Modeling dynamic controls on ice streams: a Bayesian statistical approach
Modeling dynamic controls on ice streams: a Bayesian statistical approach
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DOI：
10.3189/002214308786570917
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发表时间：
2008-01-01
影响因子：
3.4
通讯作者：
Van der Veen, Q.
中科院分区：
文献类型：
--
作者：
Berliner, L. M.;Jezek, K.;Van der Veen, Q.
我们的主要目标是通过贝叶斯统计分析结合物理，虽然不完全知道，模型使用的数据是不完整的和嘈杂的冰流动力学的研究。我们提出的物理统计模型考虑到这些不确定性在一个连贯的，分层的方式。初始建模假设估计基底剪切应力等于驱动应力，但随后包括随机校正过程以考虑模型误差。由此产生的随机方程被纳入一个简单的表面速度模型。贝叶斯定理的使用允许我们对给定的基底高程、表面高程和表面速度的所有未知数进行推断。结果是可能值的后验分布，可以用多种方式进行总结。例如，应力场的后验均值表示场中任何位置的平均行为，后验标准差描述相关的不确定性。我们分析了“东北格陵兰冰流”的数据，并说明了如何从我们的贝叶斯分析得出科学结论。
Our main goal is to exemplify the study of ice-stream dynamics via Bayesian statistical analysis incorporating physical, though imperfectly known, models using data that are both incomplete and noisy. The physical-statistical models we propose account for these uncertainties in a coherent, hierarchical manner. The initial modeling assumption estimates basal shear stress as equal to driving stress, but subsequently includes a random corrector process to account for model error. The resulting stochastic equation is incorporated into a simple model for surface velocities. Use of Bayes' theorem allows us to make inferences on all unknowns given basal elevation, surface elevation and surface velocity. The result is a posterior distribution of possible values that can be summarized in a number of ways. For example, the posterior mean of the stress field indicates average behavior at any location in the field, and the posterior standard deviations describe associated uncertainties. We analyze data from the 'Northeast Greenland Ice Stream' and illustrate how scientific conclusions may be drawn from our Bayesian analysis.