H. P. Schmid

Karlsruhe Institute of Technology, Carlsruhe, Baden-Württemberg, Germany

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Publications (119)249.44 Total impact

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    ABSTRACT: A general lack of energy balance closure indicates that tower-based eddy-covariance (EC) measurements underestimate turbulent heat fluxes, which calls for robust correction schemes. Two parametrization approaches that can be found in the literature were tested using data from the Canadian Twin Otter research aircraft and from tower-based measurements of the German Terrestrial Environmental Observatories (TERENO) programme. Our analysis shows that the approach of Huang et al. (Boundary-Layer Meteorol 127:273–292, 2008), based on large-eddy simulation, is not applicable to typical near-surface flux measurements because it was developed for heights above the surface layer and over homogeneous terrain. The biggest shortcoming of this parametrization is that the grid resolution of the model was too coarse so that the surface layer, where EC measurements are usually made, is not properly resolved. The empirical approach of Panin and Bernhofer (Izvestiya Atmos Oceanic Phys 44:701–716, 2008) considers landscape-level roughness heterogeneities that induce secondary circulations and at least gives a qualitative estimate of the energy balance closure. However, it does not consider any feature of landscape-scale heterogeneity other than surface roughness, such as surface temperature, surface moisture or topography. The failures of both approaches might indicate that the influence of mesoscale structures is not a sufficient explanation for the energy balance closure problem. However, our analysis of different wind-direction sectors shows that the upwind landscape-scale heterogeneity indeed influences the energy balance closure determined from tower flux data. We also analyzed the aircraft measurements with respect to the partitioning of the “missing energy” between sensible and latent heat fluxes and we could confirm the assumption of scalar similarity only for Bowen ratios $\approx $ 1.
    Boundary-Layer Meteorology 05/2014; 151(2). · 2.29 Impact Factor
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    Nature 03/2014; 507(7491):E2-3. · 38.60 Impact Factor
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    ABSTRACT: Predicted decreases in water availability across the temperate forest biome have the potential to offset gains in carbon (C) uptake from phenology trends, rising atmospheric CO2 , and nitrogen deposition. While it is well-established that severe droughts reduce the C sink of forests by inducing tree mortality, the impacts of mild but chronic water stress on forest phenology and physiology are largely unknown. We quantified the C consequences of chronic water stress using a 13-year record of tree growth (n = 200 trees), soil moisture, and ecosystem C balance at the Morgan-Monroe State Forest (MMSF) in Indiana, and a regional 11-year record of tree growth (n >300,000 trees) and water availability for the 20 most dominant deciduous broadleaf tree species across the Eastern and Midwestern USA. We show that despite ~26 more days of C assimilation by trees at the MMSF, increasing water stress decreased the number of days of wood production by ~42 days over the same period, reducing the annual accrual of C in woody biomass by 41%. Across the deciduous forest region, water stress induced similar declines in tree growth, particularly for water-demanding "mesophytic" tree species. Given the current replacement of water-stress adapted "xerophytic" tree species by mesophytic tree species, we estimate that chronic water stress has the potential to decrease the C sink of deciduous forests by up to 17% (0.04 Pg C yr(-1) ) in the coming decades. This reduction in the C sink due to mesophication and chronic water stress is equivalent to an additional 1 to 3 days of global C emissions from fossil fuel burning each year. Collectively, our results indicate that regional declines in water availability may offset the growth-enhancing effects of other global changes and reduce the extent to which forests ameliorate climate warming. This article is protected by copyright. All rights reserved.
