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Young-San Park and Kyaw Tha Paw U

Abstract

Local advection of scalar quantities such as heat, moisture, or carbon dioxide occurs not only above inhomogeneous surfaces but also within roughness elements on these surfaces. A two-dimensional advection–diffusion equation is applied to examine the fractionation of scalar exchange into horizontal advection within a canopy and vertical turbulent eddy transport at the canopy top. Simulations were executed with combinations of various wind speeds, eddy diffusivities, canopy heights, and source strengths. The results show that the vertical turbulent fluxes at the canopy top increase along the fetch and approach a limit at some downstream distance. The horizontal advection in the canopy is maximum at the edge of canopy and decreases exponentially along the fetch. All cases have the same features, except the absolute quantities depend on the environmental conditions. When the horizontal axis is normalized by using the dimensionless variable xK/uh 2, horizontal diffusion is negligible, and the upwind concentration profile is constant, the curves of horizontal advection and vertical flux collapse into single, unique lines, respectively (x is the horizontal distance from the canopy edge, K is the eddy diffusivity, u is the wind speed, and h is the canopy height). The ratios of horizontal advection to the vertical turbulent flux also collapse into one universal curve when plotted against the dimensionless variable xK/uh 2, irrespective of source strength. The ratio R shows a power-law relation to the dimensionless distance [R = a(xK/uh 2)b, where a and b are constant].

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R. David Pyles, Bryan C. Weare, Kyaw Tha Paw U, and William Gustafson

Abstract

The University of California, Davis, Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) is coupled to the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) as a land surface scheme. Simulations for July 1998 over western North America show that this coupling, the first between a mesoscale model and a land surface model of this complexity, is successful. Comparisons among model output, National Centers for Environmental Prediction–NCAR reanalysis fields, and station data show that MM5–ACASA generally reproduces near-surface temperature in a realistic fashion, but with a stronger diurnal cycle than observations suggest. A control run using the existing Louis/European Centre for Medium-Range Weather Forecasts land surface formulation produces unrealistically low temperatures associated with high latent heating and precipitation amounts over much of the model domain. Simulations of heat and moisture fluxes using the Biosphere–Atmosphere Transfer Scheme (BATS) are generally comparable to ACASA, but near-surface air temperatures reveal excessively warm conditions. Low specific-humidity values over land in both MM5–ACASA and MM5–BATS simulations and low oceanic values in all three simulations suggest a possible dry bias in MM5. Comparison statistics between modeled near-surface climatological behavior and associated fluxes at three sites show that MM5–ACASA, out of the three simulations, agrees most with observations. Sensitivity tests show that MM5 is generally more sensitive to the choice of surface scheme than it is to soil moisture initialization. Comparisons of mean carbon dioxide fluxes reveal that ACASA can be a useful tool in examining the terrestrial carbon cycle.

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Thomas Foken, Marc Aubinet, John J. Finnigan, Monique Y. Leclerc, Mattthias Mauder, and Kyaw Tha Paw U

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Wen Li Zhao, Guo Yu Qiu, Yu Jiu Xiong, Kyaw Tha Paw U, Pierre Gentine, and Bao Yu Chen

Abstract

Quantifying the uncertainties caused by resistance parameterizations is fundamental for understanding, improving, and developing terrestrial evapotranspiration (ET) models. Using high-density eddy covariance (EC) tower observations in a heterogeneous oasis in northwest China, this study evaluates the impacts of resistances on the estimation of latent heat flux (LE), the energy equivalent of ET, by comparing resistance parameterizations with different complexities under one- and two-source Penman–Monteith (PM) equations. The results showed that the mean absolute percent error (MAPE) for the LE estimates from the one- and two-source PM equations varied from 32% to 53%, and the uncertainties were caused mainly by the resistance parameterizations. Calibrating the parameters required in the resistance estimations could improve the performance of the PM equations; specifically, the MAPEs for the one-source PM equations were approximately 16%, whereas they were 38% for the two-source PM equations, emphasizing that multiple resistances result in increased uncertainties. The following conclusions were reached: 1) the empirical and biophysical parameters required in resistance estimations were responsible for the uncertainty; 2) increasingly complex resistance parameterizations resulted in greater uncertainties in LE estimates; and 3) models without resistance parameterizations exhibited reduced uncertainties in LE estimates.

