. All Kolmogorov complexity measures had relatively small values with the exception of the USGS (United States Geological Survey) 08088610 station at Graford, Texas, which exhibited the highest values of the complexity measures. This finding may be attributed to the elevated effect of human activities at Graford, and proportionally lesser effect at other stations. In addition, complexity tended to decrease downflow, meaning that larger catchments were generally less influenced by anthropogenic activities. The correction on randomness of Lyapunov time (quantifying predictability) was found to be inversely proportional to the Kolmogorov complexity, which strengthened our conclusion regarding the effect of anthropogenic activities, considering that KC and LT were distinct measures, based on rather different techniques.

SUMMARYThe Decision Support System for Agrotechnology Transfer (DSSAT) v. 4·2 crop model was used to estimate climate change impacts on soybean yield in Serbia in simulations for 2030 and 2050 integration periods using three global climate change models (GCMs): the European Centre Hamburg Model (ECHAM), The Hadley Centre Coupled Model (HadCM) and the National Center for Atmospheric Research Parallel Climate Model (NCAR-PCM) under two scenarios from the IPCC Special Report on Emissions Scenarios (IPCC 2001): A1B SRES and A2 SRES. Input data included weather data from a 1971–2000 baseline period from ten weather stations assimilated from the Republic Hydrometeorological Service of Serbia. Output results from the three GCMs under the two scenarios for 2030 and 2050 were statistically downscaled with the ‘Met & Roll’ weather generator for predicted climate conditions. Mechanical and chemical soil properties were collected in the vicinity of weather stations and analysed by the Agency for Environmental Safety in Belgrade. Genetic coefficients, for the soybean maturity group II variety, were slightly modified using the DSSAT-SOYGRO model ones. The results showed a considerable benefit of carbon dioxide fertilization on soybean yield and yield increases at all locations. The greatest estimated yield increases obtained using outputs the HadCM model for 2030 both scenarios; in 2050, however, the A2 scenario resulted in smaller increase in yield at some locations. The highest increase in yield was in the central and eastern parts of Serbia. Analyses of the climate change impacts on irrigation demand showed a great increase in the irrigation demand amount per growing season. The average irrigation demand reached the highest values in the southern and eastern parts of Serbia. Water productivity reached highest values in eastern and central locations, while the minimum is expected in the most southern and northern location. According to all results it can be concluded that soybean will benefit greatly under climate change conditions and that soybean cropping, currently most concentrated in the Vojvodina region in northern Serbia, expanding in the central part and one location in eastern Serbia.

We have used the Kolmogorov complexity (KC) and three suggested complexity measures to describe the complexity of spatial distribution of precipitation in Bosnia and Herzegovina, for the period 1960–1984. In particular, we have examined the monthly precipitation amount time series from 23 stations and then calculated the KC using the Lempel–Ziv Algorithm (LZA), Kolmogorov complexity spectrum (KCS), Kolmogorov complexity spectrum highest value (KCM) and overall Kolmogorov complexity (OKC) values for each time series. Our results indicate that the difference in complexity of spatial distribution of precipitation may be attributed to influence of Adriatic Sea, relief and Pannonian Basin.

The present study focuses on interpretations of the temporal variations and variations between urban locations of sulfur dioxide (SO2), nitrogen dioxide (NO2) and black smoke (BS) during the period 2001-2008 in the Vojvodina Region of Serbia (VR_S). In this study we examined variations of pollutants concentrations during household heating and non-heating seasons and the effect of household heating, traffic, rainfall and wind speed on the air pollution levels of SO2, NO2 and BS in eight locations. The analyses showed that the annual limit values of these pollutants as recommended by the Serbian regulations and recommendations were not exceeded, unlike the daily limits. Higher SO2 concentrations during household heating season in four locations indicate the substantial impact of house­hold heating on air quality. Positive effects of the use of environmentally cleaner fuels were observed in only two locations. The growing impact of traffic on air pollution is shown by the increasing trend of NO2 during both seasons. Calm wind conditions and an absence of rainfall were found to have incremental effects on pollution levels in most locations. [Projekat Ministarstva nauke Republike Srbije, br. III 43007: Studying climate change and its influence on the environment: impacts, adaptation and mitigation i br. III 43002: Biosensing Technolo­gies and Global System for Continuous Research and Integrated Management]

Turbulence is often expressed in terms of either irregular or random fluid flows, without quantification. In this paper, a methodology to evaluate the randomness of the turbulence using measures based on the Kolmogorov complexity (KC) is proposed. This methodology is applied to experimental data from a turbulent flow developing in a laboratory channel with canopy of three different densities. The methodology is even compared with the traditional approach based on classical turbulence statistics.

