Skilful seasonal forecasts of streamflow over Europe?

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the Ensemble Streamflow Prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to seven months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40% of Europe. Patterns in the EFAS seasonal streamflow hindcasts skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim to improve climate-model based seasonal streamflow forecasting

End-to-end service quality for cloud applications

This paper aims to highlight the importance of End-to-End (E2E) service quality for cloud scenarios, with focus on telecom carrier-grade services. In multi-tenant distributed and virtualized cloud infrastructures, enhanced resource sharing raises issues in terms of performance stability and reliability. Moreover, the heterogeneity of business entities responsible for the cloud service delivery, threatens the possibility of offering precise E2E service levels. Setting up proper Service-Level Agreements (SLAs) among the involved players, may become overly challenging. However, problems may be mitigated by a thoughtful intervention of standardization. The paper reviews some of the most important efforts in research and industry to tackle E2E service quality and concludes with some recommendations for additional research and/or standardization effort required to be able to deploy mission critical or interactive real-time services with high demands on service quality, reliability and predictability on cloud platforms. © 2013 Springer International Publishing

Normative data for idiomatic expressions

Peer reviewedPublisher PD

The ECMWF Ensemble Prediction System: Looking Back (more than) 25 Years and Projecting Forward 25 Years

This paper has been written to mark 25 years of operational medium-range ensemble forecasting. The origins of the ECMWF Ensemble Prediction System are outlined, including the development of the precursor real-time Met Office monthly ensemble forecast system. In particular, the reasons for the development of singular vectors and stochastic physics - particular features of the ECMWF Ensemble Prediction System - are discussed. The author speculates about the development and use of ensemble prediction in the next 25 years.Comment: Submitted to Special Issue of the Quarterly Journal of the Royal Meteorological Society: 25 years of ensemble predictio

The predictability of precipitation episodes during the West African dry season

Precipitation episodes in tropical West Africa (7-15°N, 10°W-10°E) during the dry season from November to March are rare, but can have significant impacts on human activities reaching from greening of pastures to spoiling harvests and health implications. Previous work has shown a link between these unseasonal rainfalls and extratropical disturbances via a decrease of surface pressure over the Sahara/Sahel and a subsequent inflow of moist air from the Gulf of Guinea. This paper supports the previously stated hypothesis that the extratropical influence leads to a high rainfall predictability through a careful analysis of operational 5 day forecasts from the European Centre for Medium-Range Weather Forecasts' (ECMWF) ensemble prediction system (EPS), which are evaluated using Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) precipitation estimates for the 11 dry seasons 1998/99-2008/09. The long-term regional average of ensemble-mean precipitation lies between the two observational datasets, with GPCP being considerably wetter. Temporal correlations between the ensemble mean and observations are 0.8. Standard probabilistic evaluation methods such as reliability and relative operating characteristic (ROC) diagrams indicate remarkably good reliability, sharpness and skill across a range of precipitation thresholds. However, a categorical verification focusing on the most extreme ensemble mean values indicates too many false alarms. Despite the considerable observational uncertainty the results show that the ECMWF EPS is capable of predicting winter rainfall events in tropical West Africa with good accuracy, at least on regional spatial and synoptic time-scales, which should encourage West African weather services to capitalize more on the valuable information provided by ensemble prediction systems during the dry season

An Exploratory Study on the Level of Trust towards Online Retailers among Consumers in the United Kingdom and Malaysia

This study aims to investigate the extant level of trust towards online retailers among consumers in two different geographical and cultural locations – UK and Malaysia based on Michell’s et al. trust model. The objectives of this study are: 1. To identify the predictive variables of customers’ trust towards online retailers 2. To ascertain the extent of the consumer trust variable as being the essential element of online shopping 3. To analyse the differences in perception of online trust between consumers in the United Kingdom and Malaysia The study showed that online retailers are comparatively more trusted in UK than in Malaysia indicative by the higher average levels of trust from consumers in the UK. Additionally, the UK had a higher age group in the 25 – 34 category contributing the highest average trust value compared to Malaysia’s highest average trust value found in the lower 18 – 24 age group. There were a relatively higher percentage of male users; 66 per cent and 78 per cent in the UK and Malaysia respectively. Multiple stepwise regressions were used to analyse the level of trust against the selected trust correlates

Fly-By-Wireless for Next Generation Aircraft: Challenges and Potential solutions

”Fly-By-Wireless” paradigm based on wireless connectivity in aircraft has the potential to improve efficiency and flexibility, while reducing weight, fuel consumption and maintenance costs. In this paper, first, the opportunities and challenges for wireless technologies in safety-critical avionics context are discussed. Then, the assessment of such technologies versus avionics requirements is provided in order to select the most appropriate one for a wireless aircraft application. As a result, the design of a Wireless Avionics Network based on Ultra WideBand technology is investigated, considering the issues of determinism, reliability and security

How to reduce the number of rating scale items without predictability loss?

Rating scales are used to elicit data about qualitative entities (e.g., research collaboration). This study presents an innovative method for reducing the number of rating scale items without the predictability loss. The "area under the receiver operator curve method" (AUC ROC) is used. The presented method has reduced the number of rating scale items (variables) to 28.57\% (from 21 to 6) making over 70\% of collected data unnecessary. Results have been verified by two methods of analysis: Graded Response Model (GRM) and Confirmatory Factor Analysis (CFA). GRM revealed that the new method differentiates observations of high and middle scores. CFA proved that the reliability of the rating scale has not deteriorated by the scale item reduction. Both statistical analysis evidenced usefulness of the AUC ROC reduction method.Comment: 14 pages, 5 figure