Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic

• Main Authors: Richter-Menge, Jacqueline A, Farrell, Sinead L
• Other Authors: COLD REGIONS RESEARCH AND ENGINEERING LAB HANOVER NH
• Format: Text
• Language: English
• Published: 2013
• Subjects: Snow; Ice and Permafrost; *SEA ICE; ARCTIC OCEAN; ARCTIC REGIONS; MEASUREMENT; THICKNESS; VARIATIONS; SNOW DEPTH; Arctic; Arctic Ocean; Beaufort Sea; Ice; permafrost; Sea ice
• Online Access: http://www.dtic.mil/docs/citations/ADA601070; http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA601070

This work is motivated by the desire to improve the quality of airborne and satellite-based measurements of sea ice thickness and snow depth in the Arctic; to achieve a resolution that is adequate for monitoring decadal variability and to minimize the degree of uncertainty in predictive models. The specific objectives of our proposed work are: * To carefully assess remotely-based observations of Arctic sea ice thickness and snow depth using a rare set of coordinated in situ, airborne, satellite and submarine measurements collected by US Army Corps of Engineering Cold Region Research and Engineering Laboratory (CRREL), Naval Research Laboratory (NRL) and National Aeronautics and Space Administration (NASA) in conjunction with the US Navy at the ICEX2011 sea ice field camp in March 2011 in the Alaskan Beaufort Sea; * To leverage and integrate the measurements and results from this focused effort with data collected during related national and international activities (e.g. NASA IceBridge sea ice missions, NRL under flights of CryoSat-2, European Space Agency (ESA) CryoVEx, submarine ice draft measurements, Alfred Wagner Institute (AWI) POLAR5 and historic ICESat records); * To use these data to revise error estimates of remotely-derived snow depth and thickness data products from, for example, ICESat, IceBridge and CryoSat-2. These error estimates (a) are critical for understanding the variability and trends in the long-term time series of observations, (b) will help tie the various satellite and airborne records together, and (c) provide important input for predictive sea ice models. Prepared in collaboration with University of Maryland, ESSIC, College Park, MD.