Feasibility of Estimating Ice Sheet Internal Temperatures Using Ultra-Wideband Radiometric Measurements
Abstract
ICE sheet internal temperature (Ti) is an essential factor for understanding glacier dynamics and predicting future changes of glacier ice. The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature product via measuring low frequency microwave emission. Twelve channels ranging from 0.5 to 2.0 GHz are covered by the instrument. A Greenland air-borne demonstrations were conducted in September 2017, provided first demonstration of Ultra-wideband radiometer observations of geophysical scenes including ice sheets. Radiation at higher frequencies corresponds to microwave radiation emanating from ice nearer to the ice sheet surface while emissions at lower frequencies upwell from deeper within the ice column. Measuring emissions across a range of frequencies provides the potential for inferring ice temperature vertical profiles. A Bayesian framework was designed to retrieve the ice sheet internal temperature from UWBRAD brightness temperature (T b ) measurements over Greenland flight path.
The microwave measurements are affected by both the temperature and the density of the ice sheet. A 1-D heat-flow model, the Robin Model, was used to model the ice sheet internal temperature profile with ground information. An exponential fit of ice density from Borehole measurement was used to mimic the trend of ice density. Upper layer density fluctuation affects the brightness strongly and was modeled from neutron probe measurements. Another density variation in very fine scale at deeper ice sheet was also added. The overall density is the sum of density trend and density fluctuation. The effective surface temperature (Ts), geothermal heat flux (G), snow accumulation rate (M), the variance of upper layer ice density (δ1), and the variance of fine scale density variation at deeper ice sheet (δ2) were treated as unknown variables within the retrieval framework. The Markov Chain Monte Carlo (MCMC) approach is applied to retrieve information of the parameters from UWBRAD measurements. We use the estimated parameters to generate temperature profile of the flight path. For the entire flight path, the temperature profile modeling showed variation and less uncertainty from those generated from prior information.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.C31B1520D
- Keywords:
-
- 0720 Glaciers;
- CRYOSPHERE;
- 0758 Remote sensing;
- CRYOSPHERE;
- 0762 Mass balance;
- CRYOSPHERE;
- 0776 Glaciology;
- CRYOSPHERE