Science Service System

Summary of Proposal LAN2784

TitleGreenland glaciers acceleration and climate change: intra-seasonal insights
Investigator van Leijen, Freek - Delft University of Technology, Department of Geoscience and Remote Sensing
Team Member
Dr. van Leijen, Freek - Delft University of Technology, Department of Geoscience and Remote Sensing
Dr. Vizcaino, Miren - Delft University of Technology, Department of Geoscience and Remote Sensing
Prof. dr. Hanssen, Ramon - Delft University of Technology, Department of Geoscience and Remote Sensing
Prof. dr. habil. Maas, Hans-Gerd - Technische Universitat Dresden, Institute of Photogrammetry and Remote Sensing
Dr. -Ing. Schwalbe, Ellen - Technische Universitat Dresden, Institute of Photogrammetry and Remote Sensing
SummarySea level rise is one of the major impacts of anthropogenic climate change. At the moment, glaciers and ice sheets are a main contributor to ongoing sea level rise. Of the two ice sheets, the Greenland ice sheet (GrIS) is currently contributing the most, regardless of being one order of magnitude smaller than the Antarctic ice sheet. The GrIS stores an amount of water equivalent to 7.36m of sea level rise [Bamber et al. 2013]. Current mass loss is equivalent to~250 Gt/year, or 0.6 mm/year sea level rise. Both atmospheric and ocean forcing are causing these mass losses [Joughin et al., 2012; van den Broeke et al., 2009]. The mechanisms controlling the observed increasing mass loss are not yet well understood[Joughin et al., 2012]. An important question to answer is whether current trends will be sustained into the future, or what role atmospheric and ocean forcing variability play on explaining these trends [Bamber and Aspinall, 2013;Fettweis et al., 2013; Wouters et al., 2013]. Our project aims to examine the connection between the observed acceleration of Greenland and climate change. Current all-margins GrIS flow datasets typically expand one decade of observations and have annual temporal resolution at the most. This project aims to 1) set the necessary steps to build a high-temporal resolution dataset of GrIS glacier velocities,2) expand our understanding of Arctic glaciers and climate interaction by focusing on ice flow variability at the intra-annual scale. Observational studies on intra-seasonal evolution of ice velocities have been performed only for some selected glaciers, and mainly for land-ice terminating glaciers in the SE, which are the slowest type [Moonet al., 2012; Rignot and Mouginot, 2012]. These studies were aimed to evaluate the role of surface melt in driving glacier acceleration [Joughin et al., 2013;Sundal et al., 2011; van de Wal et al., 2008] In addition to land-terminating glaciers, the GrIS has two other types of glaciers: marine-terminating(fastest, dominant in the SE & NW, and main contributors to observed ice mass loss), and ice shelf-terminating (dominant in N, Peterman Glacier drains the most of ice among them). Ocean interaction is the main driver of change in these glaciers, with surface melt contributing to seasonal variability [Joughinet al., 2008; Sundal et al., 2013]. Our work aims to extend the work of Howatet al., 2010, which examined seasonal variability in the dynamics of sixmarine-terminating outlet glaciers in the Uummannaq region. This study related glacier velocities with atmospheric and ocean variability, finding that high sea-surface temperature, low sea-ice concentrations and reduced sea-ice/iceberg mélange have triggered multi-year retreat of several glaciers in the study area. We will examine the relationship between glacier flow, front position,glacier topography, sea-ice concentration, surface melt and drainage, and oceanography conditions. We plan to use six TerraSAR-X stripmap datasets in the Uummannaq region (180 images) and 2 datasets for the Jakobshavn region (180images) to build glacier velocities with sub-annual resolution. Hence, in total360 images are requested. The TerraSAR-X images, providing high spatial and temporal resolutions (3 m and 11-day, respectively), will be a strong contribution to the overall goals of our project. Other datasets data we will use are Radarsat-2 data (with resolutions of 100 m and 24-days), along with first data from the Sentinel-1 mission. We will apply and evaluate new feature tracking algorithms to support the InSAR analysis of the data. To validate the results, we will compare our SAR/InSAR based estimates with ground truth data acquired by GNSS and ground-based video tracking results. We will report our results to DLR, in international journals, and will present our work at international conferences.

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