Aviation turbulence: dynamics, forecasting, and response to climate change

Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviation-affecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed—ideally in collaboration with the aviation industry—to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW ($\textit{P}$  < 5 × 10$^{-8}$). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure ($\textit{R}$ $_{g}$ = -0.22, $\textit{P}$  = 5.5 × 10$^{-13}$), T2D ($\textit{R}$ $_{g}$ = -0.27, $\textit{P}$  = 1.1 × 10$^{-6}$) and coronary artery disease ($\textit{R}$ $_{g}$ = -0.30, $\textit{P}$  = 6.5 × 10$^{-9}$). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions ($\textit{P}$ = 1.9 × 10$^{-4}$). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.For a full list of the funders pelase visit the publisher's website and look at the supplemetary material provided. Some of the funders are: British Heart Foundation, Cancer Research UK, Medical Research Council, National Institutes of Health, Royal Society and Wellcome Trust

Environment and Mechanisms of Severe Turbulence in a Midlatitude Cyclone

A large midlatitude cyclone occurred over the central United States from 0000 to 1800 UTC 30 April 2017. During this period, there were more than 1100 reports of moderate-or-greater turbulence at commercial aviation cruising altitudes east of the Rocky Mountains. Much of this turbulence was located above or, otherwise, outside the synoptic-scale cloud shield of the cyclone, thus complicating its avoidance. In this study we use two-way nesting in a numerical model with finest horizontal spacing of 370 m to investigate possible mechanisms producing turbulence in two distinct regions of the cyclone. In both regions, model-parameterized turbulence kinetic energy compares well to observed turbulence reports. Despite being outside of hazardous large radar reflectivity locations in deep convection, both regions experienced strong modification of the turbulence environment as a result of upper-tropospheric/lower-stratospheric (UTLS) convective outflow. For one region, where turbulence was isolated and short lived, simulations revealed breaking of ~100-km horizontal-wavelength lower-stratospheric gravity waves in the exit region of a UTLS jet streak as the most likely mechanism for the observed turbulence. Although similar waves occurred in a simulation without convection, the altitude at which wave breaking occurred in the control simulation was strongly affected by UTLS outflow from distant deep convection. In the other analyzed region, turbulence was more persistent and widespread. There, overturning waves of much shorter 5–10-km horizontal wavelengths occurred within layers of gradient Richardson number < 0.25, which promoted Kelvin–Helmholtz instability associated with strong vertical shear in different horizontal locations both above and beneath the convectively enhanced UTLS jet

The role of gravity wave breaking in a case of upper-level near-cloud turbulence

An observed turbulence encounter that occurred outside a mesoscale convective system over the central USA on 3 June 2005 is investigated using observations and high resolution numerical modeling. Here, the mechanisms associated with the observed moderate-to-severe turbulence during the evolution of this convective system are examined. Comparison between aircraftobserved eddy dissipation rate data with satellite and radar shows that a majority of turbulence reports are located on the south side and outside of a nocturnal mesoscale convective system (MCS), relatively large distances from the active convective regions. Simulations show that divergent storm-induced upper-level outflow reduces the environmental flow on the south side of the MCS, while on the north and northwest side it enhances the environmental flow. This upper-level storm outflow enhances the vertical shear near the flight levels and contributes to mesoscale reductions in Richardson number to values that support turbulence. In addition to the role of the MCS-induced outflow, high-resolution simulations (1.1-km horizontal grid spacing) show that turbulence is largely associated with a large amplitude gravity wave generated by the convective system, which propagates away from it. As the wave propagates in the region with enhanced vertical shear caused by the storm-induced upper-level outflow, it amplifies, overturns and breaks down into turbulence. The location of the simulated turbulence relative to the storm agrees with the observations and the analysis herein provides insight into the key processes underlying this event

Recent Advances in the Understanding of Near-Cloud Turbulence

Anyone who has flown in a commercial aircraft is familiar with turbulence. Unexpected encounters with turbulence pose a safety risk to airline passengers and crew, can occasionally damage aircraft, and indirectly increase the cost of air travel. Deep convective clouds are one of the most important sources of turbulence. Cloud-induced turbulence can occur both within clouds and in the surrounding clear air. Turbulence associated with but outside of clouds is of particular concern because it is more difficult to discern using standard hazard identification technologies (e.g., satellite and radar) and thus is often the source of unexpected turbulence encounters. Although operational guidelines for avoiding near-cloud turbulence exist, they are in many ways inadequate because they were developed before the governing dynamical processes were understood. Recently, there have been significant advances in the understanding of the dynamics of near-cloud turbulence. Using examples, this article demonstrates how these advances have stemmed from improved turbulence observing and reporting systems, the establishment of archives of turbulence encounters, detailed case studies, and high-resolution numerical simulations. Some of the important phenomena that have recently been identified as contributing to near-cloud turbulence include atmospheric wave breaking, unstable upper-level thunderstorm outflows, shearing instabilities, and cirrus cloud bands. The consequences of these phenomena for developing new en route turbulence avoidance guidelines and forecasting methods are discussed, along with outstanding research questions