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Abstract

The northern Chilean coastal regions are known for their extreme aridity, with annual precipitation often less than 1 mm. The interaction between ocean-atmosphere systems plays a crucial role in shaping marine advection fog patterns in this area, which is vital for the hyper-arid ecosystem along the Atacama coast. While extensive geographical research has been conducted on fog patterns since the mid-20th century, there is limited knowledge in managing fog climate records and understanding their regional and local climatological dynamics. This research is organized into three main sections. The first one outlines a methodological climate data flow, emphasizing data quality control and processing. The second section focuses on analyzing temporal gradients of fog climate at the regional level. The third section delves into local spatial analysis and modeling of Near-surface fog water in the inland desert. The processing of raw climatic data recorded from extreme environments such as the extreme aridity of the Atacama Desert poses a significant challenge in climatic research, as they exhibit gaps, inconsistencies, and errors. The process of handling climatic data from the eight climatological stations and Standard Fog Collectors (SFCs) comprising the fog climate network in the northern Atacama Desert, Region of Tarapacá, involves data identification, cleansing, correction, and normalization. This is achieved through programming flows guided by standardized parameters, primarily defined by the World Meteorological Organization (WMO). Data gaps and outliers within the network's data series account for less than 2% of the total record. Anomalies in the data series are primarily attributed to electrical and electronic issues inherent in remote/satellite transmission. The precision and quality of climatic data are essential for accurate interpretation and analysis, furthering our understanding of fog climate dynamics in hyper-arid environments. The regional approach aims to comprehend the variability between fog collection and its climatological gradient. The datasets were analyzed at different temporal intervals across eight climatological stations. The analysis elucidates how the variability of fog climates and their driving factors in these datasets manifest themselves throughout the region, considering both temporal and geographical determinants. Throughout the year, fog exhibits marked diurnal variation, being more pronounced in the morning and minimal in the afternoon and night. The seasonal influence of the thermal inversion layer (TIL) is significant, with more fog water collected in the winter due to a lower TIL and less collection in the summer due to a higher TIL. High relative humidity is crucial for fog formation in coastal areas, while inland regions are drier. Wind, varying in direction and speed, also impacts fog. Overall, this regional-temporal analysis shows the multifaceted nature of fog in the Atacama Desert, elucidating its dependence on diurnal, seasonal, and geographical variables. These findings contribute to a better understanding of fog dynamics within this unique arid ecosystem. In an inland desert at ca. 1,200 meters above sea level (masl) within the "Oyarbide" Master Site, a local study analyses the link between Near-surface fog water variability and topographical features. The monthly data of ten Mini Fog Collectors (Mini FCs) placed at Oyarbide and Digital Elevation Model (DEM) data, an Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) were employed for regression analysis. These methods evaluated the influence of five topographical factors on Near-surface fog water. Results revealed patterns and spatial variability in these associations, emphasizing the impact of topography on Near-surface fog water. Elevation was positively correlated with Near-surface fog water, while Aspect and Slope are related to terrain roughness. Local GWR model outperformed the global OLS model, substantially increasing the coefficient of determination (R²). This provides a comprehensive understanding of how local topography affects Near-surface fog water collection, enhancing our knowledge of atmosphere-biosphere interactions.