Revisiting the 26.5°C Sea Surface Temperature Threshold for Tropical Cyclone Development

Abstract A high sea surface temperature is generally accepted to be one of the necessary ingredients for tropical cyclone development, indicative of the potential for surface heat and moisture fluxes capable of fueling a self-sustaining circulation. Although the minimum 26.5°C threshold for tropical cyclogenesis has become a mainstay in research and education, the fact that a nonnegligible fraction of storm formation events (about 5%) occur over cooler waters casts some doubt on the robustness of this estimate. Tropical cyclogenesis over subthreshold sea surface temperatures is associated with low tropopause heights, indicative of the presence of a cold trough aloft. To focus on this type of development environment, the applicability of the 26.5°C threshold is investigated for tropical transitions from baroclinic precursor disturbances in all basins between 1989 and 2013. Although the threshold performs well in the majority of cases without appreciable environmental baroclinicity, the potential for development is underestimated by up to 27% for systems undergoing tropical transition. An alternative criterion of a maximum 22.5°C difference between the tropopause-level and 850-hPa equivalent potential temperatures (defined as the coupling index) is proposed for this class of development. When combined with the standard 26.5°C sea surface temperature threshold for precursor-free environments, error rates are reduced to 3%–6% for all development types. The addition of this physically relevant representation of the deep-tropospheric state to the ingredients-based conceptual model for tropical cyclogenesis improves the representation of the important tropical transition-based subset of development events.</jats:p

Low Temperature Combustion Optimization and Cycle-by-Cycle Variability Through Injection Optimization and Gas-to-Liquid Fuel-Blend Ratio

The advent of common rail technology alongside powerful control systems capable of delivering multiple accurate fuel charges during a single engine cycle has revolutionized the level of control possible in diesel combustion. This technology has opened a new path enabling low-temperature combustion (LTC) to become a viable combustion strategy. The aim of the research work presented within this paper is the understanding of how various engine parameters of LTC optimize the combustion both in terms of emissions and in terms of fuel efficiency. The work continues with an investigation of in-cylinder pressure and IMEP cycle-by-cycle variation. Attention will be given to how repeatability changes throughout the combustion cycle, identifying which parts within the cycle are least likely to follow the mean trend and why. Experiments were conducted on a single-cylinder 510cc boosted diesel engine. LTC was affected over varying rail pressure and combustion phasing. Single and split injection regimes of varying dwell-times were investigated. All injection conditions were phased across several crank-angles to demonstrate the interaction between emissions and efficiency. These tests were then repeated with blends of 30% and 50% gas-to-liquid (GTL)-diesel blends in order to determine whether there is any change in the trends of repeatability and variance with increasing GTL blend ratio. The experiments were evaluated in terms of emissions, fuel efficiency, and cyclic behavior. Specific attention was given to how the NO x -PM trade-off changes through increased injection complexity and increasing GTL blend ratio. The cyclic behavior was analyzed in terms of in-cylinder pressure standard deviation. This gives a behavior profile of the repeatability of in-cylinder pressure in comparison to the mean. Each condition was then compared to the behavior of equivalent injection conditions in conventional diesel combustion. Short-dwell split injection was shown to be beneficial for LTC, while NO x was shown to be reduced by the substitution of GTL in the fuel. In-cylinder pressure cyclic behavior was also shown to be comparable or superior to conventional combustion in every case examined. GTL improved this further, but not in proportion to its blend ratio

The “Grey Zone” cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation “Grey Zone” project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity

Experience-based utility and own health state valuation for a health state classification system: why do it and how to do it

In the estimation of population value sets for health state classification systems such as the EQ-5D, there is increasing interest in asking respondents to value their own health state, sometimes referred to as "experienced-based utility values" or more correctly ownrather than hypothetical health states. Own health state values differ to hypothetical health state values, and this may be attributed to many reasons. This paper critically examines: whose values matter; why there is a difference between own and hypothetical values; how to measure own health state values; and why to use own health state values. Finally, the paper also examines other ways that own health state values can be taken into account, such as including the use of informed general population preferences that may better take into account experience-based values

Australian utility weights for the EORTC QLU-C10D, a multi-attribute utility instrument derived from the cancer-specific quality of life questionnaire, EORTC QLQ-C30

Background: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely-used cancer-specific quality of life questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with 4 levels. To be used in cost-utility analysis, country-specific valuation sets are required. Objective: To provide Australian utility weights for the QLU-C10D. Methods: An Australian online panel was quota sampled to ensure population representativeness by sex and age (≥18y). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy. Results: 1979 panel members opted-in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death. Conclusions: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively

Are preferences over health states informed?

BACKGROUND: The use of preference-elicitation tasks for valuing health states is well established, but little is known about whether these preferences are informed. Preferences may not be informed because individuals with little experience of ill health are asked to value health states. The use of uninformed preferences in cost-effectiveness can result in sub-optimal resource allocation. The aim of this study was to pilot a novel method to assess whether members of the public are informed about health states they value in preference-elicitation tasks. METHODS: The general public was said to be informed if the expectations of the public about the effect of ill health on people's lives were in agreement with the experience of patients. Sixty-two members of the public provided their expectations of the consequences of ill health on five life domains (activities, enjoyment, independence, relationships, and avoiding being a burden). A secondary dataset was used to measure patient experience on those five consequences. RESULTS: There were differences between the expectations of the public and the experience of patients. For example, for all five life consequences the public underestimated the effects of problems in usual activities compared to problems in mobility. They also underestimated the effect of 'anxiety or depression' compared to physical problems on enjoyment of life and on the quality of personal relationships. CONCLUSIONS: This proof-of-concept study showed that it is possible to test whether preferences are informed. This study should be replicated using a larger sample. The findings suggest that preferences over health states in this sample are not fully informed because the participants do not have accurate expectations about the consequences of ill health. These uninformed preferences may not be adequate for allocation of public resources, and research is needed into methods to make them better informed