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Gabriel G. Katul, Chris D. Geron, Cheng-I. Hsieh, Brani Vidakovic, and Alex B. Guenther

Abstract

Turbulent velocity, temperature, water vapor concentration, and other scalars were measured at the canopy–atmosphere interface of a 13–14-m-tall uniform pine forest and a 33-m-tall nonuniform hardwood forest. These measurements were used to investigate whether the mixing layer (ML) analogy of predicts eddy sizes and flow characteristics responsible for much of the turbulent stresses and vertical scalar fluxes. For this purpose, wavelet spectra and cospectra were derived and analyzed. It was found that the ML analogy predicts well vertical velocity variances and integral timescales. However, at low wavenumbers, inactive eddy motion signatures were present in horizontal velocity wavelet spectra, suggesting that ML may not be suitable for scaling horizontal velocity perturbations. Momentum and scalar wavelet cospectra of turbulent stresses and scalar fluxes demonstrated that active eddy motion, which was shown by to be the main energy contributor to vertical velocity (w) spectral energy (E w), is also the main scalar flux–transporting eddy motion. Predictions using ML of the peak E w frequency are in excellent agreement with measured wavelet cospectral peaks of vertical fluxes (Kh = 1.5, where K is wavenumber and h is canopy height). Using Lorentz wavelet thresholding of vertical velocity time series, wavelet coefficients associated with active turbulence were identified. It was demonstrated that detection frequency of organized structures, as predicted from Lorentz wavelet filtering, relate to the arrival frequency 〈U〉/h and integral timescale, where 〈U〉 is the mean horizontal velocity at height z = h. The newly proposed wavelet thresholding approach, which relies on a “global” wavelet threshold formulation for the energy in w, provides simultaneous energy–covariance-preserving characterization of “active” turbulence at the canopy–atmosphere interface.

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Craig A. Stroud, Athanasios Nenes, Jose L. Jimenez, Peter F. DeCarlo, J. Alex Huffman, Roelof Bruintjes, Eiko Nemitz, Alice E. Delia, Darin W. Toohey, Alex B. Guenther, and Sreela Nandi

Abstract

Measurements of aerosol size distribution, chemical composition, and cloud condensation nuclei (CCN) concentration were performed during the Chemical Emission, Loss, Transformation, and Interactions with Canopies (CELTIC) field program at Duke Forest in North Carolina. A kinetic model of the cloud activation of ambient aerosol in the chamber of the CCN instrument was used to perform an aerosol–CCN closure study. This study advances prior investigations by employing a novel fitting algorithm that was used to integrate scanning mobility particle sizer (SMPS) measurements of aerosol number size distribution and aerosol mass spectrometer (AMS) measurements of the mass size distribution for sulfate, nitrate, ammonium, and organics into a single, coherent description of the ambient aerosol in the size range critical to aerosol activation (around 100-nm diameter). Three lognormal aerosol size modes, each with a unique internally mixed composition, were used as input into the kinetic model. For the two smaller size modes, which control CCN number concentration, organic aerosol mass fractions for the defined cases were between 58% and 77%. This study is also unique in that the water vapor accommodation coefficient was estimated based on comparing the initial timing for CCN activation in the instrument chamber with the activation predicted by the kinetic model. The kinetic model overestimated measured CCN concentrations, especially under polluted conditions. Prior studies have attributed a positive model bias to an incomplete understanding of the aerosol composition, especially the role of organics in the activation process. This study shows that including measured organic mass fractions with an assumed organic aerosol speciation profile (pinic acid, fulvic acid, and levoglucosan) and an assumed organic aerosol solubility of 0.02 kg kg−1 still resulted in a significant model positive bias for polluted case study periods. The slope and y intercept for the CCN predicted versus CCN observed regression was found to be 1.9 and −180 cm−3, respectively. The overprediction generally does not exceed uncertainty limits but is indicative that a bias exists in the measurements or application of model. From this study, uncertainties in the particle number and mass size distributions as the cause for the model bias can be ruled out. The authors are also confident that the model is including the effects of growth kinetics on predicted activated number. However, one cannot rule out uncertainties associated with poorly characterized CCN measurement biases, uncertainties in assumed organic solubility, and uncertainties in aerosol mixing state. Sensitivity simulations suggest that assuming either an insoluble organic fraction or external aerosol mixing were both sufficient to reconcile the model bias.

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Philip A. Feiner, William H. Brune, David O. Miller, Li Zhang, Ronald C. Cohen, Paul S. Romer, Allen H. Goldstein, Frank N. Keutsch, Kate M. Skog, Paul O. Wennberg, Tran B. Nguyen, Alex P. Teng, Joost DeGouw, Abigail Koss, Robert J. Wild, Steven S. Brown, Alex Guenther, Eric Edgerton, Karsten Baumann, and Juliane L. Fry

