Search results for "Forecast"
showing 10 items of 417 documents
Automatic generation of emissivity maps on a European scale
2009
The remote sensing measurement of the land surface temperature from satellites provides an overview of this magnitude on a continuous and regular basis. The study of its evolution in time and space is a critical factor in many scientific fields such as weather forecasting, detection of forest fires, climate change, and so on. The main problem of making this measurement from satellite data is the need to correct the effects of the atmosphere and the surface emissivity. In this work, these corrections have been made using a split-window algorithm. The aim was to define an enhanced vegetation cover method and develop a system that used it, in order to automatically generate maps of land surfac…
Proposal and Validation of an Emissivity-Dependent Algorithm to Retrieve Sea-Surface Temperature From MSG-SEVIRI Data
2010
A frequent and accurate determination of sea-surface temperature (SST) would permit an improvement in both the forecasting of natural hazards and the monitoring of the effects of climate change. The Meteosat Second Generation (MSG) spinning enhanced visible and infrared imager (SEVIRI) (MSG-SEVIRI) offers this possibility, since it has a temporal resolution of 15 min. Current algorithms for SST retrieval from MSG-SEVIRI data use angular-dependent coefficients, but they do not use sea-surface emissivity (SSE) as an explicit input. This letter proposes a both angular- and emissivity-dependent split-window equation, together with simple equations to estimate SSE and atmospheric water-vapor con…
The Satellite Application Facility for Land Surface Analysis
2011
Information on land surface properties finds applications in a range of areas related to weather forecasting, environmental research, hazard management and climate monitoring. Remotely sensed observations yield the only means of supplying land surface information with adequate time sampling and a wide spatial coverage. The aim of the Satellite Application Facility for Land Surface Analysis (Land-SAF) is to take full advantage of remotely sensed data to support land, land-atmosphere and biosphere applications, with emphasis on the development and implementation of algorithms that allow operational use of data from European Organization for the Exploitation of Meteorological Satellites (EUMET…
Automatic classification-based generation of thermal infrared land surface emissivity maps using AATSR data over Europe
2012
The remote sensing measurement of land surface temperature from satellites provides a monitoring of this magnitude on a continuous and regular basis, which is a critical factor in many research fields such as weather forecasting, detection of forest fires or climate change studies, for instance. The main problem of measuring temperature from space is the need to correct for the effects of the atmosphere and the surface emissivity. In this work an automatic procedure based on the Vegetation Cover Method, combined with the GLOBCOVER land surface type classification, is proposed. The algorithm combines this land cover classification with remote sensing information on the vegetation cover fract…
Identification and Handling of Critical Irradiance Forecast Errors Using a Random Forest Scheme – A Case Study for Southern Brazil
2015
Abstract Large forecast errors of solar power prediction cause challenges for the management of electric grids. Here, the classification technique Random Forests is applied to analyze the possible linkage of hourly or daily forecast errors to the actual situation given by a set of meteorological variables. This form a prediction of the forecast error and is thus usable to update the forecast. The performance of this scheme is assessed for the example of irradiance forecasts in Brazil. While limited to none improvements are obtained for next-hour forecasts, significant improvements are obtained for the next-day forecasts.
Could the recent zika epidemic have been predicted?
2017
AbstractGiven knowledge at the time, the recent 2015-2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction was for potential risk of an Aedes-borne disease epidemic. Here we use a recently published two-vector capacity model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potenti…
Incidence and predictive factors for perforation of the maxillary antrum in operations to remove upper wisdom teeth: prospective multicentre study.
2006
Our aim was to evaluate the incidence of perforations of the sinuses and their related treatment after the removal of upper wisdom teeth depending on various anatomical and clinical variables.A total of 1057 upper wisdom teeth were removed under local anaesthetic in the departments of oral surgery at the Universities of Bonn, Düsseldorf, Frankfurt and Mainz, Germany. Data were collected with the help of an anonymised questionnaire dealing with information about the patients, and the position and stage of the development of teeth, as well as the occurrence and size of an oro-antral communication and its treatment.Of 465 extractions and 592 osteotomies of the upper third molars, 134 intervent…
Association between climate and new daily diagnoses of COVID-19
2020
AbstractBackgroundAlthough evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks, uncertainty remains concerning the real impact of climate factors on viral transmission. Methods. The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region, while information on daily weather parameters in the same area was downloaded from IlMeteo website, a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 to November 11, 2020. The number of new daily COVID-19 cases and meteorological da…
Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team
2021
Abstract COVID-19 disrupted international tourism worldwide, subsequently presenting forecasters with a challenging conundrum. In this competition, we predict international arrivals for 20 destinations in two phases: (i) Ex post forecasts pre-COVID; (ii) Ex ante forecasts during and after the pandemic up to end 2021. Our results show that univariate combined with cross-sectional hierarchical forecasting techniques (THieF-ETS) outperform multivariate models pre-COVID. Scenarios were developed based on judgemental adjustment of the THieF-ETS baseline forecasts. Analysts provided a regional view on the most likely path to normal, based on country-specific regulations, macroeconomic conditions,…
Stochastic Nonlinear Time Series Forecasting Using Time-Delay Reservoir Computers: Performance and Universality
2014
International audience; Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay diFFerential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We …