Publikationsdatum:
2017
Beschreibung:
〈div data-abstract-type="normal"〉〈p〉Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction 〈span〉f〈/span〉〈span〉p〈/span〉 has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of 〈span〉f〈/span〉〈span〉p〈/span〉 as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict 〈span〉f〈/span〉〈span〉p〈/span〉 during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring 〈span〉f〈/span〉〈span〉p〈/span〉, detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of 〈span〉f〈/span〉〈span〉p〈/span〉 from Sentinel-1 data are provided (〈span〉r〈/span〉〈span〉2〈/span〉 ≥ 0.72). The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted 〈span〉f〈/span〉〈span〉p〈/span〉 is generally representative of major ice types first-year ice and multiyear ice during the stage in seasonal melt pond evolution where 〈span〉f〈/span〉〈span〉p〈/span〉 is closely related to spatial variations in ice topography.〈/p〉〈/div〉
Print ISSN:
0260-3055
Digitale ISSN:
1727-5644
Thema:
Geographie
,
Geologie und Paläontologie
Permalink
