Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements

TY - JOUR

T1 - Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements

AU - Simonsen, Sebastian Bjerregaard

AU - Stenseng, Lars

AU - Adalgeirsdottir, G.

AU - Fausto, R.S.

AU - Hvidberg, Christine Schøtt

AU - Lucas-Picher, P.

PY - 2013/7/2

Y1 - 2013/7/2

N2 - A method to assess firn compaction using data collected with the Airborne SAR (Synthetic Aperture Radar)/Interferometric Radar Altimeter System (ASIRAS) is developed. For this, we develop a dynamical firn-compaction model that includes meltwater retention. Based on the ASIRAS data, which show internal layers as annual horizons in the uppermost firn, the method relies on inferring the age/ depth (internal layers) information from the radar data using a Monte Carlo inversion technique to tune in parallel both the firn model and the atmospheric forcing parameters (temperature and accumulation). The model is validated against two firn cores, and it is shown that applying both firn densities and age/ depth information for the inversion gives the most accurate understanding of model biases. The method is then applied to a 67 km section of the EGIG line forced by atmospheric output from a regional climate model using only age/depth information in the inversion step. The layers traced by the ASIRAS data are modeled with a root-mean-square error of 9 cm, which is within the estimated error of the layer tracing. This gives us confidence in applying observed annual layering from firn radar data to assess firn compaction; however, the study also indicates that our firn-model-tuning parameters are site-dependent and cannot be parameterized by temperature and accumulation alone.

AB - A method to assess firn compaction using data collected with the Airborne SAR (Synthetic Aperture Radar)/Interferometric Radar Altimeter System (ASIRAS) is developed. For this, we develop a dynamical firn-compaction model that includes meltwater retention. Based on the ASIRAS data, which show internal layers as annual horizons in the uppermost firn, the method relies on inferring the age/ depth (internal layers) information from the radar data using a Monte Carlo inversion technique to tune in parallel both the firn model and the atmospheric forcing parameters (temperature and accumulation). The model is validated against two firn cores, and it is shown that applying both firn densities and age/ depth information for the inversion gives the most accurate understanding of model biases. The method is then applied to a 67 km section of the EGIG line forced by atmospheric output from a regional climate model using only age/depth information in the inversion step. The layers traced by the ASIRAS data are modeled with a root-mean-square error of 9 cm, which is within the estimated error of the layer tracing. This gives us confidence in applying observed annual layering from firn radar data to assess firn compaction; however, the study also indicates that our firn-model-tuning parameters are site-dependent and cannot be parameterized by temperature and accumulation alone.

U2 - 10.3189/2013JoG12J158

DO - 10.3189/2013JoG12J158

M3 - Journal article

SN - 0022-1430

VL - 59

SP - 545

EP - 558

JO - Journal of Glaciology

JF - Journal of Glaciology

IS - 215

ER -