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A detailed representation of plant hydraulic traits and stomatal closure in land surface models (LSMs) is a prerequisite for improved predictions of ecosystem drought response. This work presents the integration of a macroscopic root water uptake (RWU) model based on the hydraulic architecture approach in the LSM of the Terrestrial Systems Modeling Platform. The novel RWU approach is based on three parameters derived from first principles that describe the root system equivalent conductance, the compensatory RWU conductance, and the leaf water potential at stomatal closure, which defines the water stress condition for the plants. The developed RWU model intrinsically accounts for changes in the root density as well as for the simulation of the hydraulic lift process. The standard and the new RWU approach are compared by performing point-scale simulations for cropland over a sheltered minirhizotron facility in Selhausen, Germany, and validated against transpiration fluxes estimated from sap flow and soil water content measurements at different depths. Numerical sensitivity experiments are carried out using different soil textures and root distributions in order to evaluate the interplay between soil hydrodynamics and plant characteristics, and the impact of assuming time-constant plant physiological properties. Results show a good agreement between simulated and observed transpiration fluxes for both RWU models, with a more distinct response under water stress conditions and with uncertainty in the soil parameterization prevailing to the differences due to changes in the model formulation. The hydraulic RWU model exhibits also a lower sensitivity to the root distributions when simulating the onset of the water stress period. Finally, an analysis of variability across the soil and root scenarios indicates that differences in soil water content are mainly influenced by the root distribution, while the transpiration flux in both RWU models is additionally determined by the soil characteristics. ispartof: AGRICULTURAL AND FOREST METEOROLOGY vol:269 pages:28-45 status: published

Thermal infrared sensing of evapotranspiration (E) through surface energy balance (SEB) models is challenging due to uncertainties in determining the aerodynamic conductance (g(A)) and due to inequalities between radiometric (T-R) and aerodynamic temperatures (T-0). We evaluated a novel analytical model, the Surface Temperature Initiated Closure (STIC1.2), that physically integrates T-R observations into a combined Penman-Monteith Shuttleworth-Wallace (PM-SW) framework for directly estimating E, and overcoming the uncertainties associated with T0 and gA determination. An evaluation of STIC1.2 against high temporal frequency SEB flux measurements across an aridity gradient in Australia revealed a systematic error of 10-52% in E from mesic to arid ecosystem, and low systematic error in sensible heat fluxes (H) (12-25%) in all ecosystems. Uncertainty in TR versus moisture availability relationship, stationarity assumption in surface emissivity, and SEB closure corrections in E were predominantly responsible for systematic E errors in arid and semi-arid ecosystems. A discrete correlation (r) of the model errors with observed soil moisture variance (r = 0.33-0.43), evaporative index (r = 0.77-0.90), and climatological dryness (r = 0.60-0.77) explained a strong association between ecohydrological extremes and T-R in determining the error structure of STIC1.2 predicted fluxes. Being independent of any leaf-scale biophysical parameterization, the model might be an important value addition in working group (WG2) of the Australian Energy and Water Exchange (OzEWEX) research initiative which focuses on observations to evaluate and compare biophysical models of energy and water cycle components. Plain Language Summary Evapotranspiration modeling and mapping in arid and semi-arid ecosystems are uncertain due to empirical approximation of surface and atmospheric conductances. Here we demonstrate the performance of a fully analytical model which is independent of any leaf-scale empirical parameterization of the conductances and can be potentially used for continental scale mapping of ecosystem water use as well as water stress using thermal remote sensing satellite data.d

The failure of the Monin–Obukhov Similarity Theory (MOST) in the roughness sublayer is a major problem for the estimation of fluxes over tall forests, whenever indirect methods that rely on MOST, such as flux-gradient or the variance method, are involved. While much research focuses on micrometeorological measurements over temperate-climate forests, very few studies deal with such measurements over tropical forests. In this paper, we show evidence that some similarity functions over the Amazon forest are somewhat different from temperate forests. Comparison of the nondimensional scalar gradients canonical values for the inertial sublayer with our measurements in the roughness sublayer showed smaller deviations than what is usually reported for temperate forests. Although the fluxes of water vapor and CO2 derived from mean profiles show considerable scatter when compared with the eddy covariance measurements, using calibrated dimensionless gradients it is possible to estimate their mean daily cycle during the period of measurement (36 days in May and June, transition between rainy and dry season). Moreover, since mean ozone profiles were available, although without the corresponding eddy covariance measurements, mean daily ozone fluxes were calculated with the flux-gradient method, yielding a nighttime value of −0.05 and a daily peak of −0.45 μg m−2 s−1 (−1.04 and −9.37 nmol m−2 s−1, respectively). These values are comparable to previously measured fluxes in the literature for the Amazon forest.

