EOF analysis of three records of sea-ice concentration spanning the last 30 years

Several continuous observational datasets of Artic sea-ice concentration are currently available that cover the period since the advent of routine satellite observations. We report on a comparison of three sea-ice concentration datasets. These are the National Ice Center charts, and two passive microwave radiometer datasets derived using different approaches: the NASA team and Bootstrap algorithms. Empirical orthogonal function (EOF) analyses were employed to compare modes of variability and their consistency between the datasets. The analysis was motivated by the need for a reliable, realistic sea ice climatology for use in climate model simulations, for which both the variability and absolute values of extent and concentration are important. We found that, while there are significant discrepancies in absolute concentrations, the major modes of variability derived from all records were essentially the same.

Aircraft observations and model simulations of concentration and particle size distribution in the Eyjafjallajökull volcanic ash cloud

The Eyjafjallajökull volcano in Iceland emitted a cloud of ash into the atmosphere during April and May 2010. Over the UK the ash cloud was observed by the FAAM BAe-146 Atmospheric Research Aircraft which was equipped with in-situ probes measuring the concentration of volcanic ash carried by particles of varying sizes. The UK Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME) has been used to simulate the evolution of the ash cloud emitted by the Eyjafjallajökull volcano during the period 4–18 May 2010. In the NAME simulations the processes controlling the evolution of the concentration and particle size distribution include sedimentation and deposition of particles, horizontal dispersion and vertical wind shear. For travel times between 24 and 72 h, a 1/t relationship describes the evolution of the concentration at the centre of the ash cloud and the particle size distribution remains fairly constant. Although NAME does not represent the effects of microphysical processes, it can capture the observed decrease in concentration with travel time in this period. This suggests that, for this eruption, microphysical processes play a small role in determining the evolution of the distal ash cloud. Quantitative comparison with observations shows that NAME can simulate the observed column-integrated mass if around 4% of the total emitted mass is assumed to be transported as far as the UK by small particles (< 30 μm diameter). NAME can also simulate the observed particle size distribution if a distal particle size distribution that contains a large fraction of < 10 μm diameter particles is used, consistent with the idea that phraetomagmatic volcanoes, such as Eyjafjallajökull, emit very fine particles.

Flow synthesis using gaseous ammonia in a Teflon AF-2400 tube-in-tube reactor: Paal–Knorr pyrrole formation and gas concentration measurement by inline flow titration

Using a simple and accessible Teflon AF-2400 based tube-intube reactor, a series of pyrroles were synthesised in flow using the Paal–Knorr reaction of 1,4-diketones with gaseous ammonia. An inline flow titration technique allowed measurement of the ammonia concentration and its relationship to residence time and temperature.

Radical cations of end-capped tetrathienoacenes and their p-dimerization controlled by the nature of a-substituents and counterion concentration

Radical cations of a soluble rigid tetrathienoacene are capable of forming stable p-dimer dications at ambient temperature when the short backbone becomes extended with conjugated thiophene-2-yl substituents in the a-positions. On the other hand, simple attachment of methyl groups on the a-carbon of the external thiophen-2-yl rings proved sufficient to inhibit the dimerization. Stable radical cationswere also exclusively formed for tetrathienoacene derivatives end-capped with bulky TIPS and phenyl substituents.

Short communication: plasma concentration of glucose-dependent insulinotropic polypeptide may regulate milk energy production in lactating dairy cows