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Rommel C. Zulueta, Walter C. Oechel, Joseph G. Verfaillie, Steven J. Hastings, Beniamino Gioli, William T. Lawrence, and Kyaw Tha Paw U

Abstract

Natural ecosystems are rarely structurally simple or functionally homogeneous. This is true for the complex coastal region of Magdalena Bay, Baja California Sur, Mexico, where the spatial variability in ecosystem fluxes from the Pacific coastal ocean, eutrophic lagoon, mangroves, and desert were studied. The Sky Arrow 650TCN environmental research aircraft proved to be an effective tool in characterizing land–atmosphere fluxes of energy, CO2, and water vapor across a heterogeneous landscape at the scale of 1 km. The aircraft was capable of discriminating fluxes from all ecosystem types, as well as between nearshore and coastal areas a few kilometers distant. Aircraft-derived average midday CO2 fluxes from the desert showed a slight uptake of −1.32 μmol CO2 m−2 s−1, the coastal ocean also showed an uptake of −3.48 μmol CO2 m−2 s−1, and the lagoon mangroves showed the highest uptake of −8.11 μmol CO2 m−2 s−1. Additional simultaneous measurements of the normalized difference vegetation index (NDVI) allowed simple linear modeling of CO2 flux as a function of NDVI for the mangroves of the Magdalena Bay region. Aircraft approaches can, therefore, be instrumental in determining regional CO2 fluxes and can be pivotal in calculating and verifying ecosystem carbon sequestration regionally when coupled with satellite-derived products and ecosystem models.

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Jason Beringer, Jorg Hacker, Lindsay B. Hutley, Ray Leuning, Stefan K. Arndt, Reza Amiri, Lutz Bannehr, Lucas A. Cernusak, Samantha Grover, Carol Hensley, Darren Hocking, Peter Isaac, Hizbullah Jamali, Kasturi Kanniah, Stephen Livesley, Bruno Neininger, Kyaw Tha Paw U, William Sea, Dennis Straten, Nigel Tapper, Richard Weinmann, Stephen Wood, and Steve Zegelin

Savannas are highly significant global ecosystems that consist of a mix of trees and grasses and that are highly spatially varied in their physical structure, species composition, and physiological function (i.e., leaf area and function, stem density, albedo, and roughness). Variability in ecosystem characteristics alters biophysical and biogeochemical processes that can affect regional to global circulation patterns, which are not well characterized by land surface models. We initiated a multidisciplinary field campaign called Savanna Patterns of Energy and Carbon Integrated across the Landscape (SPECIAL) during the dry season in Australian savannas to understand the spatial patterns and processes of land surface–atmosphere exchanges (radiation, heat, moisture, CO2, and other trace gasses). We utilized a combination of multiscale measurements including fixed flux towers, aircraft-based flux transects, aircraft boundary layer budgets, and satellite remote sensing to quantify the spatial variability across a continental-scale rainfall gradient (transect). We found that the structure of vegetation changed along the transect in response to declining average rainfall. Tree basal area decreased from 9.6 m2 ha−1 in the coastal woodland savanna (annual rainfall 1,714 mm yr−1) to 0 m2 ha−1 at the grassland site (annual rainfall 535 mm yr−1), with dry-season green leaf area index (LAI) ranging from 1.04 to 0, respectively. Leaf-level measurements showed that photosynthetic properties were similar along the transect. Flux tower measurements showed that latent heat fluxes (LEs) decreased from north to south with resultant changes in the Bowen ratios (H/LE) from a minimum of 1.7 to a maximum of 15.8, respectively. Gross primary productivity, net carbon dioxide exchange, and LE showed similar declines along the transect and were well correlated with canopy LAI, and fluxes were more closely coupled to structure than floristic change.

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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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