Abstract
Mountain regions worldwide present a pronounced spatiotemporal precipitation variability, which added to scarce monitoring networks limits our understanding of the generation processes involved. To improve our understanding of clouds and precipitation dynamics and cross-scale generation processes in mountain regions, we analyzed spatiotemporal rainfall patterns using satellite cloud products (SCP) in the Paute basin (900–4200 m a.s.l. and 6481 km2) in the Andes of Ecuador. Precipitation models, using SCP and GIS data, reveal the spatial extension of three regimes: a three-modal (TM) regime present across the basin, a bimodal (BM) regime, along sheltered valleys, and a unimodal (UM) regime at windward slopes of the eastern cordillera. Subsequently, the spatiotemporal analysis using synoptic information shows that the dry season of the BM regime during boreal summer is caused by strong subsidence inhibiting convective clouds formation. Meanwhile, in UM regions, low advective shallow cap clouds mainly cause precipitation, influenced by water vapor from the Amazon and enhanced easterlies during boreal summer. TM regions are transition zones from UM to BM and zones on the windward slopes of the western cordillera. These results highlight the suitability of satellite and GIS data-driven statistical models to study spatiotemporal rainfall seasonality and generation processes in complex terrain, as the Andes.
Highlights
Mountain regions provide diverse resources and services worldwide
The approach consists of five consecutive steps including (i) generation of normalized precipitation regimes (NPRs), (ii) area-wide seasonal delineation using satellite derived variables cloud frequency (CF), liquid water path (LWP), and ZMIT, (iii) the development of a model of rainfall based on principal component analysis (PCA) applied to CF (CFM) to generate seasonality delineation, (iv) the development of a multiple linear regression model (MLRM) of rainfall to generate seasonality delineation, and (v) the pixel-wise evaluation of regionalization obtained from CF, LWP, ZMIT, cloud frequency rainfall model (CFM), and MLRM against zonation from [7]
The results show that MRLM and CFM outperformed CF, LWP, and ZMIT, with CFM presenting a slightly higher concordance score
Summary
Mountain regions provide diverse resources and services worldwide. Of especial importance is the provision of water for several uses like irrigation and drinking water [1]. The assessment of water resources in mountain regions is uncertain due to the combination of high spatiotemporal precipitation variability and scarce monitoring networks. These hinder the understanding of the precipitation processes. Towards the west of the cordillera, in the coastal plains, one rainy season occurs from December to April, which is mainly modulated by the Pacific Ocean sea surface influence, especially by the region Nino 1+2, and by the evolution of the intertropical convergence zone (ITCZ). In the Amazon, towards the eastern part of the Andes, the rainfall is present year-around, with two periods of higher rainfall during March–May and October-November, modulated by the ITCZ and moist air from the Amazon basin. The inter-Andean valleys between the two mountain ranges present a bimodal regime of rainfall, with a dry period during boreal summer
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