Seasonal and inter-annual variabilities of biogeochemical variables, including nitrous oxide (N 2 O), an important climate active gas, were analyzed during monthly observations between 2002 and 2012 at an ocean Time-Series station in the coastal upwelling area off central Chile (36°30.8′; 73°15′).Oxygen, N 2 O, nutrients and chlorophyll-a (Chl-a) showed clear seasonal variability associated with upwelling favorable winds (spring-summer) and also inter-annual variability, which in the case of N 2 O was clearly observed during the occurrence of N 2 O hotspots with saturation levels of up to 4849%. These hotspots consistently took place during the upwelling-favorable periods in 2004, 2006, 2008, 2010 and 2011, below the mixed layer (15-50 m depth) in waters with hypoxia and some − NO 2 accumulation. The N 2 O hotspots displayed excesses of N 2 O (ΔN 2 O) three times higher than the average monthly anomalies (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Estimated relationships of ΔN 2 O versus apparent oxygen utilization (AOU), and ΔN 2 O versus − NO , 3 suggest that aerobic ammonium oxidation (AAO) and partial denitrification are the processes responsible for high N 2 O accumulation in subsurface water. Chl-a levels were reasonably correlated with the presence of the N 2 O hotspots, suggesting that microbial activities fuelled by high availability of organic matters lead to high N 2 O production. As a result, this causes a substantial N 2 O efflux into the atmosphere of up to 260 μmol m −2 d −1 . The N 2 O hotspots are transient events or hot moments, which may occur more frequently than they are observed. If so, this upwelling area is producing and emitting greater than expected amounts of N 2 O and is therefore an important N 2 O source that should be considered in the global atmospheric N 2 O balance. OPEN ACCESS RECEIVED

Coastal upwelling systems off the coasts of Peru and Chile are among the most productive marine ecosystems in the world, sustaining a significant percentage of global primary production and fishery yields. Seasonal and interannual variability in these systems has been relatively well documented; however, an understanding of recent trends and the influence of climate change on marine processes such as surface cooling and primary productivity is limited. This study presents evidence that winds favorable to upwelling have increased within the southern boundary of the Humboldt Current System (35°–42°S) in recent decades. This trend is consistent with a poleward movement of the influence of the Southeast Pacific Anticyclone and resembles the spatial pattern projected by Global Circulation Models for warming scenarios. Chlorophyll a levels (from 2002 to present) determined by satellite and field-based time-series observations show a positive trend, mainly in austral spring–summer (December–January–February), potentially explained by observed increments in nutrient flux towards surface waters and photosynthetically active radiation. Both parameters appear to respond to alongshore wind stress and cloud cover in the latitudinal range of 35°S to 42°S. In addition, net annual deepening of the mixed layer depth is estimated using density and temperature profiles. Changes in this depth are associated with increasing winds and may explain cooler, more saline, and more productive surface waters, with the latter potentially causing fluctuations in dissolved oxygen and other gases, such as nitrous oxide, sensitive to changes in oxygenation. We argue that these recent changes represent, at least in part, a regional manifestation of the Anthropocene along the Chilean coast.

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Predicting future climatic events is one of the key issues in many fields, whether in scientific or industrial areas. An artificial neural network (ANN) model, based on a backpropagation type, was developed in this study to predict the minimum air temperature of the following day from meteorological data using air temperature, relative humidity, radiation, precipitation, and wind direction and speed to detect the occurrence of radiative frost events. The configuration of the next day ANN prediction system allows operating with low-power computing machines; it is able to generate early warnings that can lead to the development of effective strategies to reduce crop damage, lower quality, and losses in agricultural production. This paper presents a procedural approach to an ANN, which was trained, validated, and tested in 10 meteorological stations in central Chile for approximately 8 yr (2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017). The overall mean results were classified by a confusion matrix and showed good performance in predicting minimum temperature with a mean square error (MSE) of 2.99 ºC for the network, 1.71 ºC for training, 1.77 ºC for validation, and 1.74 ºC for the testing processes. Frost detection results had an appropriate 98% overall mean accuracy (ACC), 86% sensitivity (TPR), and 2% error rate (ER). Differences and errors in frost detection can be attributed to several factors that are mainly associated with the accuracy of the sensors meteorological stations, local climatic and geographic conditions, and the number of parameters that enter in the ANN training processes.