887 research outputs found
Seasonal predictability of onset and cessation of the east African rains
Get PDFAdvanced warning of delayed onset or early cessation of the rainy seasons would be extremely valuable information for farmers in east Africa and is a common request from regional stakeholders. Such warnings are beginning to be provided, however forecast skill for these metrics has not been demonstrated. Here the forecast skill of the ECMWF seasonal hindcasts is evaluated for onset and cessation forecasts over east Africa. Correlation of forecast with observed long rains anomalies only above a 95% statistical significance level for a small part of the domain, whilst short rains are significance a large part of the region. The added value of updating the forecast outlook with the extended range 46 day forecast is assessed and this gives a small improvement. For the short rains detection of early onset is better near the coast, and late onset detection is better over northwestern Kenya. During exceptionally dry years the method to detect onset and cessation fails. Using this as a definition of a failed season, the model shows significant skill at anticipating long rains season failure in the northwest of Kenya, and short rains failure in Somalia and northeast Kenya. In addition the strength of the correlation between long rains cessation and seasonal total is shown to be particularly weak in observations but too strong in the hindcasts. Predictability of onset and cessation for both seasons appears to arise primarily from the link with seasonal total and it is unclear that the model represents variability in onset and cessation beyond this. This has important implications for operational forecasting: any forecast of season timing which Preprint submitted to Weather and Climate Extremes May 18, 2018 is `inconsistent' with seasonal total (e.g. an early onset but low total rainfall) must be treated with caution. Finally links with zonal winds are investigated. Late onset is correlated with easterly (westerly) anomalies during the long (short) rains, though the strength and spatial pattern of the relationship is is not well represented in the model. Early cessation is correlated with easterly anomalies in both seasons for most of the region in both observations and hindcasts. However for the long rains the sign of the correlation is reversed along the coast in observations but not in the hindcasts. These dynamical inconsistencies may have a negative impact on forecast skill and have the potential to inform process-based development of climate modelling in the region
The moderate impact of the 2015 El Niño over East Africa and its representation in seasonal reforecasts
Get PDFEl Niño–Southern Oscillation (ENSO) has large socioeconomic impacts worldwide. The positive phase of ENSO, El Niño, has been linked to intense rainfall over East Africa during the short rains season (October–December). However, we show here that during the extremely strong 2015 El Niño the precipitation anomaly over most of East Africa during the short rains season was less intense than experienced during previous El Niños, linked to less intense easterlies over the Indian Ocean. This moderate impact was not indicated by reforecasts from the ECMWF operational seasonal forecasting system, SEAS5, which instead forecast large probabilities of an extreme wet signal, with stronger easterly anomalies over the surface of the Indian Ocean and a colder eastern Indian Ocean/western Pacific than was observed. To confirm the relationship of the eastern Indian Ocean to East African rainfall in the forecast for 2015, atmospheric relaxation experiments are carried out that constrain the east Indian Ocean lower troposphere to reanalysis. By doing so the strong wet forecast signal is reduced. These results raise the possibility that link between ENSO and Indian Ocean dipole events is too strong in the ECMWF dynamical seasonal forecast system and that model predictions for the East African short rains rainfall during strong El Niño events may have a bias toward high probabilities of wet conditions
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Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach
Get PDFSoil moisture memory is a key component of seasonal predictability. However, uncertainty in current memory estimates is not clear and it is not obvious to what extent these are dependent on model uncertainties. To address this question, we perform a global sensitivity analysis of memory to key hydraulic parameters, using an uncoupled version of the H-TESSEL land surface model. Results show significant dependency of estimates of memory and its uncertainty on these parameters, suggesting that operational seasonal forecasting models using deterministic hydraulic parameter values are likely to display a narrower range of memory than exists in reality. Explicitly incorporating hydraulic parameter uncertainty into models may then give improvements in forecast skill and reliability, as has been shown elsewhere in the literature. Our results also show significant differences with previous estimates of memory uncertainty, warning against placing too much confidence in a single quantification of uncertainty
Seasonal Climate Prediction: A New Source of Information for the Management of Wind Energy Resources
Get PDFClimate predictions tailored to the wind energy sector represent an innovation in the use of climate information to better manage the future variability of wind energy resources. Wind energy users have traditionally employed a simple approach that is based on an estimate of retrospective climatological information. Instead, climate predictions can better support the balance between energy demand and supply, as well as decisions relative to the scheduling of maintenance work. One limitation for the use of the climate predictions is the bias, which has until now prevented their incorporation in wind energy models because they require variables with statistical properties that are similar to those observed. To overcome this problem, two techniques of probabilistic climate forecast bias adjustment are considered here: a simple bias correction and a calibration method. Both approaches assume that the seasonal distributions are Gaussian. These methods are linear and robust and neither requires parameter estimation—essential features for the small sample sizes of current climate forecast systems. This paper is the first to explore the impact of the necessary bias adjustment on the forecast quality of an operational seasonal forecast system, using the European Centre for Medium-Range Weather Forecasts seasonal predictions of near-surface wind speed to produce useful information for wind energy users. The results reveal to what extent the bias adjustment techniques, in particular the calibration method, are indispensable to produce statistically consistent and reliable predictions. The forecast-quality assessment shows that calibration is a fundamental requirement for high-quality climate service.The authors acknowledge funding support from the RESILIENCE (CGL2013-41055-R) project, funded by the Spanish Ministerio de Economía y Competitividad (MINECO) and the FP7 EUPORIAS (GA 308291) and SPECS (GA 308378) projects. Special thanks to Nube Gonzalez-Reviriego and Albert Soret for helpful comments and discussion.
