The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts

<p>A new object-oriented method has been developed to detect hazardous phenomena predicted by Numerical Weather Prediction (NWP) models. This method, called similarity-based method, is looking for specific meteorological objects in the forecasts, which are defined by a reference histogram repr...

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Main Authors: L. Rottner, P. Arbogast, M. Destouches, Y. Hamidi, L. Raynaud
Format: Article
Language:English
Published: Copernicus Publications 2019-09-01
Series:Advances in Science and Research
Online Access:https://www.adv-sci-res.net/16/209/2019/asr-16-209-2019.pdf
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author L. Rottner
P. Arbogast
M. Destouches
Y. Hamidi
L. Raynaud
author_facet L. Rottner
P. Arbogast
M. Destouches
Y. Hamidi
L. Raynaud
author_sort L. Rottner
collection DOAJ
description <p>A new object-oriented method has been developed to detect hazardous phenomena predicted by Numerical Weather Prediction (NWP) models. This method, called similarity-based method, is looking for specific meteorological objects in the forecasts, which are defined by a reference histogram representing the meteorological phenomena to be detected. The similarity-based method enables to cope with small scale unpredictable details of mesoscale structures in meteorological models and to quantify the uncertainties on the location of the predicted phenomena. Applied to ensemble forecasts, the similarity-based method can be viewed as a particular case of neighborhood processing, allowing spatialized probabilities to be computed. An application to rainfall detection using forecasts from the AROME deterministic and ensemble models is presented.</p>
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spelling doaj.art-50eb7955a02244b58880617e439621272022-12-21T19:35:32ZengCopernicus PublicationsAdvances in Science and Research1992-06281992-06362019-09-011620921310.5194/asr-16-209-2019The similarity-based method: a new object detection method for deterministic and ensemble weather forecastsL. RottnerP. ArbogastM. DestouchesY. HamidiL. Raynaud<p>A new object-oriented method has been developed to detect hazardous phenomena predicted by Numerical Weather Prediction (NWP) models. This method, called similarity-based method, is looking for specific meteorological objects in the forecasts, which are defined by a reference histogram representing the meteorological phenomena to be detected. The similarity-based method enables to cope with small scale unpredictable details of mesoscale structures in meteorological models and to quantify the uncertainties on the location of the predicted phenomena. Applied to ensemble forecasts, the similarity-based method can be viewed as a particular case of neighborhood processing, allowing spatialized probabilities to be computed. An application to rainfall detection using forecasts from the AROME deterministic and ensemble models is presented.</p>https://www.adv-sci-res.net/16/209/2019/asr-16-209-2019.pdf
spellingShingle L. Rottner
P. Arbogast
M. Destouches
Y. Hamidi
L. Raynaud
The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
Advances in Science and Research
title The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
title_full The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
title_fullStr The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
title_full_unstemmed The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
title_short The similarity-based method: a new object detection method for deterministic and ensemble weather forecasts
title_sort similarity based method a new object detection method for deterministic and ensemble weather forecasts
url https://www.adv-sci-res.net/16/209/2019/asr-16-209-2019.pdf
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