ALPS：一个统一的陆地冰变化时间序列模拟框架
ALPS: A Unified Framework for Modeling Time Series of Land Ice Changes
摘要：
时间序列建模是冰冻圈科学的一个研究热点，这是由于所研究事件的复杂性和多尺度性。从不同传感器以不同的准确度对测量结果进行高度不均匀的采样，这对于冰盖高程的测量来说是典型的，这使得问题更具挑战性。在本文中，我们提出了一个基于样条的近似框架（ALPS -近似局部惩罚样条）的陆地冰变化的时间序列建模。B样条基函数的局部化支持使得对非均匀采样具有鲁棒性，这比其他全局和分段局部模型有相当大的改进。通过基于离散坐标差的惩罚和两级离群值检测等功能，ALPS进一步保证了近似的稳定性和质量。ALPS将严格的模型不确定性估计与所有近似值结合起来。如通过实例所示，ALPS表现良好的各种数据集，包括时间序列的冰盖厚度，海拔，速度和终端位置。对时间序列及其衍生物的稳健估计促进了新的应用，例如通过将冰盖厚度变化的稀疏采样时间序列与模拟的积雪厚度变化相融合，重建高分辨率的海拔变化记录，以及分析不同出口冰川观测之间的关系，以获得对过程和强迫的新认识。
英文摘要：
Modeling time series is a research focus in cryospheric sciences because of the complexity and multiscale nature of events of interest. Highly non-uniform sampling of measurements from different sensors with different levels of accuracy, as is typical for measurements of ice sheet elevations, makes the problem even more challenging. In this paper, we propose a spline-based approximation framework (ALPS - Approximation by Localized Penalized Splines) for modeling time series of land ice changes. The localized support of the B-spline basis functions enable robustness to non-uniform sampling, a considerable improvement over other global and piecewise local models. With features like, discrete-coordinate-difference-based penalization and two-level outlier detection, ALPS further guarantees the stability and quality of approximations. ALPS incorporates rigorous model uncertainty estimates with all approximations. As demonstrated by examples, ALPS performs well for a variety of data sets, including time series of ice sheet thickness, elevation, velocity, and terminus locations. The robust estimation of time series and their derivatives facilitates new applications, such as the reconstruction of high-resolution elevation change records by fusing sparsely sampled time series of ice sheet thickness changes with modeled firn thickness changes, and the analysis of the relationship between different outlet glacier observations to gain new insight into processes and forcing.
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