Extreme UK rainfall and natural climate variability: combining models and data

The return periods for extreme events are estimated from observational datasets. Often those datasets are relatively short in comparison to timescales of natural climate variability; potentially introducing a systematic bias into the extreme estimates. Here we combine observations with global climate models to show that this bias is statistically insignificant for the case of extreme UK-wide rainfall estimates. This is unlikely to hold for other locations and spatial scales, yet the methodology we have developed provides a simple approach to quantify the bias for other cases

Reduced Atlantic variability in the mid-Pliocene

This study evaluates interannual-to-decadal sea surface temperature (SST) variability in the mid-Pliocene Warm Period within the Pliocene Model Intercomparison Project (PlioMIP). Our results show significantly reduced variability at low latitudes and mid-latitudes in the mid-Pliocene in comparison to the pre-industrial climate. At high latitudes of both hemispheres, the SST variability has increased. Latitudinal changes are likely driven by changes in the meridional SST gradient. Results with respect to the main Atlantic SST modes of variability show that the Atlantic Multidecadal Variability shifts southward and expands eastward due to a southward shift in the North Atlantic Drift position. The Atlantic Meridional Mode amplitude weakens due to increased SST gradient between its two poles. The South Atlantic Subtropical Dipole significantly shifts its southwestern pole towards the South American coast. Moreover, all Atlantic modes of variability have shifted their respective frequencies towards lower values. Our analyses on the PlioMIP simulation results provide a useful constraint in future projections associated with a warmer world when assessing Atlantic SST variability

Inter-annual variability in the tropical Atlantic from the Last Glacial Maximum into future climate projections simulated by CMIP5/PMIP3

Tropical Atlantic variability (TAV) plays an important role in driving year-to-year changes in rainfall over Africa and South America. In this study, its response to global climate change is investigated through a series of multi-model experiments. We explore the leading modes of TAV during the historical, Last Glacial Maximum, mid-Holocene, and future simulations in the multi-model ensemble known as PMIP3/CMIP5. Despite their known sea surface temperature biases, most of the models are able to capture the tropical Atlantic's two leading modes of SST variability patterns - the Atlantic Meridional Mode (AMM) and the Atlantic zonal mode (also called the Atlantic Niño or ATL3). The ensemble suggests that AMM amplitude was less during the mid-Holocene and increased during the Last Glacial Maximum, but is equivocal about future changes. ATL3 appears stronger under both the Last Glacial Maximum and future climate changes, with no consistent message about the mid-Holocene. The patterns and the regions under the influence of the two modes alter a little under climate change in concert with changes in the mean climate state. In the future climate experiment, the equatorial mode weakens, and the whole Northern Hemisphere warms up, while the South Atlantic displays a hemisphere-wide weak oscillating pattern. For the LGM, the AMM projects onto a pattern that resembles the pan-Atlantic decadal oscillation. No robust relationships between the amplitude of the zonal and meridional temperature gradients and their respective variability was found

The Limited Role of Mutually Unbiased Product Bases in Dimension Six

We show that a complete set of seven mutually unbiased bases in dimension six, if it exists, cannot contain more than one product basis.Comment: 8 pages, identical to published versio

Statistical mechanics of multipartite entanglement

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over all balanced bipartitions. We search for those (maximally multipartite entangled) states whose purity is minimum for all bipartitions and recast this optimization problem into a problem of statistical mechanics.Comment: final versio

A cannabigerol-rich Cannabis sativa extract, devoid of ∆9-tetrahydrocannabinol, elicits hyperphagia in rats

Objective: Non-psychoactive phytocannabinoids (pCBs) from Cannabis sativa may represent novel therapeutic options for cachexia due to their pleiotropic pharmacological activities, including appetite stimulation. We have recently shown that purified cannabigerol (CBG) is a novel appetite stimulant in rats. As standardised extracts from Cannabis chemotypes dominant in one pCB (botanical drug substances (BDS)) often show greater efficacy and/or potency than purified pCBs, we investigated the effects of a CBG-rich BDS, devoid of psychoactive ∆9-THC, on feeding behaviour. Methods: Following a 2 hour pre-feed satiation procedure, 16 male Lister-hooded rats were administered CBG-BDS (at 30-240 mg/kg) or vehicle. Food intake, meal pattern microstructure and locomotor activity were recorded over 2 hours. Results: Total food intake was increased by 120 and 240mg/kg CBG-BDS vs vehicle (1.53g and 1.36g, respectively, vs 0.56g; p<0.05 and p<0.01). Latency to feeding onset was dose-dependently decreased by all doses (p<0.05-0.01), and 120 and 240mg/kg doses increased both the number of meals consumed (p<0.01) and cumulative size of the first 2 meals (p<0.05 and p<.0.01). No significant effect was observed on ambulatory activity or rearing behaviour. Conclusions: CBG-BDS is a novel appetite stimulant, which may have greater potency than purified CBG, despite the absence of ∆9-THC in the extract