    Global Change Biology 01/2014; · 6.91 Impact Factor
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    ABSTRACT: Multicompartment and multiscale long-term observation and research are important prerequisites to tackling the scientific challenges resulting from climate and global change. Long-term monitoring programs are cost intensive and require high analytical standards, however, and the gain of knowledge often requires longer observation times. Nevertheless, several environmental research networks have been established in recent years, focusing on the impact of climate and land use change on terrestrial ecosystems. From 2008 onward, a network of Terrestrial Environmental Observatories (TERENO) has been established in Germany as an interdisciplinary research program that aims to observe and explore the long-term ecological, social, and economic impacts of global change at the regional level. State-of-the-art methods from the field of environmental monitoring, geophysics, and remote sensing will be used to record and analyze states and fluxes for different environmental compartments from groundwater compartments from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere.
    Vadose Zone Journal 12/2013; 10(2011):955-973. · 2.20 Impact Factor
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    ABSTRACT: Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata-small pores on the leaf surface that regulate gas exchange-to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation-climate models.
    Nature 07/2013; · 38.60 Impact Factor
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    ABSTRACT: Many future environmental changes will be caused by global climate change. To find solutions which help to deal with alterations in climate, ecosystem productivity, and water resources, an interdisciplinary and long-term research programme involving six Helmholtz Association Centers, was established in Germany. TERENO (Terrestrial Environmental Observatories) spans an Earth observation network that extends from the North German lowlands to the Bavarian Alps. This large-scale project aims to catalogue the longterm ecological, social and economic impact of global change at regional level. In this contribution we mainly describe the infrastructure which is used to determine the atmosphere-biosphere exchange of trace gases and energy in four German regions with different land use and climatic and edaphic conditions. A strong focus will be on the terrestrial water budgets, such as variability of precipitation and soil moisture, but also on the partitioning of evapotranspiration with the help of intensive sap flow measurements. Some of the TERENO sites do also contribute to the ICOS infrastructure where the main focus is the quantification of greenhouse gases with standardized measurement techniques. The TERENO sites involved are located in the Northeastern German Lowland (GFZ), Central Germany Lowland / Harz (UFZ), the Lower Rhine Valley / Eifel (FZJ) and in the Bavarian Prealps (KIT).
    04/2013;
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    ABSTRACT: Eddy Covariance (EC) measurements often do not close the energy balance. This indicates that surface heat fluxes are underestimated, likely because large-scale eddies and stationary circulations are not captured. Because EC is a widespread tool in environmental science to assess energy fluxes and trace gas budgets, it is essential to quantify the 'missing' fluxes. In the literature, two approaches to parameterise the lack of energy balance closure can be found. The first one by Huang et al (2008) is based on large-eddy simulations (LES) and perceives the energy imbalance as being the result of large-scale turbulent organized structures. The second approach by Panin and Bernhofer (2008) suggests an empirical approach which focuses on surface roughness heterogeneities on the landscape-scale. We tested both approaches with EC data from three sites, located in southern Germany, of the Terrestrial Environmental Observatories (TERENO) programme. Additionally, we applied the parameterisations to aircraft data from Canada, which were conducted as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) experiment and the Boreal Ecosystem Research and Monitoring Sites (BERMS) programme. For each flight, the flux contribution of turbulent structures larger than 2 km, determined by wavelet analysis, serves as an estimate of the missing flux of conventional EC measurements. In most cases, the two parameterisations do not give a reliable prediction of the energy balance residual. The approach of Panin and Bernhofer (2008) disregards topographical effects, differences in surface moisture and surface temperature and thus, it cannot explain the poor energy balance closure of the TERENO sites. However, above the flat terrain of the airborne measurements in Canada, it works surprisingly well. The parameterisation by Huang et al (2008) was developed for homogeneous terrain, a condition which is almost never met in field studies. In addition, there is a general mismatch between LES and tower-based measurements: the simulations almost close the energy balance near the surface, presumably due to the too coarse grid resolution. Therefore, this parameterisation is not really applicable to typical flux measurements in heterogeneous landscapes that are usually conducted in the surface layer. References: Huang J, Lee X, Patton E (2008) A modelling study of flux imbalance and the influence of entrainment in the convective boundary layer. Boundary Layer Meteorol 127:273-292. Panin GN, Bernhofer Ch (2008) Parametrization of turbulent fluxes over inhomogeneous landscapes. Izvestiya Atmos Oceanic Phys 44:701-716.