In dairy cows, an increase in plasma concentration of glucose-dependent insulinotropic polypeptide (GIP) is associated with an increase in metabolizable energy intake, but the role of GIP in energy partitioning of dairy cattle is not certain. The objective of this study was to examine the relationship between plasma GIP concentrations and energy partitioning toward milk production. Four mid-lactation, primiparous, rumenfistulated Holstein-Friesian cows were fed a control diet of 55% forage and 45% concentrate [dry matter (DM) basis] in a 4 × 4 Latin square design with 4-wk periods. The 4 treatments were (1) control diet fed at 1000 and 1600 h, and (2) once-daily (1000 h) feeding, (3) twice daily (1000 and 1600 h) feeding, and (4) 4 times/d (1000, 1600, 2200 and 0400 h) feeding of the control diet plus 1 dose (1.75 kg on a DM basis at 0955 h) into the rumen of supplemental vegetable proteins (Amino Green; SCA NuTec Ltd., Thirsk, UK). Measurements of respiratory exchange and energy balance were obtained over 4 d during the last week of each period while cows were housed in open-circuit respiration chambers. Blood was collected from the jugular vein every 30 min for 12 h, using indwelling catheters, starting at 0800 h on d 20 of each period. Plasma GIP concentration was measured in samples pooled over each 5 consecutive blood samplings. The relationships between plasma GIP, DM intake, heat production, respiratory quotient, milk yield, and milk energy output were analyzed using linear correlation procedures, with metabolizable intake as a partial variant. Plasma GIP concentration was not correlated with heat production, or milk yield, but was positively correlated with milk energy yield (correlation coefficient = 0.67) and negatively correlated with RQ (correlation coefficient = −0.72). The correlations between GIP and RQ and milk energy output do not imply causality, but suggest that a role for GIP may exist in the regulation of energy metabolism in dairy cows.

Assimilation of sea-ice concentration in a global climate model — physical and statistical aspects

We investigate the initialization of Northern-hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates significantly reduces assimilation error both in identical-twin experiments and when assimilating sea-ice observations, reducing the concentration error by a factor of four to six, and the thickness error by a factor of two. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that the strong dependence of thermodynamic ice growth on ice concentration necessitates an adjustment of mean ice thickness in the analysis update. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that proportional mean-thickness updates are superior to the other two methods considered and enable us to assimilate sea ice in a global climate model using simple Newtonian relaxation.

Assimilation of sea-ice concentration in a global climate model — physical and statistical aspects

We investigate the initialisation of Northern Hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates leads to good assimilation performance for sea-ice concentration and thickness, both in identical-twin experiments and when assimilating sea-ice observations. The simulation of other Arctic surface fields in the coupled model is, however, not significantly improved by the assimilation. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that an adjustment of mean ice thickness in the analysis update is essential to arrive at plausible state estimates. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that assimilation with proportional mean-thickness updates outperforms the other two methods considered. The method described here is very simple to implement, and gives results that are sufficiently good to be used for initialising sea ice in a global climate model for seasonal to decadal predictions.

Ecosystem effects of CO2 concentration: evidence from past climates

Atmospheric CO2 concentration has varied from minima of 170-200 ppm in glacials to maxima of 280-300 ppm in the recent interglacials. Photosynthesis by C-3 plants is highly sensitive to CO2 concentration variations in this range. Physiological consequences of the CO2 changes should therefore be discernible in palaeodata. Several lines of evidence support this expectation. Reduced terrestrial carbon storage during glacials, indicated by the shift in stable isotope composition of dissolved inorganic carbon in the ocean, cannot be explained by climate or sea-level changes. It is however consistent with predictions of current process-based models that propagate known physiological CO2 effects into net primary production at the ecosystem scale. Restricted forest cover during glacial periods, indicated by pollen assemblages dominated by non-arboreal taxa, cannot be reproduced accurately by palaeoclimate models unless CO2 effects on C-3-C-4 plant competition are also modelled. It follows that methods to reconstruct climate from palaeodata should account for CO2 concentration changes. When they do so, they yield results more consistent with palaeoclimate models. In conclusion, the palaeorecord of the Late Quaternary, interpreted with the help of climate and ecosystem models, provides evidence that CO2 effects at the ecosystem scale are neither trivial nor transient.

