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Abstract: Deposition of trace gases, such as sulfur dioxide (SO2), can affect plant and soil chemistry in different ecosystems. Measurements over a complex ecosystem, like a forest clearing, are necessary to determine more accurate deposition rates that can be used to improve parameterizations and models. The flux-gradient technique was used to determine SO2 fluxes over grass in a clearing at Duke Forest, North Carolina, USA on 25 June – 2 July 2008. The mean flux was −0.037 ± 0.024 μg m−2 s−1. Dew on the canopy enhanced the uptake of SO2, which increased deposition rates. Deposition velocities (Vd ) fluctuated greatly with a mean of 1.00 ± 0.48 cm s−1. The large variation in Vd was not fully captured by estimates determined from a multilayer model (MLM) and a big-leaf model (BLM). Mean deposition velocities derived from the MLM and BLM were 1.25 ± 0.21 cm s−1 and 0.63 ± 0.12 cm s−1, respectively. The model estimations of Vd in this study were probably affected by uncertainties associated with canopy resistance, particularly with stomatal and non-stomatal processes. [Copyright &y& Elsevier]

Surface-layer parameterizations for heat, mass, momentum, and turbulence exchange are a critical component of the land surface models (LSMs) used in weather prediction and climate models. Although formulations derived from Monin–Obukhov similarity theory (MOST) have long been used, bulk Richardson (Rib) parameterizations have recently been suggested as a MOST alternative but have been evaluated over a limited number of land-cover and climate types. Examining the parameterizations' applicability over other regions, particularly drylands that cover approximately 41% of terrestrial land surfaces, is a critical step toward implementing the parameterizations into LSMs. One year (1 January–31 December 2018) of eddy covariance measurements from a 10-m tower in southeastern Arizona and a 200-m tower in western Texas were used to determine how well the Rib parameterizations for friction velocity ( u * ), sensible heat flux (H), and turbulent kinetic energy (TKE) compare against MOST-derived parameterizations of these quantities. Independent of stability, wind speed regime, and season, the Rib u * and TKE parameterizations performed better than the MOST parameterizations, whereas MOST better represented H. Observations from the 200-m tower indicated that the parameterizations' performance degraded as a function of height above ground. Overall, the Rib parameterizations revealed promising results, confirming better performance than traditional MOST relationships for kinematic (i.e., u * ) and turbulence (i.e., TKE) quantities, although caution is needed when applying the RibH parameterizations to drylands. These findings represent an important milestone for the applicability of Rib parameterizations, given the large fraction of Earth's surface covered by drylands. Significance Statement: Weather forecasting models rely upon complex mathematical relationships to predict temperature, wind, and moisture. Monin–Obukhov similarity theory (MOST) has long been used to forecast these quantities near the land surface, even though MOST's limitations are well known in the scientific community. Researchers have suggested an alternative to MOST called the bulk Richardson (Rib) approach. To allow for the Rib approach to be used in weather forecasting models, the approach needs to be tested over different land-cover and climate types. In this study, we applied the Rib approach to dry areas of the United States and found that the approach better represented turbulence variables than MOST relationships. These findings are an important step toward using Rib relationships in weather forecasting models. [ABSTRACT FROM AUTHOR]

