Search results for "forecast"
showing 10 items of 417 documents
Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo, Italy
2007
Abstract Artificial neural networks are functional alternative techniques in modelling the intricate vehicular exhaust emission dispersion phenomenon. Pollutant predictions are notoriously complex when using either deterministic or stochastic models, which explains why this model was developed using a neural network. Neural networks have the ability to learn about non-linear relationships between the used variables. In this paper a recurrent neural network (Elman model) based forecaster for the prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the city of Palermo is proposed. The effectiveness of the presented forecaster was tested using a time series recorded between …
Performance of DEMETER calibration for rainfall forecasting purposes: Application to the July–August Sahelian rainfall
2008
International audience; This work assesses and compares the skill of direct and model-output-statistics (MOS) calibrated hindcasts of the July–August rainfall amounts for the dry period 1980–2000 over the Sahel issued from the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER) experiment, with the aim to highlight among the simulated parameters, i.e., those potentially relevant for rainfall forecasts purposes. Three approaches were used: the DEMETER (1) direct rainfall, (2) MOS-calibrated rainfall, and (3) MOS-calibrated atmospheric dynamics and energy. Canonical correlation analyses (CCA) were employed in the two latter approaches to calib…
Extreme, wintertime Saharan dust intrusion in the Iberian Peninsula: Lidar monitoring and evaluation of dust forecast models during the February 2017…
2019
The research leading to these results has received funding from the H2020 program from the European Union (grant agreement no. 654109, 778349) and also from the Spanish Ministry of Industry, Economy and Competitiviness (MINECO, ref. CGL2013-45410-R, CGL2016-81092-R, CGL2017-85344-R, TEC2015-63832-P), the Spanish Ministry of Science, Innovation and Universities (ref. CGL2017-90884-REDT); the CommSensLab "Maria de Maeztu" Unity of Excellence (ref. MDM-2016-0600) financed by the Spanish Agencia Estatal de Investigación. Co-funding was also provided by the European Union through the European Regional Development Fund (ref. POCI-01-0145-FEDER-007690, ALT20-03-0145-FEDER-000004, ALT20-03-0145-FED…
Predicting dengue fever outbreaks in French Guiana using climate indicators
2016
Background Dengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana. Methodology/Principal Findings Lagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical e…
Current and emerging developments in subseasonal to decadal prediction
2020
Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-…
MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
2015
Abstract. This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more…
In vitro fertilization and andrology laboratory in 2030: expert visions.
2021
The aim of this article is to gather 9 thought leaders and their team members to present their ideas about the future of in vitro fertilization and the andrology laboratory. Although we have seen much progress and innovation in the laboratory over the years, there is still much to come, and this article looks at what these leaders think will be important in the future development of technology and processes in the laboratory.
PREVISION JOURNALIERE DES POLLENS SUR LE TERRITOIRE NATIONAL FRANÇAIS, AVEC UN OBJECTIF D'INFORMATION SANITAIRE DES POPULATIONS ALLERGIQUES
2008
At present, 16% of French people suffer from allergies to one or several pollens. The corresponding symptoms can be presented as under benign form (rhinitis, conjunctivitis, cough) as under much more serious form : asthma. Forecast of the starting date of an allergic exposure risk to pollens is necessary from a sanitary and preventive standpoint. Forecast has to be more precisely as possible in order to begin anti-allergic treatments at appropriate moment, with a view of effectiveness and reduction of the costs due to this disease. The present study, taking place in all the French territory, concerns four pollen taxa among the most allergenic : ash, birch, grasses and ragweed. This work com…
A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe
2018
The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and…
Forecasting basketball players' performance using sparse functional data*
2019
Statistics and analytic methods are becoming increasingly important in basketball. In particular, predicting players’ performance using past observations is a considerable challenge. The purpose of this study is to forecast the future behavior of basketball players. The available data are sparse functional data, which are very common in sports. So far, however, no forecasting method designed for sparse functional data has been used in sports. A methodology based on two methods to handle sparse and irregular data, together with the analogous method and functional archetypoid analysis is proposed. Results in comparison with traditional methods show that our approach is competitive and additio…