The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Model experiment description paperProjections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017-2018 time frame, and output from the climate model projections made available and analyses performed over the 2018-2020 period.CRESCENDO project members (V. Eyring, P. Friedlingstein, E. Kriegler, R. Knutti, J. Lowe, K. Riahi, D. van Vuuren) acknowledge funding received from the Horizon 2020 European Union’s Framework Programme for Research and Innovation under grant agreement no. 641816. C. Tebaldi, G. A. Meehl and B. M. Sanderson acknowledge the support of the Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy’s, Office of Science (BER), Cooperative Agreement DE-FC02-97ER6240

Towards a typology for constrained climate model forecasts

In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context

Loss of flight promotes beetle diversification

The evolution of flight is a key innovation that may enable the extreme diversification of insects. Nonetheless, many species-rich, winged insect groups contain flightless lineages. The loss of flight may promote allopatric differentiation due to limited dispersal power and may result in a high speciation rate in the flightless lineage. Here we show that loss of flight accelerates allopatric speciation using carrion beetles (Coleoptera: Silphidae). We demonstrate that flightless species retain higher genetic differentiation among populations and comprise a higher number of genetically distinct lineages than flight-capable species, and that the speciation rate with the flightless state is twice that with the flight-capable state. Moreover, a meta-analysis of 51 beetle species from 15 families reveals higher genetic differentiation among populations in flightless compared with flight-capable species. In beetles, which represent almost one-fourth of all described species, repeated evolution of flightlessness may have contributed to their steady diversification since the Mesozoic era

Instrumented intervertebral or posterolateral fusion in elderly patients Clinical results of a single center

<p>Abstract</p> <p>Background</p> <p>Data on the clinical outcome after spinal fusion in the elderly patient are rare. To our knowledge there has been no clinical outcome assessment for instrumented spinal fusion in elderly patients comparing posterolateral fusion with intervertebral fusion. Aim of the current study was to evaluate the clinical outcome of elderly patients who underwent a spinal fusion procedure for degenerative spinal stenosis with instability. Main hypothesis was to test whether it is necessary to force an intervertebral fusion for a better clinical outcome in spinal fusion surgery of the elderly or not.</p> <p>Methods</p> <p>Two subgroups - posterolateral fusion versus intervertebral fusion (cage vs. non-cage) were compared with regard to functional outcome, fusion rates and complications after a mean follow up of 3.8 years. Questionnaires were completed by the patients before surgery and at final follow-up. Changes in mean VAS and ODI scores (decrease from the baseline VAS and ODI scores) were compared.</p> <p>Results</p> <p>The mean final follow up for all subjects was 3.8 years. Of the 114 patients, 2 patients were deceased at the time of the follow-up, 5 patients didn't want to participate and 107 patients completed the questionnaires. This resulted in an overall follow-up rate of 93%. At final follow-up, the patients demonstrated significant improvement in the VAS and ODI- compared with the preoperative scores in both groups. But overall there were no significant differences between both groups regarding the outcome assessment using the ODI and VAS.</p> <p>Conclusions</p> <p>The results of this study shows that elderly patients aged over 75 benefit from instrumented lumbar fusion. The study suggests that there is no need to force an intervertebral fusion because elderly patients do not seem to benefit from this procedure.</p

The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review

BackgroundThe Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicators to inform quality improvement initiatives is contingent upon the validity and reliability of the indicators. The purpose of this review was to systematically examine published and grey research reports in order to assess the state of the science regarding the validity and reliability of the RAI-MDS 2.0 Quality Indicators (QIs).MethodsWe systematically reviewed the evidence for the validity and reliability of the RAI-MDS 2.0 QIs. A comprehensive literature search identified relevant original research published, in English, prior to December 2008. Fourteen articles and one report examining the validity and/or reliability of the RAI-MDS 2.0 QIs were included.ResultsThe studies fell into two broad categories, those that examined individual quality indicators and those that examined multiple indicators. All studies were conducted in the United States and included from one to a total of 209 facilities. The number of residents included in the studies ranged from 109 to 5758. One study conducted under research conditions examined 38 chronic care QIs, of which strong evidence for the validity of 12 of the QIs was found. In response to these findings, the 12 QIs were recommended for public reporting purposes. However, a number of observational studies (n=13), conducted in &quot;real world&quot; conditions, have tested the validity and/or reliability of individual QIs, with mixed results. Ten QIs have been studied in this manner, including falls, depression, depression without treatment, urinary incontinence, urinary tract infections, weight loss, bedfast, restraint, pressure ulcer, and pain. These studies have revealed the potential for systematic bias in reporting, with under-reporting of some indicators and over-reporting of others.ConclusionEvidence for the reliability and validity of the RAI-MDS QIs remains inconclusive. The QIs provide a useful tool for quality monitoring and to inform quality improvement programs and initiatives. However, caution should be exercised when interpreting the QI results and other sources of evidence of the quality of care processes should be considered in conjunction with QI results.<br /

