Monitoring evapotranspirationin arid and semi-arid environments plays a key role in water irrigation scheduling for water use efficiency. This work presents an operational method for evapotranspiration retrievals based ondisaggregated Land Surface Temperature (LST). The LSTs retrieved from Landsat-8 and MODIS data weremerged in order to provide an 8-day composite LSTproduct at 100 x 100 m resolution.The method wastested in the arid region of Copiapó, Chile using data from years 2013-2014 and validated using data from years 2015-2016.In-situ measurements from agrometeorological stations were used as input to the disaggregated method such as air temperature and potential evapotranspiration (ET0)estimated at the location. The disaggregation method was developed bytaking into account1) the spatial relationship between

A set of Essential Climate Variables (ECV) have been defined to be monitored by current and new remote sensing missions. The ECV retrieved at global scale need to be validated in order to provide reliable products to be used in remote sensing applications. For this, test sites are required to use in calibration and validation of the remote sensing approaches in order to improve the ECV retrievals at global scale. The southern hemisphere presents scarce test sites for calibration and validation field campaigns that focus on soil moisture and land surface temperature retrievals. In Chile, remote sensing applications related to soil moisture estimates have increased during the last decades because of the drought and water use conflicts that generate a strong interest on improved water demand estimates. This work describes the Laboratory for Analysis of the Biosphere (LAB)-NETwork, called herein after 'LAB-net', which was designed to be the first network in Chile for remote sensing applications. The test sites were placed in four sites with different cover types: vineyards and olive orchards located in the semi-arid region of Atacama, an irrigated raspberry crop in the Mediterranean climate zone of Chimbarongo, and a rainfed pasture in the south of Chile. Over each site, well implemented meteorological and radiative flux instrumentation was installed and continuously recorded the following parameters: soil moisture and temperature at two ground levels (10 and 20 cm), air temperature and relative humidity, net radiation, global radiation, radiometric temperature (8-14 µm), rainfall and soil heat flux. The LAB-net data base post-processing procedure is also described here. As an application, surface remote sensing products such as soil moisture data derived from the Soil Moisture Ocean Salinity (SMOS) and Land Surface Temperature (LST) extracted from the MODIS-MOD11A1 and GOES LST from Copernicus products were compared to in situ data in Oromo LAB-net site. Moreover, land surface energy flux estimation is also shown as an application of LAB-net data base. These applications revealed a good performance between in situ and remote sensing data. LAB-net data base also contributes to provide suitable information for land surface energy budget and therefore water resources management at cultivars scale. The data based generated by LAB-net is freely available for any research or scientific purpose related to current and future remote sensing applications.

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The evidence for global warming can be seen in various forms, such as glacier shrinkage, sea ice retreat, sea level rise and air temperature increases. The magnitude of these changes tends to be critical over pristine and extreme biomes. Chilean Patagonia is one of the most pristine and uninhabited regions in the world, home to some of the most important freshwater reservoirs as well as to evergreen forest, lakes and fiords. Furthermore, this region presents a sparse and weak network of ground stations which must be complemented with satellite information to determine trends on biophysical parameters. The main objective of this work is to present the first assessment on snow cover over the Aysén basin in Patagonia-Chile by using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the period 2000-2016. The MOD10A2 product was processed at 500 × 500 m spatial resolution. The time-series analysis consisted in the application of non-parametric tests such as the Mann-Kendall test and Sen's slope for annual and seasonal mean of snow covered area (SCA). Data from ground meteorological network and river discharges were also included in this work to show the trends in air temperature, precipitation and stream flow during the last decades. Results indicate that snow cover shows a decreasing non-significant trend in annual mean SCA with a −20.01 km 2 •year −1 slope, and neither seasonal mean shows statistical significance. The comparison with in situ data shows a seasonal decrease in stream flows and precipitation during summer. The hydrological year 2016 was the year with the most negative standardized joint anomalies in the period. However, the lack of in situ snow-monitoring stations in addition to the persistence of cloud cover over the basin can impact trends, creating some uncertainties in the data. Finally, this work provides an initial analysis of the possible impacts of global warming as seen by snow cover in Chilean Patagonia.

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