Effect of bed surface roughness on longitudinal dispersion in artificial open channels

In several empirical and modelling studies on river hydraulics, dispersion was negatively correlated to surface roughness. In this study, it was aimed to investigate the influence of surface roughness on longitudinal dispersion under controlled conditions. In artificial flow channels with a length of 104 m, tracer experiments with variations in channel bed material were performed. By use of measured tracer breakthrough curves, average flow velocity, mean longitudinal dispersion, and mean longitudinal dispersivity were calculated. Longitudinal dispersion coefficients ranged from 0·018 m² s^?1 in channels with smooth bed surface up to 0·209 m² s^?1 in channels with coarse gravel as bed material. Longitudinal dispersion was linearly related to mean flow velocity. Accordingly, longitudinal dispersivities ranged between 0·152 ± 0·017 m in channels with smooth bed surface and 0·584 ± 0·015 m in identical channels with a coarse gravel substrate. Grain size and surface roughness of the channel bed were found to correlate positively to longitudinal dispersion. This finding contradicts several existing relations between surface roughness and dispersion. Future studies should include further variation in surface roughness to derive a better‐founded empirical equation forecasting longitudinal dispersion from surface roughness. Copyright © 2011 John Wiley & Sons, Ltd.     

Tropical precipitation anomalies and d‐excess evolution during El Niño 2014‐16

The last 2014‐16 El Niño event was among the three strongest episodes on record. El Niño considerably changes annual and seasonal precipitation across the tropics. Here, we present a unique stable isotope data set of daily precipitation collected in Costa Rica prior to, during, and after El Niño 2014‐16, in combination with Lagrangian moisture source and precipitation anomaly diagnostics. δ²H composition ranged from ‐129.4 to +18.1 (‰) while δ¹⁸O ranged from ‐17.3 to +1.0 (‰). No significant difference was observed among δ¹⁸O (P=0.186) and δ²H (P=0.664) mean annual compositions. However, mean annual d‐excess showed a significant decreasing trend (from +13.3 to +8.7 ‰) (P<0.001) with values ranging from +26.6 to ‐13.9 ‰ prior to and during the El Niño evolution. The latter decrease in d‐excess can be partly explained by an enhanced moisture flux convergence across the southeastern Caribbean Sea coupled with moisture transport from northern South America by means of an increased Caribbean Low Level Jet regime. During 2014‐15, precipitation deficit across the Pacific domain averaged 46% resulting in a very severe drought; while a 94% precipitation surplus was observed in the Caribbean domain. Understanding these regional moisture transport mechanisms during a strong El Niño event may contribute to a) better understanding of precipitation anomalies in the tropics and b) re‐evaluate past stable isotope interpretations of ENSO events in paleoclimatic archives within the Central America region.     

Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models

Ozone is one of the most significant secondary pollutants with numerous negative effects on human health and environment including plants and vegetation. Therefore, more effort is made recently by governments and associations to predict ozone concentrations which could help in establishing better plans and regulation for environment protection. In this study, we use two Artificial Neural Network based approaches (MPL and RBF) to develop, for the first time, accurate ozone prediction models, one for urban and another one for rural area in the eastern part of Croatia. The evaluation of actual against the predicted ozone concentrations revealed that MLP and RBF models are very competitive for the training and testing data in the case of Kopa?ki Rit area whereas in the case of Osijek city, MLP shows better evaluation results with 9% improvement in the correlation coefficient. Furthermore, subsequent feature selection process has improved the prediction power of RBF network.     

Convective and stratiform precipitation characteristics in an ensemble of regional climate model simulations

We apply a recently proposed algorithm for disaggregating observed precipitation data into predominantly convective and stratiform, and evaluate biases in characteristics of parameterized convective (subgrid) and stratiform (large-scale) precipitation in an ensemble of 11 RCM simulations for recent climate in Central Europe. All RCMs have a resolution of 25 km and are driven by the ERA-40 reanalysis. We focus on mean annual cycle, proportion of convective precipitation, dependence on altitude, and extremes. The results show that characteristics of total precipitation are often better simulated than are those of convective and stratiform precipitation evaluated separately. While annual cycles of convective and stratiform precipitation are reproduced reasonably well in most RCMs, some of them consistently and substantially overestimate or underestimate the proportion of convective precipitation throughout the year. Intensity of convective precipitation is underestimated in all RCMs. Dependence on altitude is also simulated better for stratiform and total precipitation than for convective precipitation, for which several RCMs produce unrealistic slopes. Extremes are underestimated for convective precipitation while they tend to be slightly overestimated for stratiform precipitation, thus resulting in a relatively good reproduction of extremes in total precipitation amounts. The results suggest that the examined ensemble of RCMs suffers from substantial deficiencies in reproducing precipitation processes and support previous findings that climate models’ errors in precipitation characteristics are mainly related to deficiencies in the representation of convection.     

Identification of Greigite in the Pliocene Sediments of Qinghai Lake and Its Geological Significance

正Objective The Qinghai Lake in North China is the largest interior plateau lake in Central Asia,and is sensitive to climate change and the environmental effects of Tibetan Plateau uplift.An almost continuous 626 m long sediment core was drilled in an in-filled part of the southern lake basin in the Scientific Drilling at Qinghai Lake.Previous