Climate model forecast biases assessed with a perturbed physics ensemble

Perturbed physics ensembles have often been used to analyse long-timescale climate model behaviour, but have been used less often to study model processes on shorter timescales. We combine a transient perturbed physics ensemble with a set of initialised forecasts to deduce regional process errors present in the standard HadCM3 model, which cause the model to drift in the early stages of the forecast. First, it is shown that the transient drifts in the perturbed physics ensembles can be used to recover quantitatively the parameters that were perturbed. The parameters which exert most influence on the drifts vary regionally, but upper ocean mixing and atmospheric convective processes are particularly important on the 1-month timescale. Drifts in the initialised forecasts are then used to recover the ‘equivalent parameter perturbations’, which allow identification of the physical processes that may be at fault in the HadCM3 representation of the real world. Most parameters show positive and negative adjustments in different regions, indicating that standard HadCM3 values represent a global compromise. The method is verified by correcting an unusually widespread positive bias in the strength of wind-driven ocean mixing, with forecast drifts reduced in a large number of areas as a result. This method could therefore be used to improve the skill of initialised climate model forecasts by reducing model biases through regional adjustments to physical processes, either by tuning or targeted parametrisation refinement. Further, such regionally tuned models might also significantly outperform standard climate models, with global parameter configurations, in longer-term climate studies

High stakes decisions under uncertainty: dams, development and climate change in the Rufiji river basin

The need to stress test designs and decisions about major infrastructure under climate change conditions is increasingly being recognised. This chapter explores new ways to understand and—if possible—reduce the uncertainty in climate information to enable its use in assessing decisions that have consequences across the water, energy, food and environment sectors. It outlines an approach, applied in the Rufiji River Basin in Tanzania, that addresses uncertainty in climate model projections by weighting them according to different skill metrics; how well the models simulate important climate features. The impact of different weighting approaches on two river basin performance indicators (hydropower generation and environmental flows) is assessed, providing an indication of the reliability of infrastructure investments, including a major proposed dam under different climate model projections. The chapter ends with a reflection on the operational context for applying such approaches and some of the steps taken to address challenges and to engage stakeholders

Impact of Deep Coalescence on the Reliability of Species Tree Inference from Different Types of DNA Markers in Mammals

An important challenge for phylogenetic studies of closely related species is the existence of deep coalescence and gene tree heterogeneity. However, their effects can vary between species and they are often neglected in phylogenetic analyses. In addition, a practical problem in the reconstruction of shallow phylogenies is to determine the most efficient set of DNA markers for a reliable estimation. To address these questions, we conducted a multilocus simulation study using empirical values of nucleotide diversity and substitution rates obtained from a wide range of mammals and evaluated the performance of both gene tree and species tree approaches to recover the known speciation times and topological relationships. We first show that deep coalescence can be a serious problem, more than usually assumed, for the estimation of speciation times in mammals using traditional gene trees. Furthermore, we tested the performance of different sets of DNA markers in the determination of species trees using a coalescent approach. Although the best estimates of speciation times were obtained, as expected, with the use of an increasing number of nuclear loci, our results show that similar estimations can be obtained with a much lower number of genes and the incorporation of a mitochondrial marker, with its high information content. Thus, the use of the combined information of both nuclear and mitochondrial markers in a species tree framework is the most efficient option to estimate recent speciation times and, consequently, the underlying species tree

Towards improved cover glasses for photovoltaic devices

For the solar energy industry to increase its competitiveness there is a global drive to lower the cost of solar generated electricity. Photovoltaic (PV) module assembly is material-demanding and the cover glass constitutes a significant proportion of the cost. Currently, 3 mm thick glass is the predominant cover material for PV modules, accounting for 10-25% of the total cost. Here we review the state-of-the-art of cover glasses for PV modules and present our recent results for improvement of the glass. These improvements were demonstrated in terms of mechanical, chemical and optical properties by optimizing the glass composition, including addition of novel dopants, to produce cover glasses that can provide: (i) enhanced UV protection of polymeric PV module components, potentially increasing module service lifetimes; (ii) re-emission of a proportion of the absorbed UV photon energy as visible photons capable of being absorbed by the solar cells, thereby increasing PV module efficiencies; (iii) Successful laboratory-scale demonstration of proof-of-concept, with increases of 1-6% in Isc and 1-8% Ipm. Improvements in both chemical and crack resistance of the cover glass were also achieved through modest chemical reformulation, highlighting what may be achievable within existing manufacturing technology constraints