We considered shifts in the Koppen 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 Koppen 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.

Some issues which are relevant for the recent state in climate modeling have been considered. A detailed overview of literature related to this subject is given. The concept in modeling of climate, as a complex system, seen through Godel's Theorem and Rosen's definition of complexity and predictability is discussed. It is pointed out to occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form. A coupled system of equations, often used in climate models is analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this systems. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, is analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameters, the logistic parameter and the parameter of exchange, was studied calculating the Lyapunov exponent under simulations with the closed contour of N=100 environmental interfaces. Finally, we have explored possible differences in complexities of two global and two regional climate models using their output time series by applying the algorithm for calculating the Kolmogorov complexity., Comment: 21 pages, 6 figures, 1 table; This paper has been submitted to Advances in Meteorology

We have considered the complexity and asymptotic stability in the process of biochemical substance exchange in a coupled ring of cells. We have used coupled maps to model this process. It includes the coupling parameter, cell affinity and environmental factor as master parameters of the model. We have introduced: (i) the Kolmogorov complexity spectrum and (ii) the Kolmogorov complexity spectrum highest value to analyze the dynamics of two cell model. The asymptotic stability of this dynamical system using an eigenvalue-based method has been considered. Using these complexity measures we have noticed an 'island' of low complexity in the space of the master parameters for the weak coupling. We have explored how stability of the equilibrium of the biochemical substance exchange in a multi-cell system (N=100) is influenced by the changes in the master parameters of the model for the weak and strong coupling. We have found that in highly chaotic conditions there exists space of master parameters for which the process of biochemical substance exchange in a coupled ring of cells is stable., Comment: 17 pages, 8 figures; This paper has been submitted to Chaos, Solitons and Fractals

Mining activities have the potential to cause excess scour and affect the streambed stability around bridge piers present in the vicinity. Randomness characteristics of turbulence around the pier in a mining infested channel can be helpful in better understanding of this phenomenon. In this study, the effect of a mining pit on the randomness in turbulent flow around the pier has been explored on the basis of Kolmogorov complexity (KC) measure and its derivative, i.e. KC spectrum. Conventionally, turbulent stresses are supposed to govern the sediment transport characteristics, hence the Reynolds shear stresses (RSS) and bursting events are also analyzed. Results of two cases have been comparatively studied; for the first case, only an oblong pier is embedded in the channel while in the second case, a rectangular mining pit is excavated upstream of the pier. Quadrant analysis of the Reynolds shear stress revealed that strong ejection events in the upstream side and inward interaction events in the downstream side of the pier cause excess momentum transport in presence of a mining pit. Streamwise and vertical turbulence intensities also increase by 20% and 33% respectively in the down-flow zone in front of the pier. KC value of turbulence around the pier, especially in the down-flow zone and separation zone is found to be 10% and 12% higher due to pit excavation. Comparing the KC spectra for both cases suggests that dredging of a pit in the channel increases the degree of randomness of higher velocity scales around the bridge pier. These alterations in turbulent stresses and randomness characteristics can be helpful in explaining the streambed scour and undermining of bridge piers due to mining activities.

[1] The radiation transfer within the forest canopy plays crucial role in energy balance and turbulent transfer processes. Objective of this study is to suggest a new relation for vertical profile of photosynthetically active radiation (PAR) in case of horizontally uniform forest canopy. It is based on (i) the Lambert-Beer law relationship and (ii) new parameterization of leaf area density (LAD) profile. We have supposed that absorption coefficient μ varies with height and depends on LAD distribution. To check validity of the relation proposed, we have compared calculated values with the observations using data sets assimilated during Anglo-Brazilian Amazonian Climate Observation Study experiment at two observational sites located in Reserva Jaru and Reserva Ducke (Brazil) with different types of forest. Among all available measurements, 615 profiles observed between 08 and 18 local mean time for 72 days at 2 locations were selected. For comparison study, two more profiles based on constant- and variable-LAD approximation were introduced. Obtained results indicate that suggested relation: (i) well reproduces PAR profile within the forest in comparison with observations and (ii) shows better agreement with observations in comparison with two other profiles used in this study.