Abstract: Atmospheric ammonia has been shown to degrade regional air quality and affect environmental health. In-situ measurements of ammonia are needed to determine how ambient concentrations vary in different ecosystems and the extent to which emission sources contribute to those levels. The objective of this study was to measure and compare ammonia concentrations in two Tennessee Valley (USA) ecosystems: a forested rural area and a metropolitan site adjacent to a main transportation route. Integrated samples of atmospheric ammonia were collected with annular denuder systems for ~4weeks during the summer of 2009 in both ecosystems. Ancillary measurements of meteorological variables, such as wind direction and precipitation, were also conducted to determine any relationships with ammonia concentration. Measurements in the two ecosystems revealed ammonia concentrations that were mostly representative of background levels. Arithmetic means were 1.57±0.68μgm−3 at the metropolitan site and 1.60±0.77μgm−3 in the forest. The geometric mean concentrations for both sites were ~1.46μgm−3. Wind direction, and to a lesser extent air temperature and precipitation, did influence measured concentrations. At the metropolitan site, ammonia concentrations were slightly higher in winds emanating from the direction of the interstate highway. Meteorological variables, such as wind direction, and physical factors, such as topography, can affect measurement of ambient ammonia concentrations, especially in ecosystems distant from strong emission sources. The 12-h integrated sampling method used in this study was unable to measure frequent changes in ambient ammonia concentrations and illustrates the need for measurements with higher temporal resolution, at least ~1–2h, in a variety of diverse ecosystems to determine the behavior of atmospheric ammonia and its environmental effects. [Copyright &y& Elsevier]

Highlights • Modeling the bi-directional NH 3 exchange at the field scale using SURFATM-NH 3. • Integrating an operational parameterization of emission potentials in the model. • Parameterizing the effect of urease inhibitor on NH 3 volatilization. • Satisfactory simulations of NH 3 fluxes by integrating the effect of urease inhibitor. • Good predictions of dynamic and order of magnitude of emission potentials by the model. Abstract Agriculture is the main source of ammonia (NH 3) emissions in the atmosphere. NH 3 is precursor to secondary fine particulate matter, which is of concern for its impacts on health and visibility. There are a limited number of field measurements of NH 3 emissions from fertilizer application in the US, and this limits our understanding of the importance of individual NH 3 source and sink processes in controlling timing and magnitude of NH 3 emissions. In this study, a new parameterization of the effect of urease inhibitor on NH 3 emissions from urea-based fertilizer was developed on the basis of experimental results found in the literature. This parameterization was combined with an existing operational parameterization of soil and stomatal emission potentials (Γ g , Γ s) and was implemented in a surface-atmosphere transfer model for NH 3 (SURFATM-NH 3) in order to evaluate the bi-directional fluxes of NH 3 at the field scale. The model was evaluated with field measurements obtained by the flux-gradient (FG) and relaxed eddy accumulation (REA) methods in a fertilized corn field in central Illinois. By integrating the effect of urease inhibitor, the timing of the highest NH 3 emission peak was successfully predicted and its magnitude was close to that measured (predicted 2106 ng m−2 s−1, measured by FG 2312 ± 582 ng m−2 s−1). Based on the model results, urease inhibitor has a considerable effect on the dynamics and order of magnitude of NH 3 fluxes. Furthermore, the model simulated the inhibiting action of N- (n -butyl) thiophosphoric (nBTPT) and suggests that it can reduce NH 3 volatilization by 32%. The model also successfully predicted environmental parameters, such as soil temperature. Finally, this new version of SURFATM-NH 3 is a valuable tool to estimate the NH 3 bi-directional fluxes at the field scale, which describes dynamic modeling of Γ s and Γ g by taking into account the effect of urease inhibitor which is commonly used in the US to improve the efficiency of urea fertilizers. [ABSTRACT FROM AUTHOR]

We present unique observations of a total solar eclipse from a small unmanned aircraft system (sUAS) platform that was operated during the 21 August 2017 North American solar eclipse. The observations were collected near Ten Mile, Tennessee, where eclipse totality lasted 2 min 38 s. A 2-m micrometeorological tripod was erected on-site to measure surface and air temperature, near-surface water vapour, incoming and outgoing shortwave and longwave radiative fluxes, and turbulent fluxes. The sUAS platform and micrometeorological tripod observations indicate significant cooling below a height of 50 m above ground level (a.g.l.) during and shortly after totality. Near-surface temperatures do not return to pre-eclipse values until about 60 min following totality. Above about 50 m a.g.l., smaller temperature changes are observed during the eclipse, as the duration of the eclipse has less influence on deeper boundary-layer turbulence. Additionally, the sensible heat flux becomes slightly negative around totality, and the turbulence kinetic energy and vertical velocity variance concurrently decrease. The evolution of the near-surface meteorological fields are investigated in more detail using a large-eddy simulation (LES) model. The simulations generally reproduce the observations well, in terms of the timing and magnitude of changes in temperature, moisture and sensible and latent heat fluxes. However, the LES model slightly underestimates the diurnal range and decrease in temperature during the eclipse while overestimating the sensible heat fluxes. [ABSTRACT FROM AUTHOR]