While modeling approaches of evapotranspiration (λE) perform reasonably well when evaluated at daily or monthly timescales, they can show systematic deviations at the sub-daily timescale, which results in potential biases in modeled λE to global climate change. Here we decompose the diurnal variation of heat fluxes and meteorological variables into their direct response to incoming solar radiation (Rsd) and a phase shift to Rsd. We analyze data from an eddy-covariance (EC) station at a temperate grassland site, which experienced a pronounced summer drought. We employ three structurally different modeling approaches of λE, which are used in remote sensing retrievals, and quantify how well these models represent the observed diurnal cycle under clear-sky conditions. We find that energy balance residual approaches, which use the surface-to-air temperature gradient as input, are able to reproduce the reduction of the phase lag from wet to dry conditions. However, approaches which use the vapor pressure deficit (Da) as the driving gradient (Penman–Monteith) show significant deviations from the observed phase lags, which is found to depend on the parameterization of surface conductance to water vapor. This is due to the typically strong phase lag of 2–3 h of Da, while the observed phase lag of λE is only on the order of 15 min. In contrast, the temperature gradient shows phase differences in agreement with the sensible heat flux and represents the wet–dry difference rather well. We conclude that phase lags contain important information on the different mechanisms of diurnal heat storage and exchange and, thus, allow a process-based insight to improve the representation of land–atmosphere (L–A) interactions in models.

An important current problem in micrometeorology is the characterization of turbulence in the roughness sublayer (RSL), where most of the measurements above tall forests are made. There, scalar turbulent fluctuations display significant departures from the predictions of Monin?Obukhov similarity theory (MOST). In this work, we analyze turbulence data of virtual temperature, carbon dioxide, and water vapor in the RSL above an Amazonian forest (with a canopy height of 40 m), measured at 39.4 and 81.6 m above the ground under unstable conditions. We found that dimensionless statistics related to the rate of dissipation of turbulence kinetic energy (TKE) and the scalar variance display significant departures from MOST as expected, whereas the vertical velocity variance follows MOST much more closely. Much better agreement between the dimensionless statistics with the Obukhov similarity variable, however, was found for the subset of measurements made at a low zenith angle Z, in the range 0°

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman–Monteith and Shuttleworth–Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy–atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land–surface–atmosphere exchange parameterizations across a range of spatial scales.

Missing data in river flow records represent a loss of information and a serious drawback in water management. In this work, we introduce gapIt, a user-driven case-based reasoning tool for infilling gaps in daily mean river flow records. Given a set of flow time series, gapIt builds a database of artificial gaps for which it computes several flow estimates, to find the best combinations of infilling algorithm and automatically selected donor station(s), according to state-of-the-art performance indicators. We obtained satisfactory results with Nash-Sutcliffe >0.7 for more than half of the ~5000 synthetic gaps of various lengths and positions, randomly created along the available records. gapIt was evaluated on 24 daily river discharge time series recorded in Luxembourg over seven years from 01/01/2007 to 31/12/2013. We also discuss the benefits of coupling this approach with user-expertise for an improved infilling of real data gaps. We propose a user-driven case-based reasoning tool to infill gaps in flow records.With data analytics the tool finds the best combination: algorithm - donor stations.Satisfactory results were obtained on synthetic gaps of different characteristics.The tool bridges a gap between data-driven and user-expertise approaches.

This study reports NO, NO2 and O3 mixing ratios and flux measurements using the eddy covariance method during a 7-month period over an oilseed-rape field, spanning an organic and a mineral fertilisation event. Cumulated NO emissions during the whole period were in agreement with previous studies and showed quite low emissions of 0.26 kg N ha−1 with an emission factor of 0.27 %, estimated as the ratio between total N emitted in the form of NO and total N input. The NO emissions were higher following organic fertilisation in August due to conditions favouring nitrification (soil water content around 20 % and high temperatures), while mineral fertilisation in February did not result in high emissions. The ozone deposition velocity increased significantly after organic fertilisation. The analysis of the chemical and turbulent transport times showed that reactions between NO, NO2 and O3 below the measurement height occurred constantly throughout the 7-month period. Following organic fertilisation, the NO ground fluxes were 30 % larger than the NO fluxes at the measurement height (3.2 m), while the NO2 fluxes switched from deposition to emission during certain periods, being negative at the surface and positive at the measurement height. This phenomenon of apparent NO2 emissions appears to be significant during strong NO emissions and high O3 ambient mixing ratios, even on a bare soil during August.

