论文标题
北极海冰范围措施的最佳组合：动态因子建模方法
Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach
论文作者
论文摘要
北极海冰的减少范围是气候变化以及未来全球变暖的促进物的关键指标。自1978年以来，使用基于卫星的微波传感测量了北极海冰。然而，基于原始卫星数据的不同算法转换，已经提供了不同的北极海冰范围。我们提出并估算一个动态因子模型，该模型以最佳方式结合了其中四个措施，以解释其不同的波动性和互相关。然后，我们使用卡尔曼（Kalman）更顺畅地提取北极海冰范围的最佳组合度量。事实证明，几乎所有的重量都放在NSIDC海冰指数上，确认并增强了对海冰指数和NASA团队算法的信心。
The diminishing extent of Arctic sea ice is a key indicator of climate change as well as an accelerant for future global warming. Since 1978, Arctic sea ice has been measured using satellite-based microwave sensing; however, different measures of Arctic sea ice extent have been made available based on differing algorithmic transformations of the raw satellite data. We propose and estimate a dynamic factor model that combines four of these measures in an optimal way that accounts for their differing volatility and cross-correlations. We then use the Kalman smoother to extract an optimal combined measure of Arctic sea ice extent. It turns out that almost all weight is put on the NSIDC Sea Ice Index, confirming and enhancing confidence in the Sea Ice Index and the NASA Team algorithm on which it is based.