Highlights • Inter-comparison of relaxed eddy accumulation and flux gradient measurements. • Strong correlation between the two NH 3 flux measurement methods. • Peak NH 3 flux measured with both systems six days after fertilizer application. • Two elevated emission periods influenced by urease inhibitor and environmental conditions. Abstract Studies of NH 3 flux over agricultural ecosystems in the USA are limited by low temporal resolution (typically hours or days) and sparse spatial coverage, with no studies over corn in the Midwest USA. We report on NH 3 flux measurements over a corn canopy in Central Illinois, USA, using the relaxed eddy accumulation (REA) and flux gradient (FG) methods, providing measurements at 4 h and 0.5 h intervals, respectively. The REA and FG systems were operated for the duration of the 2014 corn-growing season. Flux-footprint analysis was used to select data from both systems, resulting in 82 concurrent measurements. Mean NH 3 flux of concurrent measurements was 205 ± 300 ng m−2 s−1 from REA and 110 ± 256 ng m−2 s−1 from FG for all concurrent samples. Results from both methods were not significantly different at a 95% confidence level for all concurrent measurements. The FG system resolved NH 3 emission peaks at 0.5 h averaging time that were otherwise un-observed with 4 h REA averaging. Two early-season peak emission periods were identified (DOY 130-132 and 140-143), where the timing and intensity of such emissions were attributed to a combination of urease inhibitor, applied as a field-management decision, and localized soil temperature and precipitation. Given the dependence of NH 3 fluxes on multiple parameters, this study further highlights the need for increased spatial coverage and high temporal resolution (e.g., <1 h) of measurements to better understand the impact of agricultural NH 3 emissions on air quality and the global nitrogen cycle. Such measurements are also needed for evaluation of models describing surface-atmosphere exchange of NH 3. [ABSTRACT FROM AUTHOR]

Airborne turbulence measurement gives a spatial distribution of air-surface fluxes that networks of fixed surface sites typically cannot capture. Much work has improved the accuracy of such measurements and the estimation of the uncertainty peculiar to streams of turbulence data measured from the air. A particularly significant challenge and opportunity is to distinguish fluxes from different surface types, especially those occurring in patches smaller than the necessary averaging length. The flux fragment method (FFM), a conditional-sampling variant of eddy covariance in the space-time domain, was presented in 2008. It was shown capable of segregating the mean flux density (CO2, H2O, sensible heat) in maize from that in soybeans over the patchwork farmlands of Illinois. This was, however, an ideal surface for the method, and the random-error estimate used a relatively rudimentary bootstrap resampling. The present paper describes an upgraded random-error estimate that accounts for the serial correlation of the time/space series and the heterogeneity of the signal. Results are presented from the Alaskan tundra. Though recognized as important, systematic error estimates are not covered in this paper. Some discussion is offered on the relation of the FFM to other approaches similarly motivated, particularly those using wavelets. Successful measurement of the variation of air-surface exchange over heterogeneous surfaces has value for developing and improving process models relating surface flux to remotely sensible quantities, such as the vegetative land-cover type and its condition. [ABSTRACT FROM AUTHOR]