The results of the Sun’s UV radiation and stratospheric ozone layer thickness over the region of Novi Sad (Serbia) are reported. Monitoring the UV radiation and stratospheric ozone layer thickness started in 2003 and 2007 respectively. Results recorded during these years have been analyzed. Upon these analyses it can be concluded that during observational period, the significant difference in daily maxima of the UV radiation recordings or ozone seasonal maximal values from year to year, has not been detected. Obtained results are graphically depicted.

The parameterization of physical processes over the heterogeneous environmental interfaces has become one of the basic tasks in environmental modeling from large to small scales. Previously introduced new approach for calculating the aggregated albedo of the heterogeneous grid cell with regions of different heights is analyzed in the case of different geometries (“rectangular prism,” “trilateral prism,” “slope” and “canyon”) in a grid cell commonly met in the environmental models. In order to determine the loss coefficient, relative flux that is lost due to the absorption on the vertical lateral boundaries of the patches lying on a higher level, rather complex analytical expression for this flux is derived wherever it was possible. For the situations when the analytical solution for the loss coefficient is not accessible, the Monte Carlo ray tracing (MCRT) method is highly efficient approach for calculating the aggregated albedo. Finally, the differences in albedo obtained in a conventional way and by the MCRT method were emphasized by the calculation of the effective surface temperature of the grid cell, for all considered geometries, using the land surface scheme LAPS. In all cases the temperature obtained by present method is higher.

Many physical, biological as well as the environmental problems, can be described by the dynamics of driven coupled oscillators. In order to study their behaviour as a function of coupling strength and nonlinearity, we considered dynamics of two maps serving the combined coupling (diffusive and linear) in the above fields. Firstly, we have considered a logistic difference equation on extended domain that is a part of the maps, that is discussed using its bifurcation diagram, Lyapunov exponent, sample as well as the permutation entropy. Secondly we have performed the dynamical analysis of the coupled maps using Lyapunov exponent and cross sample entropy in dependence on two coupling parameters. Further, we investigated how dynamical noise can affects the structure of their bifurcation diagrams. It was done (i) by the noise entering in two specific ways, that disturbs either the logistic parameter on extended domain or (ii) by an additive “shock” to the state variables. Finally, we demonstrated the effect of forcing by parametric noise, introduced in all maps’ parameter, on Lyapunov exponent of coupled maps.

In this paper some of aspects in modeling over sparse vegetation using the Land-Air Parameterization Scheme (LAPS), including an approach in calculating the turbulent transfer coefficient using “K-theory” inside a sparse vegetation canopy, were considered. For this purpose, the scheme was run for different sparse agricultural cultivars, i.e., apple orchard, winter wheat and soybean crops, at different sites. The modeled values for surface fluxes, canopy temperature and soil moisture content, were compared with observations. [Projekat Ministarstva nauke Republike Srbije, br. 43007: Studying climate change and its influence on the environment: Impacts, adaptation and mitigation]

We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tools for its modelling. We have suggested two coupled maps serving the exchange processes on the environmental interfaces spatially ranged from cellular to planetary level, i.e. 1) the map with diffusive coupling for energy exchange simulation and 2) the map with affinity, which is suitable for matter exchange processes at the cellular level. We have performed the dynamical analysis of the coupled maps using the Lyapunov exponent, cross sample as well as the permutation entropy in dependence on different map parameters. Finally, we discussed the map with affinity, which shows some features making it a promising toll in simulation of exchange processes on the environmental interface at the cellular level.

