Recent European heatwaves have raised interest in the impact of land cover conditions on temperature extremes. At present, it is believed that such extremes are enhanced by stronger surface heating of the atmosphere, when soil moisture content is below average. However, the impact of land cover on the exchange of water and energy and the interaction of this exchange with the soil water balance during heatwaves is largely unknown. Here we analyse observations from an extensive network of flux towers in Europe that reveal a difference between the temporal responses of forest and grassland ecosystems during heatwaves. We find that initially, surface heating is twice as high over forest than over grassland. Over grass, heating is suppressed by increased evaporation in response to increased solar radiation and temperature. Ultimately, however, this process accelerates soil moisture depletion and induces a critical shift in the regional climate system that leads to increased heating. We propose that this mechanism may explain the extreme temperatures in August 2003. We conclude that the conservative water use of forest contributes to increased temperatures in the short term, but mitigates the impact of the most extreme heat and/or long-lasting events
The energy balance at most surface-atmosphere flux research sites remains unclosed. The mechanisms underlying the discrepancy between measured energy inputs and outputs across the global FLUXNET tower network are still under debate. Recent reviews have identified exchange processes and turbulent motions at large spatial and temporal scales in heterogeneous landscapes as the primary cause of the lack of energy balance closure at some intensively-researched sites, while unmeasured storage terms cannot be ruled out as a dominant contributor to the lack of energy balance closure at many other sites. We analyzed energy balance closure across 173 ecosystems in the FLUXNET database and explored the relationship between energy balance closure and landscape heterogeneity using MODIS products and GLOBEstat elevation data. Energy balance closure per research site (CEB,s) averaged 0.84 ± 0.20, with best average closures in evergreen broadleaf forests and savannas (0.91–0.94) and worst average closures in crops, deciduous broadleaf forests, mixed forests and wetlands (0.70–0.78). Half-hourly or hourly energy balance closure on a percent basis increased with friction velocity (u*) and was highest on average under near-neutral atmospheric conditions. CEB,s was significantly related to mean precipitation, gross primary productivity and landscape-level enhanced vegetation index (EVI) from MODIS, and the variability in elevation, MODIS plant functional type, and MODIS EVI. A linear model including landscape-level variability in both EVI and elevation, mean precipitation, and an interaction term between EVI variability and precipitation had the lowest Akaike’s information criterion value. CEB,s in landscapes with uniform plant functional type approached 0.9 and CEB,s in landscapes with uniform EVI approached 1. These results suggest that landscape-level heterogeneity in vegetation and topography cannot be ignored as a contributor to incomplete energy balance closure at the flux network level, although net radiation measurements, biological energy assimilation, unmeasured storage terms, and the importance of good practice including site selection when making flux measurements should not be discounted. Our results suggest that future research should focus on the quantitative mechanistic relationships between energy balance closure and landscape-scale heterogeneity, and the consequences of mesoscale circulations for surface-atmosphere exchange measurements
Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO 2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid-and high-latitudes, (2) a strong function of dryness at mid-and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45 • N). The sensitivity of NEE to mean annual temperature breaks down at ∼16 • C (a threshold value of mean annual temperature), above which no further increase of CO 2 uptake with temperature was observed and dryness influence overrules temperature influence.
Abstract. We applied a site evaluation approach combining Lagrangian Stochastic footprint modeling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.
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