The objective of this research is to quantify NH 3 flux above an intensively managed cornfield in the Midwestern United States to improve understanding of NH 3 emissions and evaluations of new and existing emission models. A relaxed eddy accumulation (REA) system was deployed above a corn canopy in central Illinois, USA (40°3′46.209″N, 88° 11′46.0212″W) from May through September 2014 (day of year 115–273) to measure NH 3 fluxes due to chemical fertilizer application. NH 3 flux was measured in four-hour periods during mornings and afternoons. Mean atmospheric NH 3 concentration during the complete measurement period was 2.6 ± 2.0 μg m −3 . Larger upward fluxes of gaseous NH 3 were measured during the first 30 days after fertilization, with variations observed throughout the field campaign. Measured NH 3 fluxes ranged from −246.0 ng m −2 s −1 during wintertime background measurements to 799.6 ng m −2 s −1 within two weeks of fertilization (where negative flux indicates deposition). Mean positive flux was 233.3 ± 203.0 ng m −2 s −1 in the morning and 260.0 ± 253.3 ng m −2 s −1 in the afternoon while mean negative flux was −45.3 ± 38.6 ng m −2 s −1 in the morning and −78.35 ± 74.9 ng m −2 s −1 in the afternoon. NH 3 volatilization during the first 21 days after fertilization accounted for 79% of total nitrogen loss during the growing season. Such measurements are critical to improve understanding of agricultural NH 3 emissions in managed agricultural ecosystems dominated by rotations of highly fertilized corn and moderately to lightly fertilized soybeans, such as the plot studied herein. These measurements are also important to improve understanding of how managed agricultural ecosystems impact air quality, and contribute to the global nitrogen cycle, and to evaluate current NH 3 emission models. [ABSTRACT FROM AUTHOR]

In Kochendorfer et al. (Boundary-Layer Meteorol 145:383-398, , hereafter K2012) the vertical wind speed $$(w)$$ measured by a non-orthogonal three-dimensional sonic anemometer was shown to be underestimated by $$\approx $$12 %. Turbulent statistics and eddy-covariance fluxes estimated using $$w$$ were also affected by this underestimate in $$w$$. Methodologies used in K2012 are clarified here in response to Mauder's comment. In addition, further analysis of the K2012 study is presented to help address questions raised in the comment. Specific responses are accompanied with examples of time series, calculated correlation coefficients, and additional explanation of the K2012 methods and assumptions. The discussion and analysis included in the comment and in this response do not affect the validity of the methods or conclusions presented in K2012. [ABSTRACT FROM AUTHOR]

Abstract: We analyzed net CO2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σ VPD. In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100g CO2 m−2 year−1. The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America. [Copyright &y& Elsevier]

Sonic anemometers are capable of measuring the wind speed in all three dimensions at high frequencies (10-50 Hz), and are relied upon to estimate eddy-covariance-based fluxes of mass and energy over a wide variety of surfaces and ecosystems. In this study, wind-velocity measurement errors from a three-dimensional sonic anemometer with a non-orthogonal transducer orientation were estimated for over 100 combinations of angle-of-attack and wind direction using a novel technique to measure the true angle-of-attack and wind speed within the turbulent atmospheric surface layer. Corrections to the vertical wind speed varied from −5 to 37% for all angles-of-attack and wind directions examined. When applied to eddy-covariance data from three NOAA flux sites, the wind-velocity corrections increased the magnitude of CO fluxes, sensible heat fluxes, and latent heat fluxes by ≈11%, with the actual magnitude of flux corrections dependent upon sonic anemometer, surface type, and scalar. A sonic anemometer that uses vertically aligned transducers to measure the vertical wind speed was also tested at four angles-of-attack, and corrections to the vertical wind speed measured using this anemometer were within ±1% of zero. Sensible heat fluxes over a forest canopy measured using this anemometer were 15% greater than sensible heat fluxes measured using a sonic anemometer with a non-orthogonal transducer orientation. These results indicate that sensors with a non-orthogonal transducer orientation, which includes the majority of the research-grade three-dimensional sonic anemometers currently in use, should be redesigned to minimize sine errors by measuring the vertical wind speed using one pair of vertically aligned transducers. [ABSTRACT FROM AUTHOR]

