Influence of mass diffusion in sea ice dynamical models

The mixing of floes of different thickness caused by repeated deformation of the ice cover is modeled as diffusion, and the mass balance equation for sea ice accounting for mass diffusion is developed. The effect of deformational diffusion on the ice thickness balance is shown to reach 1% of the divergence effect, which describes ridging and lead formation. This means that with the same accuracy the mass balance equation can be written in terms of mean velocity rather than mean mass-weighted velocity, which one should correctly use for a multicomponent fluid such as sea ice with components identified by floe thickness. Mixing (diffusion) of sea ice also occurs because of turbulent variations in wind and ocean drags that are unresolved in models. Estimates of the importance of turbulent mass diffusion on the dynamic redistribution of ice thickness are determined using empirical data for the turbulent diffusivity. For long-time-scale prediction (≫5 days), where unresolved atmospheric motion may have a length scale on the order of the Arctic basin and the time scale is larger than the synoptic time scale of atmospheric events, turbulent mass diffusion can exceed 10% of the divergence effect. However, for short-time-scale prediction, for example, 5 days, the unresolved scales are on the order of 100 km, and turbulent diffusion is about 0.1% of the divergence effect. Because inertial effects are small in the dynamics of the sea ice pack, diffusive momentum transfer can be disregarded.

The diffusion of grassroots innovations for sustainability in Italy and Great Britain: an exploratory spatial data analysis

Little research so far has been devoted to understanding the diffusion of grassroots innovation for sustainability across space. This paper explores and compares the spatial diffusion of two networks of grassroots innovations, the Transition Towns Network (TTN) and Gruppi di Acquisto Solidale (Solidarity Purchasing Groups – GAS), in Great Britain and Italy. Spatio-temporal diffusion data were mined from available datasets, and patterns of diffusion were uncovered through an exploratory data analysis. The analysis shows that GAS and TTN diffusion in Italy and Great Britain is spatially structured, and that the spatial structure has changed over time. TTN has diffused differently in Great Britain and Italy, while GAS and TTN have diffused similarly in central Italy. The uneven diffusion of these grassroots networks on the one hand challenges current narratives on the momentum of grassroots innovations, but on the other highlights important issues in the geography of grassroots innovations for sustainability, such as cross-movement transfers and collaborations, institutional thickness, and interplay of different proximities in grassroots innovation diffusion.

Pesticides and other micro-organic contaminants in freshwater sedimentary environments - a review

A wide range of issues relating to the presence and fate of pesticides and other micro-organic contaminants (MOCs) in surface freshwater sedimentary environments is reviewed. These issues include the sources, transport and occurrence of MOCs in freshwater environments; their ecological effects; their interaction with sedimentary material; and a range of processes related to their fate, including degradation, diffusion in bed sediments, bioturbation and slow contaminant release. An emphasis is placed on those processes-chemical, physical or biological-in which sediments play a role in determining the fate of micro-organics in freshwater environments. The issues of occurrence, source and transport, and the ecological effects of micro-organics are introduced more briefly, the focus where these aspects are concerned being largely on pesticides. In the concluding section, key points and issues relating to the study of micro-organics in freshwater environments are summarised and areas where initial or further research would be welcome are highlighted. It is hoped that this paper will both form a useful reference for workers in the field of micro-organic contaminants, and also stimulate new work in the freshwater environment and beyond. (C) 2003 Elsevier Science Ltd. All rights reserved.

The effect of aqueous diffusion on the fractionation of chlorine and bromine stable isotopes

Diffusive isotopic fractionation factors are important in order to understand natural processes and have practical application in radioactive waste storage and carbon dioxide sequestration. We determined the isotope fractionation factors and the effective diffusion coefficients of chloride and bromide ions during aqueous diffusion in polyacrylamide gel. Diffusion was determined as functions of temperature, time and concentration. The effect of temperature is relatively large on the diffusion coefficient (D) but only small on isotope fractionation. For chlorine, the ratio, D-35cl/D-37cl varied from 1.00128 +/- 0.00017 (1 sigma) at 2 degrees C to 1.00192 +/- 0.00015 at 80 degrees C. For bromine, D-79Br/D-81Br varied from 1.00098 +/- 0.00009 at 2 degrees C to 1.0064 +/- 0.00013 at 21 degrees C and 1.00078 +/- 0.00018 (1 sigma) at 80 degrees C. There were no significant effects on the isotope fractionation due to concentration. The lack of sensitivity of the diffusive isotope fractionation to anything at the most common temperatures (0 to 30 C) makes it particularly valuable for application to understanding processes in geological environments and an important natural tracer in order to understand fluid transport processes. (C) 2009 Elsevier Ltd. All rights reserved.