    04/2013;
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    ABSTRACT: Eddy-covariance measurements are routinely performed worldwide on a long-term basis, in order to observe ecosystem exchange of trace gases, water and energy. The data obtained are needed to validate or constrain process-based models and for evaluating ecosystem budgets. There is a strong demand for consistent and comprehensive quality flagging and uncertainty quantification to assure comparability of datasets from different sites. We review established quality assessment procedures and suggest a newly composed strategy comprising tests on high-frequency raw data, tests on statistics, fluxes and corrections. Additionally, we quantify different types of errors. This strategy will be applied within the recently launched TERENO network of ecosystem observatories. Five test datasets from TERENO and CarboEurope-IP were subjected to the specific quality assessment scheme. These datasets include two different sonic types, open- and closed-path instruments, tall and low vegetation, flat and complex terrain. We show the robustness and applicability of the scheme to data acquired with the different measurement set-ups. Coherences between established flagging schemes and newly added error determination are demonstrated. This uncertainty assessment for each flux estimate represents an indispensable value for modeling as well as for budgeting fluxes.
    04/2013;
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    ABSTRACT: The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50–100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River catchment (≈3670 km2) are accurate to ≤18% (1 σ). The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m−2 < H < 364 W m−2, 46 W m−2 < LE < 425 W m−2) and spatial variability (11 W m−2 < σH < 169 W m−2, 14 W m−2 < σLE < 152 W m−2) to a precision of ≤5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River catchment. Agreement of the land cover specific Bowen ratios to within 12 ± 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.
    Biogeosciences 01/2013; 10(4):2193-2217. · 3.75 Impact Factor
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    ABSTRACT: Eddy-covariance measurements are performed at several hundred sites all over the world on a long-term basis. The gathered data are used to characterise ecosystem exchanges of trace gases, water and energy and to validate or constrain process-based models. There is an increasing demand on standardised and comprehensive quality flagging and uncertainty quantification of these fluxes. In this paper, we review established quality assessment procedures and present a comprehensive newly composed strategy emphasising tests on high-frequency raw data, expanding existing tests on statistics, fluxes and corrections, plus quantification of errors. Moreover, representativity of fluxes is checked by footprint analysis. This strategy is applied within the recently launched TERENO network of ecosystem observatories, and its robustness is demonstrated for data acquired with different measurement set-ups. Four test data sets from TERENO and one data set from CarboEurope-IP were subjected to this quality assessment. The presented strategy is compared with established quality assessment schemes, and it is demonstrated that unrealistic fluxes are now efficiently excluded while retaining the largest possible amount of high quality data. Additionally, the algorithms applied provide comprehensive, reproducible, qualitative and quantitative uncertainty estimates for users of eddy-covariance flux data.
    Agricultural and Forest Meteorology 01/2013; 169:122–135. · 3.42 Impact Factor
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    ABSTRACT: Measurements of land-surface emission rates of greenhouse and other gases at large spatial scales (10 000 m2) are needed to assess the spatial distribution of emissions. This can be readily done using spatial-integrating micro-meteorological methods like flux-gradient methods which were evaluated for determining land-surface emission rates of trace gases under stable boundary layers. Non-intrusive path-integrating measurements are utilized. Successful application of a flux-gradient method requires confidence in the gradients of trace gas concentration and wind, and in the applicability of boundary-layer turbulence theory; consequently the procedures to qualify measurements that can be used to determine the flux is critical. While there is relatively high confidence in flux measurements made under unstable atmospheres with mean winds greater than 1 m s-1, there is greater uncertainty in flux measurements made under free convective or stable conditions. The study of N2O emissions of flat grassland and NH3 emissions from a cattle lagoon involves quality-assured determinations of fluxes under low wind, stable or night-time atmospheric conditions when the continuous "steady-state" turbulence of the surface boundary layer breaks down and the layer has intermittent turbulence. Results indicate that following the Monin-Obukhov similarity theory (MOST) flux-gradient methods that assume a log-linear profile of the wind speed and concentration gradient incorrectly determine vertical profiles and thus flux in the stable boundary layer. An alternative approach is considered on the basis of turbulent diffusivity, i.e. the measured friction velocity as well as height gradients of horizontal wind speeds and concentrations without MOST correction for stability. It is shown that this is the most accurate of the flux-gradient methods under stable conditions.
