Search results for "Weather forecasting"
showing 9 items of 19 documents
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…
Automatic Generation of Land Surface Emissivity Maps
2011
The remote sensing measurement of the land surface temperature (LST) 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, etc. The main problem of making this measurement from satellite data is the need to correct the effects of the atmosphere and the land surface emissivity (LSE). Nowadays, these corrections are usually made using a split-window algorithm, which has an explicit dependence on land surface emissivity. Therefore, the aim of our work was to define an enhanced vegetation cover met…
Visualizing Confidence in Cluster-based Ensemble Weather Forecast Analyses
2020
In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we — a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enab…
SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product
2017
© 2017 by the authors. The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product that was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d'Etudes Spatiales de la BIOsphère). One of the main go…
Electricity load forecasting for Urban area using weather forecast information
2016
The global demand for energy is increasing daily with the expansion of energy infrastructure and the addition of new appliances. Efficient Energy Management System (EMS) is the need of the day. All residential and commercial buildings can achieve better energy efficiency and consumption with the use of EMS. Load forecasting is one of the methods to enable EMS to work efficiently. The accuracy of load forecast depends on many factors. The load forecast model must consider the weather forecast for the region in developing an accurate forecast. This paper develops Artificial Neural Network (ANN) and Bagged Regression Trees to generate and predicted load forecast in Urban area using Meteorologi…
G-CLASS: geosynchronous radar for water cycle science – orbit selection and system design
2019
The mission geosynchronous – continental land atmosphere sensing system (G-CLASS) is designed to study thediurnal water cycle, using geosynchronous radar. Although the water cycle is vital to human society, processes on timescalesless than a day are very poorly observed from space. G-CLASS, using C-band geosynchronous radar, could transform this. Itsscience objectives address intense storms and high resolution weather prediction, and significant diurnal processes such assnow melt and soil moisture change, with societal impacts including agriculture, water resource management, flooding, andlandslides. Secondary objectives relate to ground motion observations for earthquake, volcano, and subs…