Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements
Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements
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DOI：
10.3189/2013jog12j158
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发表时间：
2013
影响因子：
3.4
通讯作者：
S. Simonsen;L. Stenseng;G. Ađalgeirsdóttir;R. Fausto;C. Hvidberg;P. Lucas‐Picher
中科院分区：
文献类型：
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作者：
S. Simonsen;L. Stenseng;G. Ađalgeirsdóttir;R. Fausto;C. Hvidberg;P. Lucas‐Picher
摘要提出了一种利用机载合成孔径雷达（SAR）/干涉雷达高度计系统（ASIRAS）数据评估积雪压实的方法。为此，我们开发了一个动态积雪压实模型，包括融水保留。ASIRAS数据的基础上，其中显示内部层作为年度的视野在最上层的积雪，该方法依赖于推断的年龄/深度（内部层）的信息，从雷达数据使用蒙特卡洛反演技术，并行调谐的积雪模型和大气强迫参数（温度和积累）。该模型对两个雪芯进行验证，它表明，应用雪密度和年龄/深度信息的反演模型的偏差提供了最准确的理解。然后，该方法被施加到一个67公里的部分的EGIG线强迫大气输出的区域气候模型，只使用年龄/深度信息的反演步骤。由ASIRAS数据跟踪的层建模的均方根误差为9厘米，这是在层跟踪的估计误差。这使我们有信心应用观测到的年度分层从积雪雷达数据，以评估积雪压实;然而，研究还表明，我们的积雪模型调整参数是网站依赖的，不能单独通过温度和积累参数化。
Abstract 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.