A Compilation of Snow Cover Datasets for Svalbard: A Multi-Sensor, Multi-Model Study

Reliable and accurate mapping of snow cover are essential in applications such as water resource management, hazard forecasting, calibration and validation of hydrological models and climate impact assessments. Optical remote sensing has been utilized as a tool for snow cover monitoring over the last several decades. However, consistent long-term monitoring of snow cover can be challenging due to differences in spatial resolution and retrieval algorithms of the different generations of satellite-based sensors. Snow models represent a complementary tool to remote sensing for snow cover monitoring, being able to fill in temporal and spatial data gaps where a lack of observations exist. This study utilized three optical remote sensing datasets and two snow models with overlapping periods of data coverage to investigate the similarities and discrepancies in snow cover estimates over Nordenskiöld Land in central Svalbard. High-resolution Sentinel-2 observations were utilized to calibrate a 20-year MODIS snow cover dataset that was subsequently used to correct snow cover fraction estimates made by the lower resolution AVHRR instrument and snow model datasets. A consistent overestimation of snow cover fraction by the lower resolution datasets was found, as well as estimates of the first snow-free day (FSFD) that were, on average, 10–15 days later when compared with the baseline MODIS estimates. Correction of the AVHRR time series produced a significantly slower decadal change in the land-averaged FSFD, indicating that caution should be exercised when interpreting climate-related trends from earlier lower resolution observations. Substantial differences in the dynamic characteristics of snow cover in early autumn were also present between the remote sensing and snow model datasets, which need to be investigated separately. This work demonstrates that the consistency of earlier low spatial resolution snow cover datasets can be improved by using current-day higher resolution datasets.

[1]  G. Blöschl,et al.  The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models , 2008 .

[2]  Laurent Bertino,et al.  Evaluating satellite retrieved fractional snow-covered area at a high-Arctic site using terrestrial photography , 2020 .

[3]  David J. Selkowitz,et al.  Prevalence of Pure Versus Mixed Snow Cover Pixels across Spatial Resolutions in Alpine Environments , 2014, Remote. Sens..

[4]  Eirik Malnes,et al.  A 20-Year MODIS-Based Snow Cover Dataset for Svalbard and Its Link to Phenological Timing and Sea Ice Variability , 2020, Remote. Sens..

[5]  V. Salomonson,et al.  Estimating fractional snow cover from MODIS using the normalized difference snow index , 2004 .

[6]  Anne W. Nolin,et al.  Recent advances in remote sensing of seasonal snow , 2010, Journal of Glaciology.

[7]  J. Oerlemans,et al.  Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model , 2012 .

[8]  L. Andreassen,et al.  Improving runoff modelling using satellite-derived snow covered area? , 2007 .

[9]  V. Pohjola,et al.  Accelerating future mass loss of Svalbard glaciers from a multi-model ensemble , 2021, Journal of Glaciology.

[10]  Karl-Göran Karlsson,et al.  CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data , 2016 .

[11]  G. McCabe,et al.  Assimilation of snow covered area information into hydrologic and land-surface models , 2006 .

[12]  R. Benestad,et al.  Temperature and Precipitation Development at Svalbard 1900-2100 , 2011 .

[13]  Stefan Dech,et al.  Remote sensing of snow – a review of available methods , 2012 .

[14]  Thomas H. Painter,et al.  Assessment of methods for mapping snow cover from MODIS , 2011 .

[15]  C. De Michele,et al.  Cloud obstruction and snow cover in Alpine areas from MODIS products , 2014 .

[16]  Günter Blöschl,et al.  Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments , 2007 .

[17]  Xinghua Li,et al.  The recent developments in cloud removal approaches of MODIS snow cover product , 2019, Hydrology and Earth System Sciences.

[18]  Olivier Hagolle,et al.  A snow cover climatology for the Pyrenees from MODIS snow products , 2014 .

[19]  Olivier Hagolle,et al.  Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index , 2020, Remote. Sens..

[20]  J. Hagen,et al.  A long-term dataset of climatic mass balance, snow conditions, and runoff in Svalbard (1957–2018) , 2019, The Cryosphere.

[21]  J. Dozier.  Spectral Signature of Alpine Snow Cover from the Landsat Thematic Mapper , 1989 .

[22]  Chris Derksen,et al.  Evaluation of spring snow covered area depletion in the Canadian Arctic from NOAA snow charts , 2005 .

[23]  T. Saloranta.  Operational snow mapping with simplified data assimilation using the seNorge snow model , 2016 .