Abstract

The chemical species emitted by forests create complex atmospheric oxidation chemistry and influence global atmospheric oxidation capacity and climate. The Southern Oxidant and Aerosol Study (SOAS) provided an opportunity to test the oxidation chemistry in a forest where isoprene is the dominant biogenic volatile organic compound. Hydroxyl (OH) and hydroperoxyl (HO2) radicals were two of the hundreds of atmospheric chemical species measured, as was OH reactivity (the inverse of the OH lifetime). OH was measured by laser-induced fluorescence (LIF) and by taking the difference in signals without and with an OH scavenger that was added just outside the instrument’s pinhole inlet. To test whether the chemistry at SOAS can be simulated by current model mechanisms, OH and HO2 were evaluated with a box model using two chemical mechanisms: Master Chemical Mechanism, version 3.2 (MCMv3.2), augmented with explicit isoprene chemistry and MCMv3.3.1. Measured and modeled OH peak at about 106 cm−3 and agree well within combined uncertainties. Measured and modeled HO2 peak at about 27 pptv and also agree well within combined uncertainties. Median OH reactivity cycled between about 11 s−1 at dawn and about 26 s−1 during midafternoon. A good test of the oxidation chemistry is the balance between OH production and loss rates using measurements; this balance was observed to within uncertainties. These SOAS results provide strong evidence that the current isoprene mechanisms are consistent with measured OH and HO2 and, thus, capture significant aspects of the atmospheric oxidation chemistry in this isoprene-rich forest.

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Edward G. Patton, Thomas W. Horst, Peter P. Sullivan, Donald H. Lenschow, Steven P. Oncley, William O. J. Brown, Sean P. Burns, Alex B. Guenther, Andreas Held, Thomas Karl, Shane D. Mayor, Luciana V. Rizzo, Scott M. Spuler, Jielun Sun, Andrew A. Turnipseed, Eugene J. Allwine, Steven L. Edburg, Brian K. Lamb, Roni Avissar, Ronald J. Calhoun, Jan Kleissl, William J. Massman, Kyaw Tha Paw U, and Jeffrey C. Weil

The Canopy Horizontal Array Turbulence Study (CHATS) took place in spring 2007 and is the third in the series of Horizontal Array Turbulence Study (HATS) experiments. The HATS experiments have been instrumental in testing and developing subfilterscale (SFS) models for large-eddy simulation (LES) of planetary boundary layer (PBL) turbulence. The CHATS campaign took place in a deciduous walnut orchard near Dixon, California, and was designed to examine the impacts of vegetation on SFS turbulence. Measurements were collected both prior to and following leafout to capture the impact of leaves on the turbulence, stratification, and scalar source/sink distribution. CHATS utilized crosswind arrays of fast-response instrumentation to investigate the impact of the canopy-imposed distribution of momentum extraction and scalar sources on SFS transport of momentum, energy, and three scalars. To directly test and link with PBL parameterizations of canopy-modified turbulent exchange, CHATS also included a 30-m profile tower instrumented with turbulence instrumentation, fast and slow chemical sensors, aerosol samplers, and radiation instrumentation. A highresolution scanning backscatter lidar characterized the turbulence structure above and within the canopy; a scanning Doppler lidar, mini sodar/radio acoustic sounding system (RASS), and a new helicopter-observing platform provided details of the PBL-scale flow. Ultimately, the CHATS dataset will lead to improved parameterizations of energy and scalar transport to and from vegetation, which are a critical component of global and regional land, atmosphere, and chemical models. This manuscript presents an overview of the experiment, documents the regime sampled, and highlights some preliminary key findings.

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Annmarie G. Carlton, Joost de Gouw, Jose L. Jimenez, Jesse L. Ambrose, Alexis R. Attwood, Steven Brown, Kirk R. Baker, Charles Brock, Ronald C. Cohen, Sylvia Edgerton, Caroline M. Farkas, Delphine Farmer, Allen H. Goldstein, Lynne Gratz, Alex Guenther, Sherri Hunt, Lyatt Jaeglé, Daniel A. Jaffe, John Mak, Crystal McClure, Athanasios Nenes, Thien Khoi Nguyen, Jeffrey R. Pierce, Suzane de Sa, Noelle E. Selin, Viral Shah, Stephanie Shaw, Paul B. Shepson, Shaojie Song, Jochen Stutz, Jason D. Surratt, Barbara J. Turpin, Carsten Warneke, Rebecca A. Washenfelder, Paul O. Wennberg, and Xianling Zhou

Abstract

The Southeast Atmosphere Studies (SAS), which included the Southern Oxidant and Aerosol Study (SOAS); the Southeast Nexus (SENEX) study; and the Nitrogen, Oxidants, Mercury and Aerosols: Distributions, Sources and Sinks (NOMADSS) study, was deployed in the field from 1 June to 15 July 2013 in the central and eastern United States, and it overlapped with and was complemented by the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. SAS investigated atmospheric chemistry and the associated air quality and climate-relevant particle properties. Coordinated measurements from six ground sites, four aircraft, tall towers, balloon-borne sondes, existing surface networks, and satellites provide in situ and remotely sensed data on trace-gas composition, aerosol physicochemical properties, and local and synoptic meteorology. Selected SAS findings indicate 1) dramatically reduced NOx concentrations have altered ozone production regimes; 2) indicators of “biogenic” secondary organic aerosol (SOA), once considered part of the natural background, were positively correlated with one or more indicators of anthropogenic pollution; and 3) liquid water dramatically impacted particle scattering while biogenic SOA did not. SAS findings suggest that atmosphere–biosphere interactions modulate ambient pollutant concentrations through complex mechanisms and feedbacks not yet adequately captured in atmospheric models. The SAS dataset, now publicly available, is a powerful constraint to develop predictive capability that enhances model representation of the response and subsequent impacts of changes in atmospheric composition to changes in emissions, chemistry, and meteorology.

Open access