Search results for " Forecasting"
showing 10 items of 163 documents
Hydrological post-processing based on approximate Bayesian computation (ABC)
2019
[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or …
Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast
2016
Abstract Wind has been the largest contributor to the growth of renewal energy during the early 21st century. However, the natural uncertainty that arises in assessing the wind resource implies the occurrence of wind power forecasting errors which perform a considerable role in the impacts and costs in the wind energy integration and its commercialization. The main goal of this paper is to provide a deeper insight in the analysis of timing errors which leads to the proposal of a new methodology for its control and measure. A new methodology, based on Dynamic Time Warping, is proposed to be considered in the estimation of accuracy as attribute of forecast quality. A new dissimilarity measure…
RAMS-forecasts comparison of typical summer atmospheric conditions over the Western Mediterranean coast
2014
Abstract The Regional Atmospheric Modeling System (RAMS) has been used in order to perform a high-resolution numerical simulation of two meteorological events related to the most common atmospheric environments during the summer over the Western Mediterranean coast: mesoscale circulations and western synoptic advections. In this regard, we take advantage of the operational RAMS configuration running within the real-time forecasting system environment already implemented over this Mediterranean area, precisely in the Valencia Region and nearby areas. The attention of this paper is especially focused on identifying the main features of both events and the ability of the model in resolving the…
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…
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…
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,…
Flexible Data Driven Inventory Management with Interactive Multiobjective Lot Size Optimization
2021
We study data-driven decision support and formalise a path from data to decision making. We focus on lot sizing in inventory management with stochastic demand and propose an interactive multi-objective optimisation approach. We forecast demand with a Bayesian model, which is based on sales data. After identifying relevant objectives relying on the demand model, we formulate an optimisation problem to determine lot sizes for multiple future time periods. Our approach combines different interactive multi-objective optimisation methods for finding the best balance among the objectives. For that, a decision maker with substance knowledge directs the solution process with one’s preference inform…