科研之友
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摘要
This article explores spatial modeling of daily minimum and maximum air temperatures using data from both ground-based, embedded sensors and remote sensors. Eleven models of min/max air temperature were developed ranging from simple proximity-based models to more complicated models that combine spatial similarity, temporal trends, and remotely sensed observations. These models are compared based on their accuracy, using a case study comprising data from the state of New Jersey. The results show that nearest neighbor and inverse distance weighted models based solely on land-based measurements are superior to models that include remotely sensed land surface temperature even when the gauge network is very sparse.
- 出版日期2013-6-1