Possibility of using pure Lagrangian approach in modeling transport phenomena is described in this paper. The application of pure Lagrangian approach in real atmospheric field induces highly irregular spatial distribution of grid points, after only a few time steps. In order to avoid problems caused by that irregularity, a quasi interpolation procedure is proposed. Proposed interpolation procedure is similar to the radial basis functions interpolation and does not impose any demands about spatial distribution of the grid points or about continuity and differentiability of the field that needs to be interpolated. Besides that, proposed procedure is explicitly mass conserving. Combination of particle mesh method and pure Lagrangian approach creates efficient transport scheme that does not produce any new local maxima and minima in advected field. In proposed advection scheme motion of points are performed in Lagrangian manner while spatial derivatives are evaluated on the basis of values interpolated onto regular grid. Applicability of proposed advection scheme in an unambiguous way is proved by performing “standard” numerical tests with (i) the slotted cylinder under solid body rotation, (ii) the test with Doswell’s idealized cyclogenesis as well as (iii) integration of shallow water equations.

Numerical simulations and tests with the recently redesigned land–air parameterization scheme (LAPS) are presented. In all experiments, supported either by one-point micrometeorological, 1D or 3D simulations, the attention has been directed to: (1) comparison of simulation outputs, expressing the energy transfer over and through heterogeneous and non-heterogeneous surfaces, versus observations and (2) analysis of uncertainties occurring in the solution of the energy balance equation at the land–air interface. To check the proposed method for aggregation of albedo, “propagating hole” sensitivity tests with LAPS over a sandstone rock grid cell have been performed with the forcing meteorological data for July 17, 1999 in Baxter site, Philadelphia (USA). Micrometeorological and biophysical measurements from the surface experiments conducted over crops and apple orchard in Serbia, Poland, Austria and France were used to test the operation of LAPS in calculating surface fluxes and canopy environment temperatures within and above plant covers of different densities. In addition, sensitivity tests with single canopy covers over the Central Europe region and comparison against the observations taken from SYNOP data using 3D simulations were made. Validation of LAPS performances over a solid surface has been done by comparison of 2 m air temperature observations against 5-day simulations over the Sahara Desert rocky ground using 3D model. To examine how realistically the LAPS simulates surface processes over a heterogeneous surface, we compared the air temperature measured at 2 m and that predicted by the 1D model with the LAPS as the surface scheme. Finally, the scheme behaviour over urban surface was tested by runs over different parts of a hypothetical urban area. The corresponding 1D simulations were carried out with an imposed meteorological dataset collected during HAPEX-MOBILHY experiment at Caumont (France). The quantities predicted by the LAPS compare well with the observations and the various subcomponents of the scheme appear to operate realistically.

Asymmetrical convective non-local scheme (CON) with varying upward mixing rates is developed for simulation of vertical turbulent mixing in the convective boundary layer in air quality and chemical transport models.The upward mixing rate form the surface layer is parameterized using the sensible heat flux and the friction and convective velocities. Upward mixing rates varying with height are scaled with an amount of turbulent kinetic energy in layer, while the downward mixing rates are derived from mass conservation.This scheme provides a less rapid mass transport out of surface layer into other layers than other asymmetrical convective mixing schemes.In this paper, we studied the performance of a nonlocal convective mixing scheme with varying upward mixing in the atmospheric boundary layer and its impact on the concentration of pollutants calculated with chemical and air-quality models. This scheme was additionally compared versus a local eddy-diffusivity scheme (KSC). Simulated concentrations of NO(2) and the nitrate wet deposition by the CON scheme are closer to the observations when compared to those obtained from using the KSC scheme.Concentrations calculated with the CON scheme are in general higher and closer to the observations than those obtained by the KSC scheme (of the order of 15-20%). Nitrate wet deposition calculated with the CON scheme are in general higher and closer to the observations than those obtained by the KSC scheme.To examine the performance of the scheme, simulated and measured concentrations of a pollutant (NO(2)) and nitrate wet deposition was compared for the year 2002. The comparison was made for the whole domain used in simulations performed by the chemical European Monitoring and Evaluation Programme Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.

In this paper, we studied the performance of a local and non-local scheme for vertical diffusion in the atmospheric boundary layer and their impact on the concentration of pollutants calculated with chemical and air-quality models. In the local diffusion scheme, the vertical eddy-diffusivity is determined independently at each point based on local vertical gradients of wind and potential temperature. The non-local scheme determines an eddy-diffusivity profile based on a diagnosed boundary layer height and a turbulent vertical scale. Depending on the boundary layer stability regime, a modification was introduced into the non-local scheme to facilitate different values of the parameter in the equation for eddy-diffusivity. To examine the performance of the schemes, simulated and measured concentrations of a pollutant (NO"2), believed to be one of the most affected ones by the processes in the atmospheric boundary layer, were compared for the years 1999, 2001 and 2002. The comparison was made for the whole domain used in simulations performed by the chemical EMEP Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.

