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The Madden–Julian oscillation (MJO), a prominent feature of the tropical atmospheric circulation at sub seasonal time scales, is known to modulate atmospheric variability in the Euro-Atlantic region. However, current sub seasonal prediction systems fail to accurately reproduce the physical processes involved in these teleconnection mechanisms. This paper explores the observed impact of strong MJO events on surface wind speed over Europe. It is found that some MJO phases are accompanied by strong wind anomalies in Europe. After showing that this teleconnective mechanism is not present in the predictions of the ECMWF monthly forecasting system, a methodology to reconstruct forecasts of daily mean wind speed in the continent weeks ahead is proposed. This method combines MJO forecasts from the S2S project database and the observed teleconnection impacts in the historical records. Although it is found that strong MJO events cannot be skillfully predicted more than 10 days ahead with current prediction systems, a theoretical experiment shows that this method can effectively transform a dynamical MJO forecast into a probabilistic wind speed prediction in Europe. [ABSTRACT FROM AUTHOR]

This paper presents an approach to postprocess ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical postprocessing of ensemble predictions are tested: the first approach is based on multinomial logistic regression and the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on stationwise postprocessing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. [ABSTRACT FROM AUTHOR]

This paper presents the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which has been developed for use in mountainous terrain. Analysis and nowcasting fields include temperature, humidity, wind, precipitation amount, precipitation type, cloudiness, and global radiation. The analysis part of the system combines surface station data with remote sensing data in such a way that the observations at the station locations are reproduced, whereas the remote sensing data provide the spatial structure for the interpolation. The nowcasting part employs classical correlation-based motion vectors derived from previous consecutive analyses. In the case of precipitation the nowcast includes an intensity-dependent elevation effect. After 2--6 h of forecast time the nowcast is merged into an NWP forecast provided by a limited-area model, using a predefined temporal weighting function. Cross validation of the analysis and verification of the nowcast are performed. Analysis quality is high for temperature, but comparatively low for wind and precipitation, because of the limited representativeness of station data in mountainous terrain, which can be only partially compensated by the analysis algorithm. Significant added value of the system compared to the NWP forecast is found in the first few hours of the nowcast. At longer lead times the effects of the latest observations becomes small, but in the case of temperature the downscaling of the NWP forecast within the INCA system continues to provide some improvement compared to the direct NWP output. [ABSTRACT FROM AUTHOR]

The current state of the art in three-dimensional chemistry-transport models allows them to be considered as mature and reliable enough to be combined with observations networks for implementing integrated air quality monitoring systems over large territories. A cooperative initiative of tour research and operational organizations in France has led to the creation of an integrated air quality platform providing near-real-time and forecasted information using last model developments. Since summer 2003, this system, Prévisions et Observations de la Qualité de l'Air en France et en Europe (PRBV AIR; available online at www.prevair. org), has been delivering daily air quality observations short-term (0-3 days) forecasts, and real-time analyses of ozone, nitrogen dioxide, and particulate matter (PM) at the global and European scales, with a focus over France. It has become a powerful scientific and communication tool to inform the public, sensitive population about the potential occurrence of air pollutant concentrations exceeding regulatory thresholds. The architecture of the operational system is described in this paper. Its setup allows the partners to cope with stringent operational constraints regarding the timely availability of the forecasts and the reliability and the quality of the products delivered. The system relies on a chain of numerical models and methods, and on real-time air quality observations, it uses National Centers for Environmental Predictions (NCEP) and Météo-France weather forecasts. Methods used for producing air pollutant concentration forecasts and analyses are described, as well as the final products, with case examples. A synthesis of the operational system skill results obtained over three consecutive years of operation (2003-06) is given. Lessons learned are presented and issues related to the use of the PREV'AIR system as a complementary tool for air quality management are discussed. [ABSTRACT FROM AUTHOR]