The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W12-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 101–106, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-101-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 101–106, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-101-2020

  04 Nov 2020

04 Nov 2020

SPATIAL ASSOCIATION TO CHARACTERIZE THE CLIMATE TELECONNECTION PATTERNS IN ECUADOR BASED ON SATELLITE PRECIPITATION ESTIMATES

D. Ballari1, L. Campozano2, E. Samaniego3, and D. Orellana4 D. Ballari et al.
  • 1IERSE, Facultad de Ciencia y Tecnología, Universidad del Azuay, Cuenca, Ecuador
  • 2Departamento de Ingeniería Civil y Ambiental, Escuela Politécnica Nacional, Quito, Ecuador
  • 3Departamento de Recursos Hídricos y Ciencias Ambientales, Facultad de Ingeniería, Universidad de Cuenca, Cuenca, Ecuador
  • 4LlactaLAB – Ciudades Sustentables, Departamento Interdisciplinario de Espacio y Población, Facultad de Ciencias Agropecuarias, Universidad de Cuenca, Cuenca, Ecuador

Keywords: Spatial Association, Spatial Patterns, Climate Teleconnections, Satellite Precipitation, Moran’s I and LISA Indicators

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.