[1] This study evaluates ozone (O3) deposition to an agricultural field over a period of 2 years. A two-layer soil-vegetation-atmosphere-transfer (Surfatm-O3) model is used to partition the O3 flux between the soil, the cuticular, and the stomatal pathways. The comparison between measured and modeled O3 fluxes exhibited a good agreement, independently of the canopy structure and coverage and the climatic conditions, which implicitly validates the O3 flux partitioning. The total, soil, cuticular, and stomatal O3 budgets are then established from the modeling. Total ecosystem O3 deposition over the 2 year period was 87.5 kg ha−1. Clearly, nonstomatal deposition dominates the deposition budget, especially the soil component which represented up to 50% of the total deposition. Nevertheless, the physiological and phenological differences of maize and winter wheat induced large difference in the stomatal deposition budgets of these two crops. Then, the effect of simplified parameterizations for soil and cuticular resistances currently used in other models on the O3 budget is tested. Independently, these simplified parameterizations cause an underestimation of the O3 deposition ranging between 0% and 11.2%. However, the combination of all simplifications resulted in an underestimation of the total O3 deposition by about 20%. Finally, crop yield loss was estimated to be 1.5–4.2% for the winter wheat, whereas maize was not affected by O3.

Nowadays, eddy covariance is the state-of-the-art method to quantify turbulent exchange fluxes in the surface boundary layer. In the absence of instruments suitable for high-frequency measurements, fluxes can also be determined using e.g., chamber techniques. However, up to date fluxes of depositing compounds were rarely determined using chamber techniques, mainly due to a modification of the aerodynamic conditions for the trace gas transport within the chamber. In this study, we present ozone (O3) deposition fluxes measured by the dynamic chamber technique and validate them against the eddy covariance (EC) method for a natural grassland site in Germany. The chamber system presented in Pape et al. (2009) was used and optimized to (i) reduce the likelihood of non-stationarities, (ii) yield 30 min averages of flux measurements, and (iii) supply simultaneous profile measurements. The raw O3 fluxes of the dynamic chamber were corrected for gas-phase chemistry in the chamber volume and for the modification of the aerodynamic and boundary layer resistances. Simultaneously measured carbon dioxide and water vapor fluxes by both methods compared well during daytime documenting an equal vegetation activity inside and outside the chambers. The final corrected O3 deposition fluxes of both methods deviated on average by only 11% during daytime. The findings demonstrate the capability of the dynamic chamber method to capture representative O3 deposition fluxes for grassland ecosystems, even when the canopy height is similar to the chamber height. The canopy resistance to O3 was assessed by both methods and showed a characteristic diurnal cycle with minimum hourly median values of 180 s m−1 (chambers) and 150 s m−1 (EC) before noon. During nighttime the fluxes and resistances showed a higher uncertainty for both methods due to frequent low wind associated with non-stationary conditions at the experimental site. Canopy resistances for nitrogen dioxide (NO2) deposition were determined analogously with the chambers and were on average 86% higher than for O3.

The input of nitrogen (N) to ecosystems has increased dramatically over the past decades. While total (wet+dry) N deposition has been extensively determined in temperate regions, only very few data sets of N wet deposition exist for tropical ecosystems, and moreover, reliable experimental information about N dry deposition in tropical environments is lacking. In this study we estimate dry and wet deposition of inorganic N for a remote pasture site in the Amazon Basin based on in-situ measurements. The measurements covered the late dry (biomass burning) season, a transition period and the onset of the wet season (clean conditions) (12 September to 14 November 2002) and were a part of the LBA-SMOCC (Large-Scale Biosphere-Atmosphere Experiment in Amazonia – Smoke, Aerosols, Clouds, Rainfall, and Climate) 2002 campaign. Ammonia (NH3), nitric acid (HNO3), nitrous acid (HONO), nitrogen dioxide (NO2), nitric oxide (NO), ozone (O3), aerosol ammonium (NH4+) and aerosol nitrate (NO3-) were measured in real-time, accompanied by simultaneous meteorological measurements. Dry deposition fluxes of NO2 and HNO3 are inferred using the ''big leaf multiple resistance approach'' and particle deposition fluxes are derived using an established empirical parameterization. Bi-directional surface-atmosphere exchange fluxes of NH3 and HONO are estimated by applying a ''canopy compensation point model''. N dry and wet deposition is dominated by NH3 and NH4+, which is largely the consequence of biomass burning during the dry season. The grass surface appeared to have a strong potential for daytime NH3 emission, owing to high canopy compensation points, which are related to high surface temperatures and to direct NH3 emissions from cattle excreta. NO2 also significantly accounted for N dry deposition, whereas HNO3, HONO and N-containing aerosol species were only minor contributors. Ignoring NH3 emission from the vegetation surface, the annual net N deposition rate is estimated to be about −11 kgN ha-1 yr-1. If on the other hand, surface-atmosphere exchange of NH3 is considered to be bi-directional, the annual net N budget at the pasture site is estimated to range from −2.15 to −4.25 kgN ha-1 yr-1.