A model for calculating the crop environment temperatures (soil surface temperature, crop air space temperature and crop foliage temperature) for ecological modelling is presented. The crop foliage temperature and soil surface temperatures are calculated numerically from the system of two equations that represent the partitioning of energy over the crop canopy and its bare fraction. The crop air space temperature is determined diagnostically from the equality of the canopy's sensible heat flux to some reference level in the atmosphere and the sum of sensible heat flux from the soil surface and from the leaves to the canopy air volume. Parameterization of terms included in the equations provides a reliability in prediction of crop environment temperatures, particularly in the case of the sparsely distributed crop. The model is described through detailed consideration of: (1) calculations of turbulent fluxes, (2) the shape of the wind and turbulent transfer coefficient profiles, and (3) calculation of the aerodynamic resistances inside crop canopies. The proposed model is assessed using data measured in soybean, maize and sunflower canopies. Model outputs of crop environment temperatures are compared with micrometeorological measurements in soybean, sunflower and maize fields.

We have used the Kolmogorov complexities and the Kolmogorov complexity spectrum to quantify the randomness degree in river flow time series of seven rivers with different regimes in Bosnia and Herzegovina, representing their different type of courses, for the period 1965–1986. In particular, we have examined: (i) the Neretva, Bosnia and the Drina (mountain and lowland parts), (ii) the Miljacka and the Una (mountain part) and the Vrbas and the Ukrina (lowland part) and then calculated the Kolmogorov complexity (KC) based on the Lempel–Ziv Algorithm (LZA) (lower—KCL and upper—KCU), Kolmogorov complexity spectrum highest value (KCM) and overall Kolmogorov complexity (KCO) values for each time series. The results indicate that the KCL, KCU, KCM and KCO values in seven rivers show some similarities regardless of the amplitude differences in their monthly flow rates. The KCL, KCU and KCM complexities as information measures do not “see” a difference between time series which have different amplitude variations but similar random components. However, it seems that the KCO information measures better takes into account both the amplitude and the place of the components in a time series.

This paper focuses on the development and application of a technique for filling the daily erythemal UV dose data gaps and the reconstruction of the past daily erythemal UV doses in Novi Sad, Serbia. The technique implies developing the empirical equation for estimation of daily erythemal UV doses by means of relative daily sunshine duration under all sky conditions. A good agreement was found between modeled and measured values of erythemal UV doses. This technique was used for filling the short gaps in the erythemal UV dose measurement series (2003–2009) as well as for the reconstruction of the past time-series values (1981–2002). Statistically significant positive erythemal UV dose trend of 6.9 J m−2 per year was found during the period 1981–2009. In relation to the reference period 1981–1989, an increase in the erythemal UV dose of 6.92 % is visible in the period 1990– 1999 and the increase of 9.67 % can be seen in the period 2000–2009. The strongest increase in erythemal UV doses has been found for winter and spring seasons.

In this paper, we have analyzed the time series of daily values for three meteorological elements, two continuous and a discontinuous one, i.e., the maximum and minimum air temperature and the precipitation. The analysis was done based on the observations from seven stations in Serbia from the period 1951–2010. The main aim of this paper was to quantify the complexity of the annual values for the mentioned time series and to calculate the rate of its change. For that purpose, we have used the sample entropy and the Kolmogorov complexity as the measures which can indicate the variability and irregularity of a given time series. Results obtained show that the maximum temperature has increasing trends in the given period which points out a warming, ranged in the interval 1–2 °C. The increasing temperature indicates the higher internal energy of the atmosphere, changing the weather patterns, manifested in the time series. The Kolmogorov complexity of the maximum temperature time series has statistically significant increasing trends, while the sample entropy has increasing but statistically insignificant trend. The trends of complexity measures for the minimum temperature depend on the location. Both complexity measures for the precipitation time series have decreasing trends.