Multi-Qubit Systems: Highly Entangled States and Entanglement Distribution

A comparison is made of various searching procedures, based upon different entanglement measures or entanglement indicators, for highly entangled multi-qubits states. In particular, our present results are compared with those recently reported by Brown et al. [J. Phys. A: Math. Gen. 38 (2005) 1119]. The statistical distribution of entanglement values for the aforementioned multi-qubit systems is also explored.Comment: 24 pages, 3 figure

Potential use of oxygen as a metabolic biosensor in combination with T2*-weighted MRI to define the ischemic penumbra

We describe a novel magnetic resonance imaging technique for detecting metabolism indirectly through changes in oxyhemoglobin:deoxyhemoglobin ratios and T2* signal change during ‘oxygen challenge’ (OC, 5 mins 100% O2). During OC, T2* increase reflects O2 binding to deoxyhemoglobin, which is formed when metabolizing tissues take up oxygen. Here OC has been applied to identify tissue metabolism within the ischemic brain. Permanent middle cerebral artery occlusion was induced in rats. In series 1 scanning (n=5), diffusion-weighted imaging (DWI) was performed, followed by echo-planar T2* acquired during OC and perfusion-weighted imaging (PWI, arterial spin labeling). Oxygen challenge induced a T2* signal increase of 1.8%, 3.7%, and 0.24% in the contralateral cortex, ipsilateral cortex within the PWI/DWI mismatch zone, and ischemic core, respectively. T2* and apparent diffusion coefficient (ADC) map coregistration revealed that the T2* signal increase extended into the ADC lesion (3.4%). In series 2 (n=5), FLASH T2* and ADC maps coregistered with histology revealed a T2* signal increase of 4.9% in the histologically defined border zone (55% normal neuronal morphology, located within the ADC lesion boundary) compared with a 0.7% increase in the cortical ischemic core (92% neuronal ischemic cell change, core ADC lesion). Oxygen challenge has potential clinical utility and, by distinguishing metabolically active and inactive tissues within hypoperfused regions, could provide a more precise assessment of penumbra

How to decarbonise international shipping: Options for fuels, technologies and policies

International shipping provides 80–90% of global trade, but strict environmental regulations around NOX, SOX and greenhouse gas (GHG) emissions are set to cause major technological shifts. The pathway to achieving the international target of 50% GHG reduction by 2050 is unclear, but numerous promising options exist. This study provides a holistic assessment of these options and their combined potential to decarbonise international shipping, from a technology, environmental and policy perspective. Liquefied natural gas (LNG) is reaching mainstream and provides 20–30% CO2 reductions whilst minimising SOX and other emissions. Costs are favourable, but GHG benefits are reduced by methane slip, which varies across engine types. Biofuels, hydrogen, nuclear and carbon capture and storage (CCS) could all decarbonise much further, but each faces significant barriers around their economics, resource potentials and public acceptability. Regarding efficiency measures, considerable fuel and GHG savings could be attained by slow-steaming, ship design changes and utilising renewable resources. There is clearly no single route and a multifaceted response is required for deep decarbonisation. The scale of this challenge is explored by estimating the combined decarbonisation potential of multiple options. Achieving 50% decarbonisation with LNG or electric propulsion would likely require 4 or more complementary efficiency measures to be applied simultaneously. Broadly, larger GHG reductions require stronger policy and may differentiate between short- and long-term approaches. With LNG being economically feasible and offering moderate environmental benefits, this may have short-term promise with minor policy intervention. Longer term, deeper decarbonisation will require strong financial incentives. Lowest-cost policy options should be fuel- or technology-agnostic, internationally applied and will require action now to ensure targets are met by 2050