loading page

Detecting and Characterizing Sea Ice Pressure Ridges with ICESat-2
  • Kyle Duncan,
  • Sinéad Farrell,
  • Jennifer Hutchings
Kyle Duncan
Earth System Science Interdisciplinary Center

Corresponding Author:kyle.duncan@noaa.gov

Author Profile
Sinéad Farrell
University of Maryland College Park
Author Profile
Jennifer Hutchings
Oregon State University
Author Profile

Abstract

Since its launch, in September 2018, ICESat-2’s Advanced Topographic Laser Altimeter System (ATLAS) has collected high-resolution measurements of Arctic sea ice by sampling the surface every 70 cm along-track. We utilize the high-resolution capabilities of ATLAS with a novel algorithm called the University of Maryland-Ridge Detection Algorithm (UMD-RDA) to investigate sea ice topography across a range of scales. Applying the UMD-RDA to the ATL03 Global Geolocated Photon product we measure surface roughness and derive the frequency, height, width, and angle of individual pressure ridge sails. Aggregating data from multiple orbit crossings per day we investigate ridge characteristics at length-scales varying from 1 km (individual floes) to the pan-Arctic scale (central Arctic Ocean). Here, we present an evaluation of pressure ridge characteristics during the winter seasons of 2018/19, 2019/20, and 2020/21, comparing results from distinct regions with varying ice conditions. Near-coincident, independent observations of pressure ridges with Operation IceBridge (OIB) Airborne Topographic Mapper (ATM) lidar data, OIB near-coincident Continuous Airborne Mapping By Optical Translator (CAMBOT) high-resolution (~15 cm) optical imagery, and WorldView high-resolution (~30 cm) panchromatic satellite imagery are used to evaluate the accuracy of our ICESat-2 ridge detection scheme. There are many potential use-cases for a high-resolution sea ice topography data product within the community, ranging from navigational hazard mitigation to ecological studies of marine mammal habitats. We discuss plans for releasing these data products and discuss the improvements such data would make within high-resolution sea ice models.