Multi-model ensemble predictions of atmospheric turbulence

Atmospheric turbulence is a major aviation hazard, costing the aviation industry millions of dollars each year through aircraft damage and injuries to passengers and crew. In this thesis we compare reanalysis data to climate model simulations to understand how well climate models predict the location of Clear-Air Turbulence (CAT). We then model how climate change will impact CAT on a global scale, in all four seasons and at multiple flight levels. This provides ample motivation for the second half of the thesis which aims to improve aviation turbulence forecasting by testing a multi-model ensemble forecast by combing the Met Office Global and Regional Ensemble Prediction System (MOGREPS-G) and the European Centre for Medium Range Weather Forecasting (ECMWF) Ensemble. The main results found are that climate models are able to skilfully predict the location of CAT, with the main uncertainty of the location of CAT coming from which turbulence index is the best and not from the use of a climate model. We also found CAT will increase globally in the future with climate change, for multiple aviation-relevant turbulence strength categories, at multiple flight levels and in all seasons. For ensemble forecasting we started with a single-diagnostic equally weighted multi-model ensemble and found it is at least as skilful as the single-model ensembles. This lack of significant improvement in the forecast skill could be because when increasing the forecast spread, we capture more turbulence events but also more false alarms. The relative economic value of the forecast is improved for the multi-model ensemble, particularly at low cost/loss ratios. Through combining two ensembles we gain consistency, gain more operational resilience and create one authoritative forecast whilst maintaining skill and increasing value. Extending this work further, it is found that these results apply more generally for multiple turbulence diagnostics, as the multi-model ensemble was more skilful than either of the single-model ensembles. When combining the predictors, the multi-diagnostic multi-model ensemble was more skilful than the two single-model ensembles. It was also found that an optimised 12-member ECMWF and MOGREPS-G multi-diagnostic ensemble was more skilful than the 51-member multi-diagnostic ensemble. What this therefore indicates is that a smaller ensemble spread for the individual diagnostics within a multidiagnostic ensemble is important for optimising operational forecasts in the future, which could reduce computational costs for turbulence forecasting

Global response of clear-air turbulence to climate change

Clear-air turbulence (CAT) is one of the largest causes of weather-related aviation incidents. Here we use climate model simulations to study the impact that climate change could have on global CAT by the period 2050–2080. We extend previous work by analyzing eight geographic regions, two flight levels, five turbulence strength categories, and four seasons. We find large relative increases in CAT, especially in the midlatitudes in both hemispheres, with some regions experiencing several hundred per cent more turbulence. The busiest international airspace experiences the largest increases, with the volume of severe CAT approximately doubling over North America, the North Pacific, and Europe. Over the North Atlantic, severe CAT in future becomes as common as moderate CAT historically. These results highlight the increasing need to improve operational CAT forecasts and to use them effectively in flight planning, to limit discomfort and injuries among passengers and crew

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

Adding 6 months of androgen deprivation therapy to postoperative radiotherapy for prostate cancer: a comparison of short-course versus no androgen deprivation therapy in the RADICALS-HD randomised controlled trial

Background Previous evidence indicates that adjuvant, short-course androgen deprivation therapy (ADT) improves metastasis-free survival when given with primary radiotherapy for intermediate-risk and high-risk localised prostate cancer. However, the value of ADT with postoperative radiotherapy after radical prostatectomy is unclear. Methods RADICALS-HD was an international randomised controlled trial to test the efficacy of ADT used in combination with postoperative radiotherapy for prostate cancer. Key eligibility criteria were indication for radiotherapy after radical prostatectomy for prostate cancer, prostate-specific antigen less than 5 ng/mL, absence of metastatic disease, and written consent. Participants were randomly assigned (1:1) to radiotherapy alone (no ADT) or radiotherapy with 6 months of ADT (short-course ADT), using monthly subcutaneous gonadotropin-releasing hormone analogue injections, daily oral bicalutamide monotherapy 150 mg, or monthly subcutaneous degarelix. Randomisation was done centrally through minimisation with a random element, stratified by Gleason score, positive margins, radiotherapy timing, planned radiotherapy schedule, and planned type of ADT, in a computerised system. The allocated treatment was not masked. The primary outcome measure was metastasis-free survival, defined as distant metastasis arising from prostate cancer or death from any cause. Standard survival analysis methods were used, accounting for randomisation stratification factors. The trial had 80% power with two-sided α of 5% to detect an absolute increase in 10-year metastasis-free survival from 80% to 86% (hazard ratio [HR] 0·67). Analyses followed the intention-to-treat principle. The trial is registered with the ISRCTN registry, ISRCTN40814031, and ClinicalTrials.gov, NCT00541047. Findings Between Nov 22, 2007, and June 29, 2015, 1480 patients (median age 66 years [IQR 61–69]) were randomly assigned to receive no ADT (n=737) or short-course ADT (n=743) in addition to postoperative radiotherapy at 121 centres in Canada, Denmark, Ireland, and the UK. With a median follow-up of 9·0 years (IQR 7·1–10·1), metastasis-free survival events were reported for 268 participants (142 in the no ADT group and 126 in the short-course ADT group; HR 0·886 [95% CI 0·688–1·140], p=0·35). 10-year metastasis-free survival was 79·2% (95% CI 75·4–82·5) in the no ADT group and 80·4% (76·6–83·6) in the short-course ADT group. Toxicity of grade 3 or higher was reported for 121 (17%) of 737 participants in the no ADT group and 100 (14%) of 743 in the short-course ADT group (p=0·15), with no treatment-related deaths. Interpretation Metastatic disease is uncommon following postoperative bed radiotherapy after radical prostatectomy. Adding 6 months of ADT to this radiotherapy did not improve metastasis-free survival compared with no ADT. These findings do not support the use of short-course ADT with postoperative radiotherapy in this patient population

