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Abstract
Abstract. Climate teleconnections show remote and large-scale relationships between distant points on Earth. Their relations to precipitation are important to monitor and anticipate the anomalies that they can produce in the local climate, such as flood and drought events impacting agriculture, health, and hydropower generation. Climate teleconnections in relation to precipitation have been widely studied. Nevertheless, the spatial association of the teleconnection patterns (i.e. the spatial delineation of regions with teleconnections) has been unattended. Such spatial association allows to characterize how stable (heterogeneity/dependent and statistically significant) is the underlying spatial phenomena for a given pattern. Thus our objective was to characterize the spatial association of climate teleconnection patterns related to precipitation using an exploratory spatial data analysis approach. Global and local indicators of spatial association (Moran’s I and LISA) were used to detect spatial patterns of teleconnections based on TRMM satellite images and climate indices. Moran’s I depicted high positive spatial association for different climate indices, and LISA depicted two types of teleconnections patterns. The homogenous patterns were localized in the Coast and Amazonian regions, meanwhile the disperse patterns had a major presence in the Highlands. The results also showed some areas that, although with moderate to high teleconnection influences, had a random spatial patterns (i.e. non-significant spatial association). Other areas showed both teleconnections and significant spatial association, but with dispersed patterns. This pointed out the need to explore the local underlying features (topography, orientation, wind and micro-climates) that restrict (non-significant spatial association) or reaffirm (disperse patterns) the teleconnection patterns.
Highlights
Climate teleconnections show remote and large-scale relationships between distant points on Earth, that produce anomalies and variability in the surface climate and precipitation of a region (Carleton, 2003; Z. Liu & Alexander, 2007)
A positive correlation means that when the value of a climate index increases, the precipitation increases; while a negative correlation means that when the index increases, the precipitation is expected to decrease
The results showed that Moran’s I depicted high positive spatial association in all the cases, LISA allowed to identify two types of teleconnections patterns: homogenous and disperse
Summary
Climate teleconnections show remote and large-scale relationships between distant points on Earth, that produce anomalies and variability in the surface climate and precipitation of a region (Carleton, 2003; Z. Liu & Alexander, 2007). Climate teleconnections show remote and large-scale relationships between distant points on Earth, that produce anomalies and variability in the surface climate and precipitation of a region Liu & Alexander, 2007) Their influences on local climate are highly variable across large geographic areas (Kiem & Franks, 2001). It is usual to apply correlation methods in order to show the degree of association among precipitation and climate indices (Fierro, 2014; Liu, Chen, & DaMassa, 2018).
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