Pesticides and other micro-organic contaminants in freshwater sedimentary environments - a review

A wide range of issues relating to the presence and fate of pesticides and other micro-organic contaminants (MOCs) in surface freshwater sedimentary environments is reviewed. These issues include the sources, transport and occurrence of MOCs in freshwater environments; their ecological effects; their interaction with sedimentary material; and a range of processes related to their fate, including degradation, diffusion in bed sediments, bioturbation and slow contaminant release. An emphasis is placed on those processes-chemical, physical or biological-in which sediments play a role in determining the fate of micro-organics in freshwater environments. The issues of occurrence, source and transport, and the ecological effects of micro-organics are introduced more briefly, the focus where these aspects are concerned being largely on pesticides. In the concluding section, key points and issues relating to the study of micro-organics in freshwater environments are summarised and areas where initial or further research would be welcome are highlighted. It is hoped that this paper will both form a useful reference for workers in the field of micro-organic contaminants, and also stimulate new work in the freshwater environment and beyond. (C) 2003 Elsevier Science Ltd. All rights reserved.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Surface and interstitial Ti diffusion at the rutile TiO2(110) surface

Diffusion of Ti through the TiO2 (110) rutile surface plays a key role in the growth and reactivity of TiO2. To understand the fundamental aspects of this important process, we present an analysis of the diffusion of Ti adspecies at the stoichiometric TiO2(110) surface using complementary computational methodologies of density functional theory corrected for on-site Coulomb interactions (DFT+U) and a charge equilibration (QEq) atomistic potential to identify minimum energy pathways. We find that diffusion of Ti from the surface to subsurface (and vice versa) follows an intersticialcy exchange mechanism, involving exchange of surface Ti with the 6-fold coordinated Ti below the bridging oxygen rows. Diffusion in the subsurface between layers also follows an interstitialcy mechanism. The diffusion of Ti is discussed in light of continued attempts to understand the re-oxidation of non-stoichiometric TiO2(110) surfaces.

Suspended and bed load sediment transport dynamics in two lowland UK streams—storm integrated monitoring

A great deal of work recently has focused on suspended and bedload sediment transport, driven primarily by interest in contaminant transfer. However, uncertainties regarding the role of storm events, macrophyte beds and interactions between the two phases of sediment still exist. This paper compares two study sites within the same catchment whose geology varies significantly. The differences in hydrology, suspended sediment (SS) transport and bed load transport that this causes are examined. In addition, a method to predict the mobilization of different size fractions of sediment during given flows is investigated using critical entrainment thresholds.

Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

A traceable physical calibration of the vertical advection-diffusion equation for modelling ocean heat uptake

The classic vertical advection-diffusion (VAD) balance is a central concept in studying the ocean heat budget, in particular in simple climate models (SCMs). Here we present a new framework to calibrate the parameters of the VAD equation to the vertical ocean heat balance of two fully-coupled climate models that is traceable to the models’ circulation as well as to vertical mixing and diffusion processes. Based on temperature diagnostics, we derive an effective vertical velocity w∗ and turbulent diffusivity k∗ for each individual physical process. In steady-state, we find that the residual vertical velocity and diffusivity change sign in mid-depth, highlighting the different regional contributions of isopycnal and diapycnal diffusion in balancing the models’ residual advection and vertical mixing. We quantify the impacts of the time-evolution of the effective quantities under a transient 1%CO2 simulation and make the link to the parameters of currently employed SCMs.

Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins

Providing probabilistic forecasts using Ensemble Prediction Systems has become increasingly popular in both the meteorological and hydrological communities. Compared to conventional deterministic forecasts, probabilistic forecasts may provide more reliable forecasts of a few hours to a number of days ahead, and hence are regarded as better tools for taking uncertainties into consideration and hedging against weather risks. It is essential to evaluate performance of raw ensemble forecasts and their potential values in forecasting extreme hydro-meteorological events. This study evaluates ECMWF’s medium-range ensemble forecasts of precipitation over the period 2008/01/01-2012/09/30 on a selected mid-latitude large scale river basin, the Huai river basin (ca. 270,000 km2) in central-east China. The evaluation unit is sub-basin in order to consider forecast performance in a hydrologically relevant way. The study finds that forecast performance varies with sub-basin properties, between flooding and non-flooding seasons, and with the forecast properties of aggregated time steps and lead times. Although the study does not evaluate any hydrological applications of the ensemble precipitation forecasts, its results have direct implications in hydrological forecasts should these ensemble precipitation forecasts be employed in hydrology.

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.