Modeling glacier‐surface albedo across Svalbard for the 1979–2015 period: The HiRSvaC500‐α data set

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Marco Möller, Rebecca Möller
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2017
• Subjects: Albedo; HiRSvaC500; geostatistical modeling; Svalbard; Arctic; Physical geography; GB3-5030; Oceanography; GC1-1581; albedo; Arctic Archipelago; glacier
• Online Access: https://doi.org/10.1002/2016MS000752; https://doaj.org/article/28408919e6c04b22b9d527a098517cde

Abstract Albedo is an important quantity for determining the energy balance of snow and ice surfaces and thus also for the mass balance of glaciers. It is especially important in polar regions where shortwave radiation fluxes typically provide most of the energy input to a glacier. In order to use albedo data in any spatially distributed glaciological modeling, it is vital that the albedo fields are not only of high accuracy but also available on sufficiently high spatial resolution and in a manner that is consistent over time. This article presents the newly developed data set HiRSvaC500‐α, which provides daily updated, gapless albedo fields for all glacierized areas of the Arctic archipelago Svalbard on a 500 m resolution over the period 1979–2015. Albedo modeling for creation of the data set is done using a multistep geostatistical approach on the basis of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data and gridded ERA‐Interim climate data. Validation of the modeled HiRSvaC500‐α albedo fields against in situ albedo measurements at automatic weather stations operated on two different glaciers suggests that the accuracy of the newly developed data set lies close to that of remotely sensed MODIS albedo data. An analysis of the HiRSvaC500‐α albedo data set yields a mean annual‐average albedo of 0.754 across all glaciers of Svalbard over 1979–2015. A decrease of albedo with time is found, following a highly significant (95% level) trend of −0.010 per decade. For certain subregions, this trend even reaches up to −0.014 per decade.