Search

The CloudRoots field experiment was designed to obtain a comprehensive observational dataset that includes soil, plant, and atmospheric variables to investigate the interaction between a heterogeneous land surface and its overlying atmospheric boundary layer at the sub-hourly and sub-kilometre scale. Our findings demonstrate the need to include measurements at leaf level to better understand the relations between stomatal aperture and evapotranspiration (ET) during the growing season at the diurnal scale. Based on these observations, we obtain accurate parameters for the mechanistic representation of photosynthesis and stomatal aperture. Once the new parameters are implemented, the model reproduces the stomatal leaf conductance and the leaf-level photosynthesis satisfactorily. At the canopy scale, we find a consistent diurnal pattern on the contributions of plant transpiration and soil evaporation using different measurement techniques. From highly resolved vertical profile measurements of carbon dioxide (

For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

Droughts and heat waves deeply interact with the exchange of energy and matter between land surface and atmosphere. The conditions associated with a combined heat wave and drought can have positive or negative effects on the sensible heat flux (H), latent heat flux (LE), and net flux of CO2 (NEE). In return, while each of these fluxes can exert different local feedbacks on temperature, atmospheric humidity and soil moisture, all of them result in bulk heating of the troposphere (H and LE through direct local and indirect non-local heat transfer, and NEE through radiative forcing). H is positively affected by increased solar irradiation, but can be supressed by advection of warm air diminishing the gradient between surface and air temperature. Potential LE is positively affected by irradiation, temperature and water vapour pressure deficit, but actual LE can be suppressed by stomatal closure of plants and by reduced soil moisture from low rainfall and high past LE. NEE is the result of plant photosynthesis (GPP) and plant and soil respiration (R), both of which can be enhanced by high temperatures or irradiation, and suppressed by drought. Focusing on direct measurements mostly by a network of Eddy-Covariance (EC) stations of the ICOS (www.icosri.eu), TERENO (www.tereno.net) and other networks, we hypothesize that the net effect of the 2018 event at a site, and thus its feedback on global warming, depends on the balance between co-existing positive and negative effects of the combined heat wave and drought on the respective fluxes. Variables such as albedo, growing degreedays (GDD), soil moisture and ecosystem-level water use efficiency help to separate these co-existing positive and negative effects from each other. Preliminary results indicate different degrees of heterogeneity between sites fordifferent variables. As expected, reduced precipitation and soil moisture, as well as increased GDD, could be found at almost all sites in the affected region. NEE was mostly less negative, indicating a weaker sink or even a source forCO2, as expected from past studies on earlier events. The network density and number of site-years available now confirms that this was true for all major ecosystem types - forest, grassland and (rainfed) cropland, and resultedin increased atmospheric CO2 concentrations. However, notable exceptions occurred at elevated low mountain range sites and during early stages of the event, supporting the hypothesis of a balance between positive andnegative effects, where the former may prevail at strongly energy-limited sites with a usually large water surplus. H was mostly above-average, indicating that local heat production contributed to the event and was typically notsuppressed by warm air advection. LE as well as inferred GPP and R reacted most heterogeneously across sites, demonstrating the large discrepancy between potentially high fluxes due to high irradiation and temperature on theone hand, and suppression by water shortage on the other hand. Despite the variability in LE, its relation to NEE was such that ecosystem-level water use was less efficient than usual at the majority of sites through reduced CO2uptake.

Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled "Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors", is shared via Forschungszentrum Julich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021)., Earth System Science Data, 14 (3), ISSN:1866-3516, ISSN:1866-3508