An evaluation of planktonic foraminiferal zonation of the Oligocene

42 p., 8 pl., 7 fig.http://paleo.ku.edu/contributions.htm

Characterising the Optical Response of the SNO+ Detector

SNO+ is a liquid scintillator based neutrino experiment located 2039 m underground in VALE's Creighton mine, Lively, Ontario, CA. It is a re-purposing of the original Cherenkov detector used in the SNO experiment to study neutrino oscillations. The advent of neutrino oscillations has revealed that neutrinos have a small yet non-zero mass. However, the nature of this mass has yet to be determined. It is possible that the neutrino is its own anti-particle, a Majorana fermion. If so, such particles necessitate lepton number violating processes such as neutrinoless double beta decay. SNO+ intends to search for the neutrinoless double beta decay of Te-130. Other physics objectives include the study of low-energy solar neutrinos, reactor anti-neutrinos, geo-neutrinos and sensitivity to nucleon decay and supernova neutrinos. To fulfil these objectives, SNO+ will operate over three detector phases; water, scintillator and tellurium (loading of the scintillator with tellurium). Prior to each phase, the experiment will undergo a full detector calibration. This includes an optical calibration that seeks to characterise the optical response of the detector using two types of in-situ light sources; one of these is called the laserball. The laserball provides a pulsed, near-isotropic light distribution throughout the detector. Laserball data is used in conjunction with a parameterised model that characterises the optical response; the parameters are determined using a statistical fit. This thesis presents an implementation of said model to all three phases of the SNO+ experiment. A characterisation of the optical response in water is presented using a combination of original laserball data from SNO and MC data of the SNO+ detector. Thereafter, the two scintillator based phases are considered, wherein the increased attenuation of light due to absorption and reemission introduced by the scintillator is addressed alongside a model of the scintillation time profile

Correction to: “Constraining climate forecasts: The role of prior assumptions”

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Irreducible uncertainty in near-term climate projections

Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified

In-situ characterization of the Hamamatsu R5912-HQE photomultiplier tubes used in the DEAP-3600 experiment

The Hamamatsu R5912-HQE photomultiplier-tube (PMT) is a novel high-quantum efficiency PMT. It is currently used in the DEAP-3600 dark matter detector and is of significant interest for future dark matter and neutrino experiments where high signal yields are needed. We report on the methods developed for in-situ characterization and monitoring of DEAP's 255 R5912-HQE PMTs. This includes a detailed discussion of typical measured single-photoelectron charge distributions, correlated noise (afterpulsing), dark noise, double, and late pulsing characteristics. The characterization is performed during the detector commissioning phase using laser light injected through a light diffusing sphere and during normal detector operation using LED light injected through optical fibres

Towards Prospective Life Cycle Assessment: How to Identify Key Parameters Inducing Most Uncertainties in the Future? Application to Photovoltaic Systems Installed in Spain

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-09150-1_51International audienceProspective Life Cycle Assessment (LCA) is a relevant approach to assess the environmental performance of future energy pathways. Amongst different types of prospective scenarios, cornerstone scenarios meant for complex systems and long-term approaches, are of interest to assess such performance. They rely on different types of long-term projections, such as projections of technological evolutions and of energy resources. In most studies, scenarios are defined with single values for each parameter, and environmental impacts are assessed in a deterministic way. Inherent uncertainties related to these prospective assumptions are not considered and prospective LCA uncertainties are thus not addressed. In this paper we describe a methodology to account for these uncertainties and to identify the parameters inducing most of the uncertainties in the prospective LCA results. We apply this approach to prospective LCAs of photovoltaic-based electricity generation systems

Using the past to constrain the future: how the palaeorecord can improve estimates of global warming

Climate sensitivity is defined as the change in global mean equilibrium temperature after a doubling of atmospheric CO2 concentration and provides a simple measure of global warming. An early estimate of climate sensitivity, 1.5-4.5{\deg}C, has changed little subsequently, including the latest assessment by the Intergovernmental Panel on Climate Change. The persistence of such large uncertainties in this simple measure casts doubt on our understanding of the mechanisms of climate change and our ability to predict the response of the climate system to future perturbations. This has motivated continued attempts to constrain the range with climate data, alone or in conjunction with models. The majority of studies use data from the instrumental period (post-1850) but recent work has made use of information about the large climate changes experienced in the geological past. In this review, we first outline approaches that estimate climate sensitivity using instrumental climate observations and then summarise attempts to use the record of climate change on geological timescales. We examine the limitations of these studies and suggest ways in which the power of the palaeoclimate record could be better used to reduce uncertainties in our predictions of climate sensitivity.Comment: The final, definitive version of this paper has been published in Progress in Physical Geography, 31(5), 2007 by SAGE Publications Ltd, All rights reserved. \c{opyright} 2007 Edwards, Crucifix and Harriso

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like