Centre de documentation
scientifique

Using remote sensing data to develop seasonal outlooks for Arctic regional sea-ice minimum extent / S. Drobot in Remote sensing of environment, vol 111 n° 2-3 (30 November 2007)  

Public [article]  inRemote sensing of environment > vol 111 n° 2-3 (30 November 2007) . - pp 136 - 147 Titre : Using remote sensing data to develop seasonal outlooks for Arctic regional sea-ice minimum extent Type de document : Article/Communication Auteurs : S. Drobot, Auteur Année de publication : 2007 Article en page(s) : pp 136 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Arctique [Termes IGN] Canada [Termes IGN] épaisseur de la glace [Termes IGN] glace de mer [Termes IGN] prévision à court terme [Termes IGN] régression linéaire [Termes IGN] variation saisonnière Résumé : (Auteur) This paper discusses the development of simple multiple linear regression (MLR) models for developing seasonal forecasts of the annual minimum sea-ice extent in the Beaufort/Chukchi Seas, the Laptev/East Siberian Seas, the Kara/Barents Seas, and the Canadian Arctic Archipelago regions. The potential predictor data are based on mean monthly weighted indices of sea-ice concentration, multiyear sea-ice concentration, surface skin temperature, surface albedo, and downwelling longwave radiation flux at the surface. Predictions are developed based on data available in March (spring forecast), to coincide with the National American Ice Service's annual outlooks, and based on data available in June (summer forecast), which would provide a seasonal revision. The final regression equations retain one to three predictors, and each of the MLR models is superior to climatology. The r2 for the MLR models range from a low of 0.44 (for the spring forecast in the Canadian Arctic Archipelago) to a high of 0.80 (for the summer forecast in the Beaufort/Chukchi Seas). Copyright Elsevier Numéro de notice : A2007-486 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.03.024 En ligne : https://doi.org/10.1016/j.rse.2007.03.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28849 [article]