Arctic Sea Ice Thickness from Satellite Observations, Aircraft Field Campaign Measurements, and Numerical Model Simulations

Sea ice is an important indicator and effective modulator of regional and global climate change because it significantly affects the complex exchanges of momentum, heat, and mass between the sea and atmosphere. At present, there are datasets for Arctic sea ice thickness from satellite observations, aircraft field campaign measurements, numerical model simulations, and some in-situ measurements. Among satellite derived data sets, one satellite ice thickness product has been generated using NASA's Ice, Cloud and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) observations (Kwok et al., 2009), another has been produced from long-term optical (visible, near-IR, and thermal IR) imager data from NOAA Polar Orbiting Satellites (Wang et al., 2010). The approaches are completely different: the ICESat product estimates ice thickness from surface elevation; the optical imager approach estimates ice thickness by solving the surface energy budget equation. NASA's IceBridge program fills the gap between the loss of ICESat in 2010 and the launch of ICESat-2 in 2016. IceBridge employs an aircraft for altimeter and other measurements of the ice sheets and sea ice. The IceBridge Snow Radar, Digital Mapping System (DMS), Continuous Airborne Mapping By Optical Translator (CAMBOT), and Airborne Topographic Mapper (ATM) instruments can be used to estimate ice thickness with a methodology similar to that used for ICESat. Ice thickness has also been modeled with the numerical model called Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) (Zhang and Rothrock, 2003). Arctic sea ice thickness estimates from these different data sources will be examined and inter-compared to evaluate their consistency and validity with in-situ measurements. Arctic sea ice thickness variations over time and space will be also investigated.