Duration of androgen deprivation therapy with postoperative radiotherapy for prostate cancer: a comparison of long-course versus short-course androgen deprivation therapy in the RADICALS-HD randomised trial

Background Previous evidence supports androgen deprivation therapy (ADT) with primary radiotherapy as initial treatment for intermediate-risk and high-risk localised prostate cancer. However, the use and optimal duration of ADT with postoperative radiotherapy after radical prostatectomy remains uncertain. Methods RADICALS-HD was a randomised controlled trial of ADT duration within the RADICALS protocol. Here, we report on the comparison of short-course versus long-course ADT. Key eligibility criteria were indication for radiotherapy after previous radical prostatectomy for prostate cancer, prostate-specific antigen less than 5 ng/mL, absence of metastatic disease, and written consent. Participants were randomly assigned (1:1) to add 6 months of ADT (short-course ADT) or 24 months of ADT (long-course ADT) to radiotherapy, using subcutaneous gonadotrophin-releasing hormone analogue (monthly in the short-course ADT group and 3-monthly in the long-course ADT group), daily oral bicalutamide monotherapy 150 mg, or monthly subcutaneous degarelix. Randomisation was done centrally through minimisation with a random element, stratified by Gleason score, positive margins, radiotherapy timing, planned radiotherapy schedule, and planned type of ADT, in a computerised system. The allocated treatment was not masked. The primary outcome measure was metastasis-free survival, defined as metastasis arising from prostate cancer or death from any cause. The comparison had more than 80% power with two-sided α of 5% to detect an absolute increase in 10-year metastasis-free survival from 75% to 81% (hazard ratio [HR] 0·72). Standard time-to-event analyses were used. Analyses followed intention-to-treat principle. The trial is registered with the ISRCTN registry, ISRCTN40814031, and ClinicalTrials.gov , NCT00541047 . Findings Between Jan 30, 2008, and July 7, 2015, 1523 patients (median age 65 years, IQR 60–69) were randomly assigned to receive short-course ADT (n=761) or long-course ADT (n=762) in addition to postoperative radiotherapy at 138 centres in Canada, Denmark, Ireland, and the UK. With a median follow-up of 8·9 years (7·0–10·0), 313 metastasis-free survival events were reported overall (174 in the short-course ADT group and 139 in the long-course ADT group; HR 0·773 [95% CI 0·612–0·975]; p=0·029). 10-year metastasis-free survival was 71·9% (95% CI 67·6–75·7) in the short-course ADT group and 78·1% (74·2–81·5) in the long-course ADT group. Toxicity of grade 3 or higher was reported for 105 (14%) of 753 participants in the short-course ADT group and 142 (19%) of 757 participants in the long-course ADT group (p=0·025), with no treatment-related deaths. Interpretation Compared with adding 6 months of ADT, adding 24 months of ADT improved metastasis-free survival in people receiving postoperative radiotherapy. For individuals who can accept the additional duration of adverse effects, long-course ADT should be offered with postoperative radiotherapy. Funding Cancer Research UK, UK Research and Innovation (formerly Medical Research Council), and Canadian Cancer Society

Can a climate model successfully diagnose clear‐air turbulence and its response to climate change?

Atmospheric turbulence causes the majority of weatherrelated aircraft accidents. Climate models project large increases in clear-air turbulence as the jet streams become more sheared in response to climate change. However, climate models have coarser resolutions than the numerical weather prediction models that are used to forecast clearair turbulence operationally, raising questions about their suitability for this purpose. Here we provide the first rigorous demonstration that climate models are capable of successfully diagnosing clear-air turbulence and its response to climate change. We use an ensemble of seven clear-air turbulence diagnostics to compare 38 years of historic turbulence diagnosed from climate model simulations and highresolution reanalysis data. We find that the differences in turbulence between the climate model and reanalysis data are much smaller than the spread between the diagnostics. When using a climate model to calculate the probabilities (and their temporal trends) of encountering clear-air turbulence of any strength, at any flight cruising level, and in any season, we find that most of the uncertainty stems from the turbulencediagnosticsratherthantheclimatemodel. These results confirm the suitability of climate models for the task of producing future clear-air turbulence projections. The turbulence increases are generally larger when diagnosed from the reanalysis data than the climate model, suggest- ing that previous quantifications from climate models of the response of clear-air turbulence to climate change may be underestimates. Our results show that the key to reducing uncertainty in projections of future clear-air turbulence lies inimprovingtheclear-airturbulencediagnosticsratherthan the climate models

Excess centrosomes perturb dynamic endothelial cell repolarization during blood vessel formation

Blood vessel formation requires dynamic movements of endothelial cells (ECs) within sprouts. The cytoskeleton regulates migratory polarity, and centrosomes organize the microtubule cytoskeleton. However, it is not well understood how excess centrosomes, commonly found in tumor stromal cells, affect microtubule dynamics and interphase cell polarity. Here we find that ECs dynamically repolarize during sprouting angiogenesis, and excess centrosomes block repolarization and reduce migration and sprouting. ECs with excess centrosomes initially had more centrosome-derived microtubules but, paradoxically, fewer steady-state microtubules. ECs with excess centrosomes had elevated Rac1 activity, and repolarization was rescued by blockade of Rac1 or actomyosin blockers, consistent with Rac1 activity promoting cortical retrograde actin flow and actomyosin contractility, which precludes cortical microtubule engagement necessary for dynamic repolarization. Thus normal centrosome numbers are required for dynamic repolarization and migration of sprouting ECs that contribute to blood vessel formation