Exposure to parabens at the concentration of maximal proliferative response increases migratory and invasive activity of human breast cancer cells in vitro

Alkyl esters of p–hydroxybenzoic acid (parabens) are widely used as preservatives in personal care products, foods and pharmaceuticals. Their oestrogenic activity, their measurement in human breast tissue and their ability to drive proliferation of oestrogen-responsive human breast cancer cells has opened a debate on their potential to influence breast cancer development. Since proliferation is not the only hallmark of cancer cells, we have investigated the effects of exposure to parabens at concentrations of maximal proliferative response on migratory and invasive properties using three oestrogen-responsive human breast cancer cell lines (MCF-7, T-47-D, ZR-75-1). Cells were maintained short-term (1 week) or long-term (20±2 weeks) in phenol-red-free medium containing 5% charcoal-stripped serum with no addition, 10-8M 17-oestradiol, 1-5x10-4M methylparaben, 10-5M n-propylparaben or 10-5M n-butylparaben. Long-term exposure (20±2 weeks) of MCF-7 cells to methylparaben, n-propylparaben or n-butylparaben increased migration as measured using a scratch assay, time-lapse microscopy and xCELLigence technology: invasive properties were found to increase in matrix degradation assays and migration through matrigel on xCELLigence. Western immunoblotting showed an associated downregulation of E-cadherin and -catenin in the long-term paraben-exposed cells which could be consistent with a mechanism involving epithelial to mesenchymal transition. Increased migratory activity was demonstrated also in long-term paraben-exposed T-47-D and ZR-75-1 cells using a scratch assay and time-lapse microscopy. This is the first report that in vitro, parabens can influence not only proliferation but also migratory and invasive properties of human breast cancer cells.

An interdisciplinary modelling approach asessing the cost-effectiveness of agri-environmental measures on reducing nutrient concentration to WFD thresholds under climate change: the case of the Louros catchment

The application of the Water Framework Directive (WFD) in the European Union (EU) targets certain threshold levels for the concentration of various nutrients, nitrogen and phosphorous being the most important. In the EU, agri-environmental measures constitute a significant component of Pillar 2—Rural Development Policies in both financial and regulatory terms. Environmental measures also are linked to Pillar 1 payments through cross-compliance and the greening proposals. This paper drawing from work carried out in the REFRESH FP7 project aims to show how an INtegrated CAtchment model of plant/soil system dynamics and instream biogeochemical and hydrological dynamics can be used to assess the cost-effectiveness of agri-environmental measures in relation to nutrient concentration targets set by the WFD, especially in the presence of important habitats. We present the procedures (methodological steps, challenges and problems) for assessing the cost-effectiveness of agri-environmental measures at the baseline situation, and climate and land use change scenarios. Furthermore, we present results of an application of this methodology to the Louros watershed in Greece and discuss the likely uses and future extensions of the modelling approach. Finally, we attempt to reveal the importance of this methodology for designing and incorporating alternative environmental practices in Pillar 1 and 2 measures.

Bile salt composition is secondary to bile salt concentration in determining hydrocortisone and progesterone solubility in intestinal mimetic fluids.

Simulated intestinal fluids (SIFs) used to assay the solubility of orally administered drugs are typically based on a single bile salt; sodium taurocholate (STC). The aim of this study was to develop mimetic intestinal fluids with a closer similarity to physiological fluids than those reported to date by developing a mixed bile salt (MBS) system (STC, sodium glycodeoxycholate, sodium deoxycholate; 60:39:1) with different concentrations of lecithin, the preponderant intestinal phospholipid. Hydrocortisone and progesterone were used as model drugs to evaluate systematically the influence of SIF composition on solubility. Increasing total bile salt concentration from 0 to 30 mM increased hydrocortisone and progesterone solubility by 2- and ∼25-fold, respectively. Accordingly, higher solubilities were measured in the fed-state compared to the fasted-state SIFs. Progesterone showed the greatest increases in solubility in STC and MBS systems (2-7-fold) compared to hydrocortisone (no significant change; P>0.05) as lecithin concentration was increased. Overall, MBS systems gave similar solubility profiles to STC. In conclusion, the addenda of MBS and lecithin were found to be secondary to the influence of BS concentration. These data provide a foundation for the design of more bio-similar media for pivotal decision-guiding assays in drug development and quality control settings.