    Atmospheric Measurement Techniques 07/2012; 5(7):1571-1583. · 3.21 Impact Factor
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    ABSTRACT: Measurements of land-surface emission rates of greenhouse and other gases at large spatial scales (10 000 m2) are needed to assess the spatial distribution of emissions. This can be more readily done using spatial-integrating micro-meteorological methods than the widely-utilized small chamber measurements. Several micro-meteorological flux-gradient methods utilizing a non-intrusive path-averaging measurement method were evaluated for determining land-surface emission rates of trace gases under stable boundary layers. Successful application of a flux-gradient method requires confidence in the gradients of trace gas concentration and wind and in the applicability of boundary-layer turbulence theory. While there is relatively high confidence in flux measurements made under unstable atmospheres with mean winds greater than 1 m s-1, there is greater uncertainty in flux measurements made under free convective or stable conditions. The study involved quality-assured determinations of fluxes under low wind, stable or night-time atmospheric conditions when the continuous "steady-state" turbulence of the surface boundary layer breaks down and the layer has intermittent turbulence. Results indicate that the Monin-Obukhov similarity theory (MOST) flux-gradient methods that assume a log-linear profile of the wind speed and concentration gradient incorrectly determine vertical profiles and thus fluxes in the stable boundary layer.
    Atmospheric Measurement Techniques Discussions. 02/2012; 5(1):1459-1496.
  • Agricultural and Forest Meteorology 01/2012; · 3.42 Impact Factor
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    ABSTRACT: The objective of this study is to assess the feasibility and quality of eddy-covariance flux measurements from a weight-shift microlight aircraft (WSMA). Firstly, we investigate the precision of the wind measurement ( σu,v ≤ 0.09 m s−1, σw = 0.04 m s −1), the lynchpin of flux calculations from aircraft. From here, the smallest resolvable changes in friction velocity (0.02 m s−1), and sensible- (5 W m−2) and latent (3 W m−2) heat flux are estimated. Secondly, a seven-day flight campaign was performed near Lindenberg (Germany). Here we compare measurements of wind, temperature, humidity and respective fluxes between a tall tower and the WSMA. The maximum likelihood functional relationship (MLFR) between tower and WSMA measurements considers the random error in the data, and shows very good agreement of the scalar averages. The MLFRs for standard deviations (SDs, 2–34%) and fluxes (17–21%) indicate higher estimates of the airborne measurements compared to the tower. Considering the 99.5% confidence intervals, the observed differences are not significant, with exception of the temperature SD. The comparison with a large-aperture scintillometer reveals lower sensible heat flux estimates at both tower (−40 to −25%) and WSMA (−25–0%). We relate the observed differences to (i) inconsistencies in the temperature and wind measurement at the tower and (ii) the measurement platforms' differing abilities to capture contributions from non-propagating eddies. These findings encourage the use of WSMA as a low cost and highly versatile flux measurement platform.
    Atmospheric Measurement Techniques 01/2012; 5(7):1699-1717. · 3.21 Impact Factor
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    ABSTRACT: The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River Catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50-100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical- (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River Catchment (≈ 3670 km2) are accurate to ≤ 18%. The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m-2 < H < 364 W m-2, 46 W m-2 < LE < 425 W m-2) and spatial variability (11 W m-2 < σH < 169 W m-2, 14 W m-2 < σLE < 152 W m-2) to a precision of ≤ 5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River Catchment. Agreement of the land cover specific Bowen ratios to within 12 ± 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.
