A tailored multi-model ensemble for air traffic management: Demonstration and evaluation for the Eyjafjallajökull eruption in May 2010

High quality volcanic ash forecasts are crucial to minimize the economic impact of volcanic hazards on air traffic. Decision-making is usually based on numerical dispersion modeling with only one model realization. Given the inherent uncertainty of such approach, a multi-model multi-source term ensemble has been designed and evaluated for the Eyjafjallaj&ouml;kull eruption in May 2010. Its use for air traffic management is discussed. Two multi-model ensembles were built: the first is based on the output of four dispersion models and their own implementation of ash ejection. All a priori model source terms were constrained by observational evidence of the volcanic ash cloud top as a function of time. The second ensemble is based on the same four dispersion models, which were run with three additional source terms: (i) a source term obtained with background modeling constrained with satellite data (a posteriori source term), (ii) its lower bound estimate, and (iii) its upper bound estimate. The a priori ensemble gives valuable information about the probability of ash dispersion during the early phase of the eruption, when observational evidence is limited. However, its evaluation with observational data reveals lower quality compared to the second ensemble. While the second ensemble ash column load and ash horizontal location compare well to satellite observations, 3D ash concentrations are negatively biased. This might be caused by the vertical distribution of ash, which is too much diluted in all model runs, probably due to defaults in the a posteriori source term and vertical transport and/or diffusion processes in all models. Relevant products for the air traffic management are horizontal maps of ash concentration quantiles (median, 75 %, 99 %) at a fine-resolved flight level grid. These maps can be used for route optimization in the areas where ash does not pose a direct and urgent threat to aviation. Cost-optimized consideration of such hazards will result in much less impact on flight cancellations, reroutings, and traffic flow congestions.</p

Preoperative medical treatment in Cushing&apos;s syndrome : frequency of use and its impact on postoperative assessment : data from ERCUSYN

Background: Surgery is the definitive treatment of Cushing's syndrome (CS) but medications may also be used as a first-line therapy. Whether preoperative medical treatment (PMT) affects postoperative outcome remains controversial. Objective: (1) Evaluate how frequently PMT is given to CS patients across Europe; (2) examine differences in preoperative characteristics of patients who receive PMT and those who undergo primary surgery and (3) determine if PMT influences postoperative outcome in pituitary-dependent CS (PIT-CS). Patients and methods: 1143 CS patients entered into the ERCUSYN database from 57 centers in 26 countries. Sixty-nine percent had PIT-CS, 25% adrenal-dependent CS (ADR-CS), 5% CS from an ectopic source (ECT-CS) and 1% were classified as having CS from other causes (OTH-CS). Results: Twenty per cent of patients took PMT. ECT-CS and PIT-CS were more likely to receive PMT compared to ADR-CS (P < 0.001). Most commonly used drugs were ketoconazole (62%), metyrapone (16%) and a combination of both (12%). Median (interquartile range) duration of PMT was 109 (98) days. PIT-CS patients treated with PMT had more severe clinical features at diagnosis and poorer quality of life compared to those undergoing primary surgery (SX) (P < 0.05). Within 7 days of surgery, PIT-CS patients treated with PMT were more likely to have normal cortisol (P < 0.01) and a lower remission rate (P < 0.01). Within 6 months of surgery, no differences in morbidity or remission rates were observed between SX and PMT groups. Conclusions: PMT may confound the interpretation of immediate postoperative outcome. Follow-up is recommended to definitely evaluate surgical results