This study investigates the influence of leaf surface water films on the deposition of ozone (O3) and peroxyacetyl nitrate (PAN) under controlled laboratory conditions. A twin cuvette system was used to simulate environmental variables. We observed a clear correlation between the O3 deposition on plants (Quercus ilex) and the relative humidity (RH) under both, light and dark conditions. During the light period the observed increase of the O3 deposition was mainly attributed to the opening of leaf stomata, while during the absence of light the liquid surface films were the reason for O3 deposition. This finding was supported by experimentally induced stomatal closure by the infiltration of abscisic acid. In the case of PAN, no relationship with RH was found during the dark period, which indicates that the non-stomatal deposition of PAN is not affected by the liquid surface films. Consequently, the ratio of the O3 and PAN deposition velocities is not constant when relative humidity changes, which is in contrast to assumptions made in many models. The flux partitioning ratio between non-stomatal and stomatal deposition as well as between non-stomatal and total deposition was found to be Rnsto/sto = 0.21 – 0.40, Rnsto/tot = 0.18 – 0.30 for O3 and Rnsto/sto = 0.26 – 0.29, Rnsto/tot = 0.21 – 0.23 for PAN. Furthermore, we demonstrate that the formation of the liquid surface film on leaves and the non-stomatal O3 deposition are depending on the chemical composition of the particles deposited on the leaf cuticles as proposed previously.

Hydroxyl radicals (OH) are a key species in atmospheric photochemistry. In the lower atmosphere, up to ~30% of the primary OH radical production is attributed to the photolysis of nitrous acid (HONO), and field observations suggest a large missing source of HONO. We show that soil nitrite can release HONO and explain the reported strength and diurnal variation of the missing source. Fertilized soils with low pH appear to be particularly strong sources of HONO and OH. Thus, agricultural activities and land-use changes may strongly influence the oxidizing capacity of the atmosphere. Because of the widespread occurrence of nitrite-producing microbes, the release of HONO from soil may also be important in natural environments, including forests and boreal regions.

From Soil to Sky Trace gases emitted either through the activity of microbial communities or from abiotic reactions in the soil influence atmospheric chemistry. In laboratory column experiments using several soil types, Oswald et al. (p. 1233 ) showed that soils from arid regions and farmlands can produce substantial quantities of nitric oxide (NO) and nitrous acid (HONO). Ammonia-oxidizing bacteria are the primary source of HONO at comparable levels to NO, thus serving as an important source of reactive nitrogen to the atmosphere.

As part of a field campaign in the framework of the NitroEurope project, three different instruments for atmospheric ammonia (NH3) measurements were operated side-by-side on a managed grassland site in Switzerland: a modified Proton Transfer Reaction Mass Spectrometer (PTR-MS), a GRadient of AErosol and Gases Online Registrator (GRAEGOR), and an Automated Ammonia Analyzer (AiRRmonia). The modified PTR-MS approach is based on chemical ionization of NH3 using O2+ instead of H3O+ as ionizing agent, GRAEGOR and AiRRmonia measure NH4+ in liquids after absorption of gaseous NH3 in a rotating wet-annular denuder and through a gas permeable membrane, respectively. Bivariate regression slopes using uncorrected data from all three instruments ranged from 0.78 to 0.97 while measuring ambient NH3 levels between 2 and 25 ppbv during a 5 days intercomparison period. Correlation coefficients r2 were in the range of 0.79 to 0.94 for hourly average mixing ratios. Observed discrepancies could be partly attributed to temperature effects on the GRAEGOR calibration. Bivariate regression slopes using corrected data were >0.92 with offsets ranging from 0.22 to 0.58 ppbv. The intercomparison demonstrated the potential of PTR-MS to resolve short-time NH3 fluctuations which could not be measured by the two other slow-response instruments. During conditions favoring condensation in inlet lines, the PTR-MS underestimated NH3 mixing ratios, underlining the importance of careful inlet designs as an essential component for any inlet-based instrument.