Icelandic snow cover characteristics derived from a gap-filled MODIS daily snow cover product

dc.contributorHáskóli Íslandsen_US
dc.contributorUniversity of Icelanden_US
dc.contributor.authorGunnarsson, Andri
dc.contributor.authorGardarsson, Sigurdur
dc.contributor.authorSveinsson, Óli G. B.
dc.contributor.departmentUmhverfis- og byggingarverkfræðideild (HÍ)en_US
dc.contributor.departmentFaculty of Civil and Environmental Engineering (UI)en_US
dc.contributor.schoolVerkfræði- og náttúruvísindasvið (HÍ)en_US
dc.contributor.schoolSchool of Engineering and Natural Sciences (UI)en_US
dc.date.accessioned2020-03-31T08:29:08Z
dc.date.available2020-03-31T08:29:08Z
dc.date.issued2019-07-17
dc.descriptionPublisher's version (útgefin grein)en_US
dc.description.abstractThis study presents a spatiooral continuous data set for snow cover in Iceland based on the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2018. Cloud cover and polar darkness are the main limiting factors for data availability of remotely sensed optical data at higher latitudes. In Iceland the average cloud cover is 75 % with some spatial variations, and polar darkness reduces data availability from the MODIS sensor from late November until mid January. In this study MODIS snow cover data were validated over Iceland with comparison to manned in situ observations and Landsat 7/8 and Sentinel 2 data. Overall a good agreement was found between in situ observed snow cover, with an average agreement of 0.925. Agreement of Landsat 7/8 and Sentinel 2 was found to be acceptable, with R2 values 0.96, 0.92 and 0.95, respectively, and in agreement with other studies. By applying daily data merging from Terra and Aqua and a temporal aggregation of 7 d, unclassified pixels were reduced from 75 % to 14 %. The remaining unclassified pixels after daily merging and temporal aggregation were removed with classification learners trained with classified data, pixel location, aspect and elevation. Various snow cover characteristic metrics were derived for each pixel such as snow cover duration, first and last snow-free dates, deviation and dynamics of snow cover and trends during the study period. On average the first snow-free date in Iceland is 27 June, with a standard deviation of 19.9 d. For the study period a trend of increasing snow cover duration was observed for all months except October and November. However, statistical testing of the trends indicated that there was only a significant trend in June.en_US
dc.description.sponsorshipWe would like to thank Jessica D. Lundquist, University of Washington, for discussion and valuable feedback during the design of the study. Special thanks to Helgi Jóhannes-son, project manager at Landsvirkjun, for providing constructive feedback during review of the manuscript. The Valle Scholarship and Scandinavian Exchange Program at the University of Washington is also thanked for financial support during the academic year 2017–2018 at the University of Washington.en_US
dc.description.versionPeer Revieweden_US
dc.format.extent3021-3036en_US
dc.identifier.citationGunnarsson, A. M., Gararsson, S. G., & Sveinsson, &. (2019). Icelandic snow cover characteristics derived from a gap-filled MODIS daily snow cover product. Hydrology and Earth System Sciences, 23(7), 3021-3036.en_US
dc.identifier.doi10.5194/hess-23-3021-2019
dc.identifier.issn1607-7938
dc.identifier.journalHydrology and Earth System Sciencesen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11815/1676
dc.language.isoenen_US
dc.publisherCopernicus GmbHen_US
dc.relation.ispartofseriesHydrology and Earth System Sciences;23(7)
dc.relation.urlhttps://www.hydrol-earth-syst-sci.net/23/3021/2019/hess-23-3021-2019.pdfen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSnjóalögen_US
dc.subjectSnjómælingaren_US
dc.subjectFjarkönnunen_US
dc.titleIcelandic snow cover characteristics derived from a gap-filled MODIS daily snow cover producten_US
dc.typeinfo:eu-repo/semantics/articleen_US
dcterms.licenseThis work is distributed under the Creative Commons Attribution 4.0 License.en_US

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