We also acknowledge the COPERNICUS action CLIM4ENERGY-Climate for Energy (C3S 441 Lot 2) and the New European Wind Atlas (NEWA) project funded from ERA-NET Plus, topic FP7-ENERGY.2013.10.1.2. We acknowledge the s2dverification and SpecsVerification R-based packages. Finally we would like to thank Pierre-Antoine Bretonnière, Oriol Mula and Nicolau
Manubens for their technical support at different stages of this project.Peer ReviewedPostprint (author's final draft
Deduction of probable events of lateral gene transfer through comparison of phylogenetic trees by recursive consolidation and rearrangement
Get PDFBACKGROUND: When organismal phylogenies based on sequences of single marker genes are poorly resolved, a logical approach is to add more markers, on the assumption that weak but congruent phylogenetic signal will be reinforced in such multigene trees. Such approaches are valid only when the several markers indeed have identical phylogenies, an issue which many multigene methods (such as the use of concatenated gene sequences or the assembly of supertrees) do not directly address. Indeed, even when the true history is a mixture of vertical descent for some genes and lateral gene transfer (LGT) for others, such methods produce unique topologies. RESULTS: We have developed software that aims to extract evidence for vertical and lateral inheritance from a set of gene trees compared against an arbitrary reference tree. This evidence is then displayed as a synthesis showing support over the tree for vertical inheritance, overlaid with explicit lateral gene transfer (LGT) events inferred to have occurred over the history of the tree. Like splits-tree methods, one can thus identify nodes at which conflict occurs. Additionally one can make reasonable inferences about vertical and lateral signal, assigning putative donors and recipients. CONCLUSION: A tool such as ours can serve to explore the reticulated dimensionality of molecular evolution, by dissecting vertical and lateral inheritance at high resolution. By this, we mean that individual nodes can be examined not only for congruence, but also for coherence in light of LGT. We assert that our tools will facilitate the comparison of phylogenetic trees, and the interpretation of conflicting data
Seasonal to annual ocean forecasting skill and the role of model and observational uncertainty
Get PDFAccurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten‐month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties
Fibre volume fraction screening of pultruded carbon fibre reinforced polymer panels based on analysis of anisotropic ultrasonic sound velocity
Get PDFComposites have become the material of choice in a wide range of manufacturing applications. Whilst ultrasound inspection is a well-established non-destructive testing (NDT) technique, the application to composite imaging presents significant challenges stemming from the inherent anisotropy of the material. The fibre-volume fraction (FVF) of a composite plays a key role in determining the final strength and stiffness of a part as well as influencing the ultrasonic bulk velocity. In this work, a novel FVF determination technique, based on the angular dependence of the sound velocity with respect to the composite fibre direction, is presented. This method is introduced and validated by inspection of pultruded carbon fibre reinforced polymer (CFRP) panels commonly used in the manufacture of high-power wind turbine blades. Full matrix capture (FMC) data acquired from a phased array (PA) ultrasonic probe is used to generate calibration data for samples ranging in FVF from 60.5 % to 69.9 %. Sample velocity, as a function of propagation angle, is used to estimate the FVF of samples and ensure they fall within the desired range. Experimental results show values of 61.1, 66.1 and 68.3 %, comparing favourably to the known values of 60.5, 66.3 and 69.9 % respectively. The work offers significant potential in terms of factory implementation of NDT procedures to ensure final parts satisfy standards and certification by ensuring any FVF inconsistencies are identified as early in the manufacturing process as possible
Rift Valley Fever Outbreaks in Mauritania and Related Environmental Conditions
Get PDFFour large outbreaks of Rift Valley Fever (RVF) occurred in Mauritania in 1998, 2003, 2010 and 2012 which caused lots of animal and several human deaths. We investigated rainfall and vegetation conditions that might have impacted on RVF transmission over the affected regions. Our results corroborate that RVF transmission generally occurs during the months of September and October in Mauritania, similarly to Senegal. The four outbreaks were preceded by a rainless period lasting at least a week followed by heavy precipitation that took place during the second half of the rainy season. First human infections were generally reported three to five weeks later. By bridging the gap between meteorological forecasting centers and veterinary services, an early warning system might be developed in Senegal and Mauritania to warn decision makers and health services about the upcoming RVF risk
Understanding the patterns of use, motives, and harms of New Psychoactive Substances in Scotland.
Get PDFNew or Novel Psychoactive Substances (NPS) imitate the effects of illegal drugs and are commonly (although misleadingly) referred to as „legal highs‟. Over the last decade the use of NPS has expanded in Scotland. Current data sources and anecdotal reports have identified a number of vulnerable or potentially at risk groups. This report presents results of mixed methods research on NPS use among five key target populations: vulnerable young people, people in contact with mental health services, people affected by homelessness, people who inject drugs (PWID) and men who have sex with men (MSM)
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