Algorithms for Estimating Trends in Global Temperature Volatility
Algorithms for Estimating Trends in Global Temperature Volatility
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DOI：
10.1609/aaai.v33i01.3301614
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发表时间：
2018-05
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影响因子：
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通讯作者：
Arash Khodadadi;D. McDonald
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文献类型：
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作者：
Arash Khodadadi;D. McDonald
陆地温度变化的趋势可能比平均温度的趋势更与物种生存相关。在本文中，我们开发了使用极地轨道气象卫星的多分辨率气候数据来估计此类趋势的方法。我们推导出两种新颖的计算算法，专为空间和时间上的密集、网格化观测而定制。我们通过模拟这些数据的特征并在大型、公开的全球温度数据集上评估我们的方法，最终目标是跟踪云反射率温度变化的趋势。
Trends in terrestrial temperature variability are perhaps more relevant for species viability than trends in mean temperature. In this paper, we develop methodology for estimating such trends using multi-resolution climate data from polar orbiting weather satellites. We derive two novel algorithms for computation that are tailored for dense, gridded observations over both space and time. We evaluate our methods with a simulation that mimics these data’s features and on a large, publicly available, global temperature dataset with the eventual goal of tracking trends in cloud reflectance temperature variability.