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A Historic Record of Sea Ice Extents from Scatterometer Data
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Sea ice is a vital component of the cryosphere and does not only influence the polar regions but has a more global influence. Indeed, sea ice plays a major role in the regulation of the global climate system as the sea ice cover reflects the sun radiation back to the atmosphere keeping the polar regions cool. The shrinkage of the sea ice cover entails the warming up of the oceans and as a consequence, a further amplification of the melting of sea ice. Therefore, the polar regions are sensitive to climate change and monitoring the sea ice cover is very important.

To assess sea ice change in the polar regions, satellite active microwave sensors, scatterometers, are used to observe the evolution of sea ice extent and sea ice types. Thus, this research aims at creating a historic record of daily global Arctic and Antarctic sea ice extents and analysing the change in sea ice types with scatterometer data.

A Bayesian sea ice detection algorithm, developed for the Advanced scatterometer (ASCAT), is applied and tuned to the configurations of the scatterometers on board the European Remote Sensing satellites, ERS\textendash 1 and ERS\textendash 2. The sea ice geophysical model functions (GMFs) of ERS and ASCAT are studied together to validate the use of ASCAT sea ice GMF extrapolated to the lower incidence angles of ERS. The main adaptations from the initial algorithm aim at compensating for the lower observation densities afforded by ERS with a refined spatial filter and time\textendash variable detection thresholds. To further analyse the backscatter response from sea ice and derive information on the different sea ice types, a new model of sea ice backscattering at C\textendash band is proposed in this study. This model has been derived using ERS and ASCAT backscatter data and describes the variation of sea ice backscatter with incidence angle as a function of sea ice type.

The improvement of the sea ice detection algorithm for ERS\textendash 1 and ERS\textendash 2, operating between 1992 and 2001, leads to the extension of the existing records of daily global sea ice extents from the Quick scatterometer (QuikSCAT) which operated from 1999 to 2009 and ASCAT operating from 2007 onwards. The sea ice extents from ERS, QuikSCAT and ASCAT show excellent agreement during the overlapping periods, attesting to the consistency and homogeneity of the long\textendash term scatterometer sea ice record. The new climate record is compared against passive microwave derived sea ice extents, revealing consistent differences between spring and summer which are attributed to the lower sensitivity of the passive microwave technique to melting sea ice. The climate record shows that the minimum Arctic summer sea ice extent has been declining, reaching the lowest record of sea ice extent in 2012.

The new model for sea ice backscatter is used on ERS and ASCAT backscatter data and provides a more precise normalization of sea ice backscatter than was previously available. An application of this model in sea ice change analysis is performed by classifying sea ice types based on their normalized backscatter values. This analysis reveals that the extent of multi\textendash year Arctic sea ice has been declining remarkably over the period covered by scatterometer observations.

Place, publisher, year, edition, pages
2017. , p. 76
Series
TRITA-GIT EX ; 17-002
Keywords [en]
sea ice, radar scattering, scatterometer
National Category
Remote Sensing Climate Research
Identifiers
URN: urn:nbn:se:kth:diva-205237OAI: oai:DiVA.org:kth-205237DiVA, id: diva2:1088299
External cooperation
Royal Netherlands Meteorological Institute (KNMI)
Subject / course
Geoinformatics
Educational program
Degree of Master - Environmental Engineering and Sustainable Infrastructure
Supervisors
Examiners
Available from: 2017-04-13 Created: 2017-04-12 Last updated: 2017-04-13Bibliographically approved

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