Abstract: The seasonal and interannual variability in surface energy exchange and evapotranspiration (E) of two temperate semi-arid grasslands in southeastern Arizona, USA, were investigated using multi-year (2004–2007) eddy covariance measurements. The study sites, a post-fire site (AG) and an unburned site (KG), received 43–87% of the annual precipitation (P) during the North American Monsoon season (July–September), with the lowest values in the drought years of 2004 and 2005. Irrespective of the differences in temperature, surface albedo, vegetation cover and soil characteristics both sites responded similarly to changes in environmental conditions. The seasonal and interannual variations in the partitioning of net radiation to turbulent fluxes were mainly controlled by P through the changes in soil water content (θ) and vegetation growth. Drastic changes in albedo, vegetation growth and energy fluxes occurred following the onset of the monsoon season in July. During the dry or cool periods of autumn, winter and spring, the sensible heat flux was the largest component of the energy balance, whereas latent heat flux dominated during the warm and wet periods of summer. The dry-foliage Priestley–Taylor coefficient (α) declined when θ in the 0–15cm soil layer dropped below 0.08m3 m−3 at AG, and 0.09m3 m−3 at KG, respectively. The July–September average of dry-foliage surface conductance, α and E, reached their lowest values in 2004 at AG and in 2005 at KG. During July–September, monthly E was linearly correlated to the monthly mean θ and the broadband normalized difference vegetation index (NDVI), whereas during May–June the relationship between NDVI and E was not significant. Annual E varied from 264 to 322mm at AG and from 196 to 284mm at KG with the lowest value during the severe drought year at the site. July–September E had positive correlation with total P, the mean NDVI and the number of growing season days during that period. Annual P explained more than 80% of the variance in annual E. [Copyright &y& Elsevier]

To accurately predict ecosystem responses induced by climate warming at local-to-global scales, models are in need of more precise knowledge of response during periods of environmental stress such as drought. In this paper, we studied environmental control of canopy-level water use efficiency (WUE) during drought at an eddy flux site in an oak-hickory forest in central Missouri, USA. Two consecutive severe droughts in the summers of 2006 and 2007 afforded coverage of a broad range of environmental conditions. We stratified data to obtain subranges that minimized cross-correlations among putative WUE-controlling factors. Our results showed that WUE was subject to control by atmospheric saturation deficit (ASD), soil water potential (SWP) and the ratio of diffuse to total photosynthetically active radiation ( If/ It). Generally, WUE was found to scale with 1/(ASD)0.5, consistent with predictions from stomatal optimization theory. In contrast, SWP and If/ It were related to WUE in a linear fashion. ASD was better correlated with WUE than either of the other two factors. It was also observed that the relationship between WUE and any single controlling factor was subject to influence of the other two. One such example was an opposite response of WUE to SWP between low and high ASD values, suggesting a breakdown of stomatal optimality under severe environmental stresses and a shift from optimal stomatal regulation to nonstomatal regulation at leaf scale. We have demonstrated that different data handling (stratified vs. nonstratified) or selection (hourly vs. daily) could lead to different conclusions on the relationship between WUE and its controls. For this reason, we recommend modelers to be cautious when applying WUE-response formulas at environmental conditions or at time scales different from those at which they are derived. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA's Air Resources Laboratory (ARL)'s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of <0.23 °C, and root mean square error (RMSE) of <0.36 °C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 °C and RMSE = 0.67 °C) than with LST(LWR) (bias > 1.1 and RMSE > 1.46 °C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were <0.47 °C, whereas nighttime AT explained >81% of the variance in LST(IRT) with a bias of 2.64 °C and RMSE of 3.6 °C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was <0.7 °C, except at the semiarid grassland (1.5 °C), whereas the absolute bias between AT and LST at the four sites were <2 °C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 °C (5 °C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season. [ABSTRACT FROM AUTHOR]