Recommendations for improved tropical cyclone formation and position probabilistic Forecast products

Prediction of the potentially devastating impact of landfalling tropical cyclones (TCs) relies substantially on numerical prediction systems. Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios, it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings. RSMCs, TCWCs, and other forecast centers value probabilistic guidance for TCs, but the International Workshop on Tropical Cyclones (IWTC-9) found that the “pull-through” of probabilistic information to operational warnings using those forecasts is slow. IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products (TC-PFP) project, which is also endorsed as a WMO Seamless GDPFS Pilot Project. The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts. TC-PFP is being implemented in 3 phases: Phase 1 (TC formation and position); Phase 2 (TC intensity and structure); and Phase 3 (TC related rainfall and storm surge). This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position. There is considerable variability in the nature and interpretation of forecast products based on ensemble information, making it challenging to transfer knowledge of best practices across forecast centers. Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices. Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts. Finally, forecast centers need timely access to ensemble information that has consistent, user-friendly ensemble information. Greater consistency across forecast centers in data accessibility, probabilistic forecast products, and warnings and their communication to users will produce more reliable information and support improved outcomes

Positionnement et actions d'AQUAREF sur l'analyse non ciblée pour la surveillance des milieux aquatiques

National audiencePrésentation des travaux et réflexions du consortium Aquaref sur l'intérêt de l'analyse chimique non ciblée pour anticiper la surveillance de demain. Présentation 1/des premiers résultats d'essais collaboratifs pour l'harmonisation des méthodologies et 2/ de l'étude de démonstration dans le cadre du réseau de surveillance prospective

Comment les conditions d'extraction en phase solide affectent l'analyse suspectée et non-ciblée pour l'évaluation de la contamination des eaux de surface

International audienceIdentifying organic contaminants present in aquatic environments is of major concern for water quality monitoring. New analytical and data treatment tools have been developed to meet this challenge. The sample preparation before analyses is the first crucial step to be optimized before using suspect and non-target-screening approaches for qualitative evaluations of water pollution by contaminants from various chemical and usage families. As part of the action of Aquaref, which is the French reference laboratory for environmental monitoring in the Water Framework Directive, different solid phase extraction conditions (SPE, n=3 per condition) were tested towards UHPLC-HRMS (separation by UHPLC carried out with a C18) analysis. The SPE protocols varied according to the extraction phase (Oasis HLB or multilayer cartridge), the elution solvent (methanol or methanol and dichloromethane) and sample pH (pH 3 or 7). To ensure data quality, blank solvents, extracted blanks and quality control (QC) were also injected. The QC sample corresponds to a pool of 5 µL of each sample extract and is injected repeatedly throughout the injection sequence to monitor the analytical repeatability. By suspect screening strategy, most of the investigated compounds were found in all SPE extracts. The results revealed the presence of contaminants such as pesticides, pharmaceuticals, sweeteners, or anti-corrosive agents. For pesticides, approved (e.g. diuron) and not approved (e.g. terbutryn) compounds were both detected. Concerning the pharmaceuticals, drugs acting on the nervous system were most common (e.g. oxazepam), as well as betablockers (e.g. metoprolol). The without any a priori non-target approach highlighted that the SPE conditions affect the quality and the interpretation of the data. The number of signals (features) detected by each method varies, as does the number of signals associated with background noise, for each sample preparation method tested. These results support the suspect screening results. Data treatment revealed that the two SPE with Oasis HLB extraction phase at pH 7 (elution with methanol or methanol and dichloromethane) lead to detection of more signals with m/z above 600 Da. Based on the retention time distribution of signals detected for each SPE methods, the multilayered cartridge allowed the extraction of more polar compounds than the other SPE methods. The comparison of all the signals detected with each SPE condition revealed that 31% to 57% of them are specific to only one SPE method. The evaluation of sample preparation methods prior to suspect and non-target screening is required before data treatment to assess the presence of contaminants in water

Recommendations for improved tropical cyclone formation and position probabilistic forecast products

Prediction of the potentially devastating impact of landfalling tropical cyclones (TCs) relies substantially on numerical prediction systems. Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios, it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings. RSMCs, TCWCs, and other forecast centers value probabilistic guidance for TCs, but the International Workshop on Tropical Cyclones (IWTC-9) found that the “pull-through” of probabilistic information to operational warnings using those forecasts is slow. IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products (TC-PFP) project, which is also endorsed as a WMO Seamless GDPFS Pilot Project. The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts. TC-PFP is being implemented in 3 phases: Phase 1 (TC formation and position); Phase 2 (TC intensity and structure); and Phase 3 (TC related rainfall and storm surge). This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position. There is considerable variability in the nature and interpretation of forecast products based on ensemble information, making it challenging to transfer knowledge of best practices across forecast centers. Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices. Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts. Finally, forecast centers need timely access to ensemble information that has consistent, user-friendly ensemble information. Greater consistency across forecast centers in data accessibility, probabilistic forecast products, and warnings and their communication to users will produce more reliable information and support improved outcomes

Achievement of VGPR to induction therapy is an important prognostic factor for longer PFS in the IFM 2005-01 trial.

In the 2005-01 trial, we have demonstrated that bortezomib-dexamethasone as induction therapy before autologous stem cell transplantation was superior to vincristine-adriamycin-dexamethasone. We conducted a post-hoc analysis to assess the prognostic impact of initial characteristics as well as response to therapy in patients enrolled in this study. Multivariate analysis showed that ISS stages 2 and 3 and achievement of response less than very good partial response (VGPR) both after induction therapy and after autologous stem cell transplantation were adverse prognostic factors for progression-free survival, the most important one being achievement of response less than VGPR after induction. Progression-free survival was significantly improved with bortezomib-dexamethasone induction therapy in patients with poor-risk cytogenetics and ISS stages 2 and 3 compared with vincristine-adriamycin-dexamethasone. In these 2 groups of patients, achievement of at least VGPR after induction was of major importance. This study is registered with EudraCT (https://eudract.ema.europa.eu; EUDRACT 2005-000537-38) and http://clinicaltrials.gov (NCT00200681)