Taking the temperature of Antarctica with joint inversion of geophysical information - Antarctic Heat 2

地球物理信息联合反演获取南极温度——南极热2

• 批准号: 403765285
• 负责人: Professor Dr. Jörg Ebbing
• 金额: --
• 依托单位: Sektion Geophysik
• 依托单位国家: 德国
• 项目类别: Infrastructure Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/403765285?language=en
• 关键词: Taking; temperature; Antarctica; joint; inversion

Different methods have been applied in recent years to quantify the thermal structure and most specific the geothermal heat flow over Antarctica. In the first phase of the project, we have demonstrated that such models are often incompatible as they are based on contradicting assumptions not agreeing with the interdependencies between the geophysical products. Still, the available pieces of geophysical information from satellite observations, airborne geophysical data, geological and seismological models can be used in automatic methods like machine learning to provide a new assessment of the geothermal heat flow and its uncertainty. Critical is hereby a careful evaluation of the applied data sets. In addition to data quality, regional data sets lack the details required for ice-sheet modelling, but local data sets may lack the spatial coverage for a systematic analysis. By coupling novel geophysical inverse methods with rock properties available mainly at the coasts of Antarctica, we will predict thermal and geophysical parameters into the continent. These will be coupled with thermal parameters based on ice temperature profiles to provide a fully coupled temperature model for the transition between the Solid Earth and Cryosphere. We will furthermore explore the sensitivity of these products for ice-sheet dynamics.

近年来，人们应用了不同的方法来量化南极洲的热结构，尤其是地热热流。在该项目的第一阶段，我们已经证明这些模型通常是不兼容的，因为它们基于与地球物理产品之间的相互依赖性不相符的矛盾假设。尽管如此，来自卫星观测、机载地球物理数据、地质和地震模型的可用地球物理信息可以用于机器学习等自动方法，以提供对地热热流及其不确定性的新评估。因此，至关重要的是对所应用的数据集进行仔细评估。除了数据质量之外，区域数据集缺乏冰盖建模所需的细节，但本地数据集可能缺乏系统分析所需的空间覆盖范围。通过将新颖的地球物理反演方法与主要在南极洲海岸可用的岩石特性相结合，我们将预测该大陆的热参数和地球物理参数。这些将与基于冰温剖面的热参数相结合，为固体地球和冰冻圈之间的过渡提供完全耦合的温度模型。我们将进一步探讨这些产品对冰盖动力学的敏感性。