Summary: | The topic of this dissertation is the study of Arctic snow and ice albedo based on satellite observations. Surface albedo timeseries based on data from the AVHRR instrument family were produced, validated, and analyzed as part of the work. Of note was the production of a 28-year (1982-2009) dataset on global surface albedo from homogenized satellite data, the longest such timeseries to date.In conjunction with the dataset validation, new methods were developed to improve the reliability of the calculated dataset quality estimate. Specifically, a new method for numerically assessing the representativeness of ground truth observations at the scale of the satellite field of view was introduced. The final part of this dissertation deals with the application of the 28-year surface albedo dataset in the calculation of sea ice albedo trends over the Arctic Ocean. The results showed a clear negative trend in both the mean composite open water-sea ice albedo and the mean albedo of the remaining sea ice zone. This decrease was linked to decreasing ice concentrations across the ice zone, increased air temperatures and lengthened melt seasons. The results are significant for investigations of the surface energy budget of the Arctic. The results of this dissertation are of use in the development and validation work of both satellite-based surface albedo datasets and climate models. The created datasets are also useful in observation-based tracking of climate change in the Arctic. Väitöskirjassa tutkittiin Arktisen lumen ja jään heijastavuuden eli albedon määrittämistä satelliittihavainnoista. Työssä on tuotettu AVHRR-radiometrien mittauksiin perustuvia aikasarjoja sekä operatiiviseen käyttöön että ilmastonmuutostutkimukseen. Aikasarjojen laatu on selvitetty maan pinnan referenssimittauksiin verraten. Työssä on myös kehitetty menetelmiä parantamaan aikasarjoille laskettujen laatuarvioiden luotettavuutta. Maan pinnan referenssimittausten vertautuvuutta satelliittimittauksiin voidaan työn tulosten perusteella arvioida entistä ...
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