Deutsch
 
Benutzerhandbuch Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Impact of surface conditions on thin sea ice concentration estimate from passive microwave observations

MPG-Autoren
Es sind keine MPG-Autoren in der Publikation vorhanden
Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Shokr, M., & Kaleschke, L. (2012). Impact of surface conditions on thin sea ice concentration estimate from passive microwave observations. REMOTE SENSING OF ENVIRONMENT, 121, 36-50. doi:10.1016/j.rse.2012.01.005.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0019-92FA-F
Zusammenfassung
Ice concentration retrieved from spaceborne passive microwave observations is a prime input to operational sea ice monitoring programs, numerical weather prediction and global climate models. However, it is usually underestimated by existing algorithms due to surface conditions, especially in case of young ice types. Evaluation of those algorithms identifies errors in concentration estimates but does not necessarily link them to the adverse surface conditions. The present study is an attempt to establish those links for young ice (<25 cm) thick It uses measurements of microwave emission from artificially grown sea ice in an outdoor tank and calculates ice concentration using five established algorithms: NT, Bootstrap (BSA), NT2, ASI and ECICE. Since the actual concentration is known (100%), then any deviation from this value is considered an error and can be linked to the observed surface conditions, which are usually caused by weather events. Those conditions were acquired on hourly or daily basis. Results identify key conditions that lead to underestimation of ice concentration. They include surface refreezing, slush, snow settling following fresh snowfall, and falling precipitation in different forms. The study shows also that NT and NT2 are most affected by surface processes while BSA performs better. ASI is much less affected because it uses the high frequency channel (e.g. SSM/I 85 GHz), which is sensitive only to processes within the top snow layer. ECICE, with its probabilistic and ensemble approach shows also good results under most surface conditions. Dry or wet snow does not lead to significant difference in ice concentration estimate. The study also aims at validation of ECICE. (c) 2012 Elsevier Inc. All rights reserved.