The permeability parameter of the outer membrane of pseudomonas aeruginosa Varies with the concentration of a test substrate, cephalosporin C

The permeability parameter (C) for the movement of cephalosporin C across the outer membrane of Pseudomonas aeruginosa was measured using the widely accepted method of Zimmermann & Rosselet. In one experiment, the value of C varied continuously from 4·2 to 10·8 cm3 min-1 (mg dry wt cells)-1 over a range of concentrations of the test substrate, cephalosporin C, from 50 to 5 μm. Dependence of C on the concentration of test substrate was still observed when the effect of a possible electric potential difference across the outer membrane was corrected for. In quantitative studies of β-lactam permeation the dependence of C on the concentration of β-lactam should be taken into account.

Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections

A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO2 step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO2 step change taken directly from a GCM experiment. With radiative forcing from non-CO2 constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 1024 J); for RCP6.0: 2.3 K (1.6 × 1024 J); for RCP4.5: 2.0 K (1.6 × 1024 J); for RCP2.6: 1.1 K (1.3 × 1024 J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.

Characterising phosphorus and nitrate inputs to a rural river using high-frequency concentration-flow relationships

The total reactive phosphorus (TRP) and nitrate concentrations of the River Enborne, southern England, were monitored at hourly interval between January 2010 and December 2011. The relationships between these high-frequency nutrient concentration signals and flow were used to infer changes in nutrient source and dynamics through the annual cycle and each individual storm event, by studying hysteresis patterns. TRP concentrations exhibited strong dilution patterns with increasing flow, and predominantly clockwise hysteresis through storm events. Despite the Enborne catchment being relatively rural for southern England, TRP inputs were dominated by constant, non-rain-related inputs from sewage treatment works (STW) for the majority of the year, producing the highest phosphorus concentrations through the spring–summer growing season. At higher river flows, the majority of the TRP load was derived from within-channel remobilisation of phosphorus from the bed sediment, much of which was also derived from STW inputs. Therefore, future phosphorus mitigation measures should focus on STW improvements. Agricultural diffuse TRP inputs were only evident during storms in the May of each year, probably relating to manure application to land. The nitrate concentration–flow relationship produced a series of dilution curves, indicating major inputs from groundwater and to a lesser extent STW. Significant diffuse agricultural inputs with anticlockwise hysteresis trajectories were observed during the first major storms of the winter period. The simultaneous investigation of high-frequency time series data, concentration–flow relationships and hysteresis behaviour through multiple storms for both phosphorus and nitrate offers a simple and innovative approach for providing new insights into nutrient sources and dynamics.

Nonlinear regional warming with increasing CO₂ concentration

When considering adaptation measures and global climate mitigation goals, stakeholders need regional-scale climate projections, including the range of plausible warming rates. To assist these stakeholders, it is important to understand whether some locations may see disproportionately high or low warming from additional forcing above targets such as 2 K (ref. 1). There is a need to narrow uncertainty2 in this nonlinear warming, which requires understanding how climate changes as forcings increase from medium to high levels. However, quantifying and understanding regional nonlinear processes is challenging. Here we show that regional-scale warming can be strongly superlinear to successive CO2 doublings, using five different climate models. Ensemble-mean warming is superlinear over most land locations. Further, the inter-model spread tends to be amplified at higher forcing levels, as nonlinearities grow—especially when considering changes per kelvin of global warming. Regional nonlinearities in surface warming arise from nonlinearities in global-mean radiative balance, the Atlantic meridional overturning circulation, surface snow/ice cover and evapotranspiration. For robust adaptation and mitigation advice, therefore, potentially avoidable climate change (the difference between business-as-usual and mitigation scenarios) and unavoidable climate change (change under strong mitigation scenarios) may need different analysis methods.