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Abstract:Understanding of evapotranspiration (ET) processes over Andean mountain environments is crucial, particularly due to the importance of these regions to deliver water-related ecosystem services. In this context, the detection of spatio-temporal changes in ET remains poorly investigated for specific Andean ecosystems, like the páramo. To overcome this lack of knowledge, we implemented the energy-balance model METRIC with Landsat 7 ETM+ and MODIS-Terra imagery for a páramo catchment. The implementation contemplated adjustments for complex terrain in order to obtain daily, monthly and annual ET maps (between 2013 and 2014). In addition, we compared our results to the global ET product MOD16. Finally, a rigorous validation of the outputs was conducted with residual ET from the water balance. ET retrievals from METRIC (Landsat-based) showed good agreement with the validation-related ET at monthly and annual steps (mean bias error <8 mm¨month´1 and annual deviation <17%). However, METRIC (MODIS-based) outputs and the MOD16 product were revealed to be unsuitable for our study due to the low spatial resolution. At last, the plausibility of METRIC to obtain spatial ET retrievals using higher resolution satellite data is demonstrated, which constitutes the first contribution to the understanding of spatially-explicit ET over an alpine catchment in the neo-tropical Andes.

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Knowledge about precipitation generation remains limited in the tropical Andes due to the lack of water stable isotope (WSI) data. Therefore, we investigated the key factors controlling the isotopic composition of precipitation in the Páramo highlands of southern Ecuador using event-based (high frequency) WSI data collected between November 2017 and October 2018. Our results show that air masses reach the study site preferentially from the eastern flank of the Andes through the Amazon basin (73.2%), the Orinoco plains (11.2%), and the Mato Grosso Massif (2.7%), whereas only a small proportion stems from the Pacific Ocean (12.9%). A combination of local and regional factors influences the δ18O isotopic composition of precipitation. Regional atmospheric features (Atlantic moisture, evapotranspiration over the Amazon Forest, continental rain-out, and altitudinal lapse rates) are what largely control the meteoric δ18O composition. Local precipitation, temperature, and the fraction of precipitation corresponding to moderate to heavy rainfalls are also key features influencing isotopic ratios, highlighting the importance of localized convective precipitation at the study site. Contrary to δ18O, d-excess values showed little temporal variation and could not be statistically linked to regional or local hydrometeorological features. The latter reveals that large amounts of recycled moisture from the Amazon basin contributes to local precipitation regardless of season and predominant trajectories from the east. Our findings will help to improve the isotope-based climatic models and enhance paleoclimate reconstructions in the southern Ecuador highlands.

Understanding precipitation and its relation with atmospheric and oceanic conditions is vital in the face of climate change. This is crucial in the Tropical Andes (TA) because millions of people depend on water originated in the cordillera. Unfortunately, the paucity of meteorological monitoring that exists in mountainous regions is accentuated in the tropics. In this context, climate indices, remotely sensed, and gridded datasets, are useful tools to study climate and precipitation in the TA, and additional climate indices can be calculated from reanalysis datasets. The combination of this information with traditional indices has the potential to improve our understanding of precipitation. Our objective was to use the k‐means algorithm to regionalize precipitation in the TA (different regions have different climate), and then use the random forest algorithm to study the variables related to precipitation in each of these regions in seasonal timescales. Here, we show the suitability of the random forest algorithm to reveal climate processes and the high potential of the novel climate indices to improve the regressions. We found that convective available potential energy was the most important variable for precipitation in the northern TA, except for the Chocó, where v at 850 hPa was the most important one. Meanwhile, vertical integral of divergence of moisture flux was the most important one in the southern TA. Interestingly, in the DJF season when the South American low‐level jet (SALLJ) is more active, u and v at 850 hPa showed their lowest relative importance and the total column of water vapour showed its maximum, this could indicate that precipitation anomalies are controlled by atmospheric moisture availability rather than by the speed of the SALLJ during DJF. These results deepen our understanding of precipitation anomalies in the TA and the related oceanic and atmospheric conditions. The proposed methodology was proven to be suitable and it could be used in the future to test and formulate new hypotheses, and to forecast seasonal precipitation.

In this study, precipitation in Tropical South America in the 1931–2016 period is investigated by means of Principal Component Analysis and composite analysis of circulation fields. The associated dynamics are analyzed using the 20th century ERA-20C reanalysis. It is found that the main climatic processes related to precipitation anomalies in Tropical South America are: (1) the intensity and position of the South Atlantic Convergence Zone (SACZ); (2) El Niño Southern Oscillation (ENSO); (3) the meridional position of the Intertropical Convergence Zone (ITCZ), which is found to be related to Atlantic Sea Surface Temperature (SST) anomalies; and (4) anomalies in the strength of the South American Monsoon System, especially the South American Low-Level Jet (SALLJ). Interestingly, all of the analyzed anomalies are related to processes that operate from the Atlantic Ocean, except for ENSO. Results from the present study are in agreement with the state of the art literature about precipitation anomalies in the region. However, the added strength of the longer dataset and the larger study area improves the knowledge and gives new insights into how climate variability and the resulting dynamics are related to precipitation in Tropical South America.