    Boundary-Layer Meteorology 01/2012; · 2.29 Impact Factor
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    ABSTRACT: Ground-based eddy-covariance (EC) measurements are suited to continuously monitor the water and heat exchange above selected sites. However, these results may only represent small areas surrounding the immediate measurement locations. On the other hand, aircraft-based EC measurements can provide flux information on regional scales, but are restricted to short time intervals. It is desirable to integrate both approaches in an effort to provide suitable datasets for the design, constraint, and evaluation of flux algorithms for remote sensing and numerical modeling applications. The objective of this study is to develop environmental response functions (ERF), which enable the integration of ground-based and airborne EC flux measurements. The idea behind ERF is to explicitly relate flux observations (responses) to meteorological forcing and biophysical surface properties (drivers). Thus far ERF have built upon (i) low spatial discretization and binning of airborne flux observations, (ii) discrete land cover representations, and (iii) parametric relationships. Here, we present an approach that advances the scalability of ERFs, and enables the rigorous quantification of uncertainty. This approach consists of; (i) wavelet decomposition of airborne EC high-frequency data, which enables high resolution flux observations, (ii) quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation, and (iii) boosted regression trees, that enable detecting highly non-linear ERFs according to the information in the data. The resulting ERFs can then be used to extrapolate the water and heat exchange, e.g. across a watershed. We apply the present approach to airborne EC flux measurements that were conducted in July 2009 at ≈50 m above the heterogeneous steppe landscape of the Xilin River Watershed, Inner Mongolia, P.R. China. The wavelet decomposition of the turbulence data results in 8446 flux observations during 12 flights. Using footprint modeling, the MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in the source area of each observation are determined. Boosted regression trees are then used to infer ERFs between all observations of the sensible- and latent heat flux (H, LE) and biophysical- (LST, EVI) and meteorological drivers. Numerical tests show that ERF extrapolations covering the entire Xilin River Watershed (≈ 3670 km2) are accurate to ≤ 18%. The extrapolations are then summarized for each land cover type, providing individual estimates of source strength (40 W m−2 < H < 359 W m−2, 68 W m−2 < LE < 300 W m−2) and spatial variability (17 W m−2 < H < 129 W m−2, 35 W m−2 < LE < 134 W m−2) to a precision of ≤ 5%. This study demonstrates the potential of ERFs for ‘mining‘ the information content of EC flux observations and extracting quantitative relationships with environmental drivers. In doing so, ERFs can aid bridging observational scales by, e.g., isolating and quantifying relevant land-atmosphere exchange processes, extending flux measurements to the watershed scale, assessing the spatial representativeness of EC flux measurements etc. Deriving analogous ERFs from ground-based EC measurements could aid, e.g., constraining local to regional water budgets, distinguishing anthropogenic and natural sources/sinks in urban environments, and substantiating process-studies.
    45 th AGU annual Fall Meeting45 th AGU annual Fall Meeting; 01/2012

Publication Stats

2k Citations
249.44 Total Impact Points

Institutions

  • 2011–2014
    • Karlsruhe Institute of Technology
      • Institute of Meteorology and Climate Research
      Carlsruhe, Baden-Württemberg, Germany
  • 2013
    • Harvard University
      • Department of Organismic and Evolutionary Biology
      Cambridge, MA, United States
  • 2002–2011
    • Indiana University Bloomington
      • Department of Geography
      Bloomington, IN, United States
  • 2009–2010
    • Klinikum Garmisch-Partenkirchen
      Markt Garmisch-Partenkirchen, Bavaria, Germany
    • University of New Hampshire
      • Complex Systems Research Center
      Durham, New Hampshire, United States
    • Indiana University Kokomo
      Kokomo, Indiana, United States
  • 2008
    • East Carolina University
      • Department of Geography
      North Carolina, United States