作者: Elizabeth C. Kent , Peter K. Taylor , Peter G. Challenor
DOI: 10.1175/1520-0442(2000)013<1845:TEOSCO>2.0.CO;2
关键词: Climatology 、 Image resolution 、 Resolution (electron density) 、 Smoothing 、 Empirical orthogonal functions 、 Noise 、 Environmental science 、 Sea surface temperature 、 Ship tracks 、 Variable (computer science)
摘要: Abstract The effects on a dataset of smoothing by successive correction have been investigated. resulting spatial resolution is estimated using distribution ship reports from sample month. Although the uses same characteristic radii over whole globe, spatially variable and, in data-sparse regions, will show large month-to-month variability with changes tracks. climatological dataset, which gridded at 1°, shown to typical 3°. In some regions much coarser. Using sea surface temperature as an example, it that procedure used, for recent not successful removing all noise regions. Additionally, well-defined intermonthly main shipping lanes, where there are many observations, degraded influence poorer-quality data surrounding region...