The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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Key Points:• ECOSTRESS is a state-of-the-art combination of thermal bands, spatial and temporal resolutions, and measurement accuracy and precision • Data from 82 eddy covariance sites were coalesced concurrently with the first year of ECOSTRESS for Stage 1 validation • Clear-sky ET from ECOSTRESS compared well against a wide range of eddy Abstract The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the National Aeronautics and Space Administration (NASA). The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level-3 (L3) latent heat flux (LE) data products. These data are generated from the Level-2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear-sky ET product (L3_ET_PT-JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear-sky instantaneous/time of overpass: r 2 = 0.88; overall bias = 8%; normalized root-mean-square error, RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are overrepresented. The 70-m-high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1-km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data.

Abstract. This study compares actual evapotranspiration (ET a ) measurements by a set of six weighable lysimeters, ET a estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated with the full-form Penman-Monteith equation (ET PM ) for the Rollesbroich site in the Eifel (western Germany). The comparison of ET a measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ET a for the two methods for the year 2012 shows a good agreement with a total difference of 3.8 % (19 mm) between the ET a estimates. The highest agreement and smallest relative differences (< 8 %) on a monthly basis between both methods are found in summer. ET a was close to ET PM , indicating that ET was energy limited and not limited by water availability. ET a differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3 %. With the help of an onsite camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17 % to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5 % of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9 % to the total difference. However, 36 % of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33 %) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3 % for precipitation and 8 % for evapotranspiration.

We provide an overview of the Rur hydrological observatory, which is the main observational platform of the TERENO (TERrestrial ENvironmental Observatories) Eifel/Lower Rhine Valley Observatory. The Rur catchment area exhibits distinct gradients in altitude, climate, land use, soil properties, and geology. The Eifel National Park is situated in the southern part of the Rur catchment and serves as a reference site for the hydrological observatory. We present information on general physical characteristics of the Rur catchment and describe the main features of the multi-scale and multi-compartment monitoring framework. In addition, we also present some examples of the ongoing interdisciplinary research that aims to advance the understanding of complex hydrological processes and interactions within the Rur catchment.