On some new statistical characteristics of the wind “Koshava”

Summary Koshava is a gusty wind of moderate to strong intensity, blowing from the south-eastern direction, over the area of the Republic of Serbia. It is caused by the interaction between the synoptic circulation and the orography of the Carpathian and the Balkan mountains. The Koshava wind can damage buildings, factories and industrial plants or city infrastructure. Therefore it is important to estimate its gust and the gustiness factor on the basis of the measured data.This paper discusses a statistical analysis of wind data in the maximum influence area of the Koshava wind in the periods of maximum duration of Koshava. The focus of the paper is the examination of urban and suburban effects on Koshava wind and the correlation between the instantaneous maximum wind speed and the hourly mean wind speed. The best fitting with various empirical distributions is proposed.With 10 Figures     

Aqueous Oxidation of Sulfur(IV) Catalyzed by Manganese(II): A Generalized Simple Kinetic Model

The reaction kinetics of S(IV) autoxidation catalyzed by Mn(II) in the pH range 3–5 typical for atmospheric liquid water, was investigated. For reactions with pH maintained constant during the reaction course, the predictions obtained by a simple integral approach cover kinetic results only for concentrations of HSO ₃ ⁻ up to 0.2 mM at pH 4.5. Thus, a generalized simple kinetic model, which can be used for predicting the reaction kinetics in wider concentration, pH and temperature ranges, was derived. This model is based on the assumption that the reaction rate is proportional to the concentration of a transient manganese-sulfito complex formed in the initial step of a radical chain mechanism. In the proposed power law rate equation

The influence of raw domestic sewage on density and distribution of meiofauna

The influence of raw domestic sewage on density and distribution of meiofauna in the sea bottom sediments in the Northern Adriatic Sea, in the area of Rovinj (Yugoslavia), was investigated, comparing meiofaunal density at the stations which are under direct influence of sewage and the stations which are far from the source of pollution. It is concluded that raw domestic sewage does not have a negative influence on the density and distribution of meiofauna, but Parker's index of pollution indicates that meiofauna at these stations were under stress.     

Modeling compositional compressible two-phase flow in porous media by the concept of the global pressure

We derive a new formulation for the compositional compressible two-phase flow in porous media. We consider a liquid–gas system with two components: water and hydrogen. The formulation considers gravity, capillary effects, and diffusivity of each component. The main feature of this formulation is the introduction of the global pressure variable that partially decouples the system equations. To formulate the final system, and in order to avoid primary unknowns changing between one-phase and two-phase zones, a second persistent variable is introduced: the total hydrogen mass density. The derived system is written in terms of the global pressure and the total hydrogen mass density. The system is capable of modeling the flows in both one and two-phase zones with no changes of the primary unknowns. The mathematical structure is well defined: the system consists of two nonlinear parabolic equations, the global pressure equation, and the total hydrogen mass density equation. The derived formulation is fully equivalent to the original one. Numerical simulations show ability of this new formulation to model efficiently the phase appearance and disappearance.     

Dependence of accumulated precipitation on cloud drop size distribution

Convective precipitation is the main cause of extreme rainfall events in small areas. Its primary characteristics are both large spatial and temporal variability. For this reason, the monitoring of accumulated precipitation fields (liquid and solid components) at the surface is difficult to carry out through the use of rain gauge networks or remote-sensing observations. Alternatively, numerical models seem to be the most powerful tool in simulating convective precipitation for various analyses and predictions. Due to a lack of comparisons between modelled and observed precipitation characteristics over a long period of time, we focus our research on comparisons between observations and three model samples of accumulated convective precipitation over a particular study area. We use a numerical cloud model with two model schemes involving the unified Khrgian–Mazin size distribution of cloud drops and a model scheme involving a monodisperse cloud droplet spectrum and the Marshall–Palmer size distribution for raindrops, respectively. For comparison, we have selected a study area with a sounding site. Our analysis shows that the model version with the Khrgian–Mazin size distribution exhibits a better agreement with the observed mean, median and range of extreme values of accumulated convective precipitation. Model simulations with the Khrgian–Mazin size distribution most closely match observations, with a correlation coefficient of 0.91. Use of the Marshall–Palmer size distribution, on the other hand, systemically underestimates the observed precipitation and has the lowest correlation coefficient among the methods, 0.83. Such an investigation is crucial to improve predictions of accumulated convective precipitation for various climatological and hydrological analyses and predictions.     

Eta model forecasts of tropical cyclones from Australian Monsoon Experiment: The model sensitivity

Summary The Australian Monsoon Experiment (AMEX) (10 January through 15 February 1987) has resulted in the first ever quality mesoscale data set in the Australian tropics. This provides the first observational confirmation of previous hypotheses, modelling experiments and refinement of the parametrization of convective processes. During the AMEX a large area of convective activity off northwestern Australia accompanied four tropical cyclones onset:Connie, Irma, Damien andJason. As already reported by the author, the Eta Model of the University of Belgrade and the National Meteorological Centre, Washington (UB/NMC), successfully predicted the development, structure, associated precipitation and tracks of these cyclones.Using again the AMEX tropical cyclone cases, in the present study the sensitivity of the Eta Model is examined with respect to the initial and boundary conditions, the vertical coordinate and orography, the location of the initial vortex, the surface fluxes of heat and moisture, the sea surface temperature and the Betts-Miller convection parametrization scheme.Also, some available forecasts of the AMEX tropical cyclones were intercompared. These included the forecasts obtained by the Eta Model, the T106 global (then) operational European Centre for Medium-range Weather Forecasts (ECMWF) model, the ECMWF T106 limited area model and the Florida State University (FSU) limited area model. A review of the intercomparison results suggests that the Eta Model is highly competitive with the other sophisticated models, both in terms of quality and the computational effort required.With 9 Figures     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

The impact of boundary forcing on RegCM4.2 surface energy budget

The surface energy budget components from two simulations of the regional climate model RegCM4.2 over the European/North African domain during the period 1989–2005 are analysed. The simulations differ in specified boundary forcings which were obtained from ERA-Interim reanalysis and the HadGEM2-ES Earth system model. Surface radiative and turbulent fluxes are compared against ERA-Interim. Errors in surface radiative fluxes are derived with respect to the Global Energy and Water Cycle Experiment/Surface Radiation Budget satellite-based products. In both space and time, we find a high degree of realism in the RegCM surface energy budget components, but some substantial errors and differences between the two simulations are also present. The most prominent error is an overestimation of the net surface shortwave radiation flux of more than 50 W/m² over central and southeastern Europe during summer months. This error strongly correlates with errors in the representation of total cloud cover, and less strongly with errors in surface albedo. During other seasons, the amplitude of the surface energy budget components is more in line with reference datasets. The errors may limit the usefulness of RegCM simulations in applications (e.g. high-quality simulation-driven impact studies). However, by using a simple diagnostic model for error interpretation, we suggest potential sensitivity studies aiming to reduce the underestimation of cloud cover and overestimation of shortwave radiation flux.