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Integrated Remote Sensing and Wavelet Analyses for Screening Short-term Teleconnection Patterns in Northeast America
Citation:
Mullon, L., N. Chang, Y. J. Yang, AND J. Weiss. Integrated Remote Sensing and Wavelet Analyses for Screening Short-term Teleconnection Patterns in Northeast America. JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, 499:247-264, (2013).
Impact/Purpose:
This journal article describes a method and investigationr results of correlating sea surface temperature to precipitation and vegetation covers in the US east seaboard. The purpose is to identify locations of SST anomalies for short-term and high resolution prediction of climate in watershed scales, a subject important to water resources adaptation to climate changes.
Description:
Global sea surface temperature (SST) anomalies have a demonstrable effect on vegetation dynamics and precipitation patterns throughout the continental U.S. SST variations have been correlated with greenness (vegetation densities) and precipitation via ocean-atmospheric interactions known as climate teleconnections. Prior research has demonstrated that teleconnection can be used for climate prediction across a wide region at sub-continental scales. Yet these studies tend to have large uncertainties in estimates by utilizing simple linear analyses to examine teleconnection relationships. Yet non-stationary signals exist, making teleconnection identification difficult at the local scale. This paper establishes short-term (10-year), linear and non-stationary teleconnection signals between SST at the North Atlantic and North Pacific oceans and terrestrial responses (i.e., greenness and precipitation) along multiple pristine sites in the northeastern U.S., including (1) White Mountain National Forest – Pemigewasset Wilderness, (2) Green Mountain National Forest – Lye Brook Wilderness and (3) Adirondack State Park – Siamese Ponds Wilderness. Each site was selected to avoid anthropogenic influences that may otherwise mask climate teleconnection signals. Lagged pixel-wise linear teleconnection patterns across anomalous datasets found significant correlation regions between SST and the terrestrial sites. Non-stationary signals also exhibit salient co-variations at biennial and triennial frequencies between terrestrial responses and SST anomalies across oceanic regions in agreement with the El Nino Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) signals. Multiple regression analysis of the combined ocean indices explained up to 40% of the greenness and 36% of the precipitation in the study sites. These identified short-term teleconnection signals can improve the understanding and projection of the climate change impacts at local scales, and harness the interannual periodicity information for precipitation projections.
