Sampling Error In Eddy Correlation Flux Measurements
Maseyk, M.S. Dias, Estimating the Random Error in Eddy-Covariance Based Fluxes and Other Turbulence Statistics: The Filtering Method, Boundary-Layer Meteorology, 2012, 144, 1, 113CrossRef18J.G. Griessbaum, G. Request Permissions Publication HistoryIssue online: 1 February 2001Version of record online: 1 February 2001Manuscript Accepted: 7 November 2000Manuscript Received: 1 June 2000Index terms:Biosphere/atmosphere interactionsGlobal Change: Biogeochemical processesRelated content Articles related to Check This Out
Springer, New York, p 526Google ScholarCopyright information© Springer Science+Business Media B.V. 2012Authors and AffiliationsScott T. Salesky1Marcelo Chamecki1Email authorNelson L. Dias21.Department of MeteorologyThe Pennsylvania State UniversityUniversity ParkUSA2.Laboratory for Environmental Monitoring and Modeling AnalysisFederal University of ParanáCuritibaBrazil About this article J Atmos Ocean Technol 14(3): 512–526CrossRefGoogle ScholarWesely M, Cook D, Williams R (1981) Field measurement of small ozone fluxes to snow, wet bare soil, and lake water. These methods are compared to a more statistically rigorous method which calculates the variance of a covariance when the two variables in the covariance are auto-and cross-correlated. The system returned: (22) Invalid argument The remote host or network may be down. http://onlinelibrary.wiley.com/doi/10.1029/2000JD900731/abstract
CowanPeter E. The closed-path EC system overestimated the CO 2 by approximately 5% and underestimated the latent heat fluxes by about 10% when compared with the open-path system measurements. Coutts, Gregoire Pigeon, Nicole P. Generated Thu, 27 Oct 2016 07:41:07 GMT by s_wx1202 (squid/3.5.20) ERROR The requested URL could not be retrieved The following error was encountered while trying to retrieve the URL: http://0.0.0.10/ Connection
Several methods to estimate sampling, or random error in flux measurements, have been published. J Atmos Ocean Technol 15(2): 416–429CrossRefGoogle ScholarMann J, Lenschow D (1994) Errors in airborne flux measurements. Fratini, J.-Y. Alfieri, P.D.
Geophys. A closed-path EC system was used to measure CH 4 , CO 2 , and H 2 O fluxes. Wendel, Fast chemiluminescent method for measurement of ambient ozone, Anal. To our knowledge, this study is unique given the long-term, continuous dataset of urban CH4 fluxes analysed.
Moore, Michael E. Boundary-Layer Meteorol (2012) 144: 113. Moravek, J.-C. Boundary-Layer Meteorol 70(3): 217–246CrossRefGoogle ScholarHollinger D, Richardson A (2005) Uncertainty in eddy covariance measurements and its application to physiological models.
H., J. https://www.researchgate.net/publication/279929190_Sampling_error_in_eddy_correlation_flux_measurements Single-root scale Next article in issue: Modeling methane fluxes in wetlands with gas-transporting plants: 1. Finkelstein2nd P.F. J Atmos Ocean Technol 11(3): 661–673CrossRefGoogle ScholarLeonard A (1974) Energy cascade in large-eddy simulations of turbulent fluid flows.
Res., 105, 15365–15377, 2000.Wiley Online Library | CAS | Web of Science Times Cited: 56Fuller, W. http://onlivetalk.com/sampling-error/sampling-bias-and-sampling-error.php Blanken, How representative is a point? Jordan, Larry Mahrt, Dean Vickers, Estimating the Bowen ratio over the open and ice-covered ocean, Journal of Geophysical Research: Oceans, 2013, 118, 9, 4334Wiley Online Library12Olaf Menzer, Antje Maria Moffat, Wendy J Clim Appl Meteorol 25: 1100–1124Google ScholarDias N, Chamecki M, Kan A, Okawa C (2004) A study of spectra, structure and correlation functions and their implications for the stationarity of surface-layer
There were not large or significant differences between random errors for fluxes measured over crops versus those measured over forests. Boundary-Layer Meteorol 83(1): 117–137CrossRefGoogle ScholarJohansson C, Smedman A, Högström U, Brasseur J, Khanna S (2001) Critical test of the validity of Monin–Obukhov similarity during convective conditions. There were not large or significant differences between random errors for fluxes measured over crops versus those measured over forests. this contact form Marr, Tim O.
Several methods to estimate sampling, or random error in flux measurements, have been published. Chang, O. Please try the request again.
J Geophys Res 86(C8): 7291–7297CrossRefGoogle ScholarLenschow D, Pearson R Jr, Stankov B (1982) Measurements of ozone vertical flux to ocean and forest.
Trebs, Comparison of ozone deposition measured with the dynamic chamber and the eddy covariance method, Agricultural and Forest Meteorology, 2015, 206, 97CrossRef2Torbern Tagesson, Rasmus Fensholt, Ford Cropley, Idrissa Guiro, Stéphanie Horion, C., On surface layer turbulence, Workshop on MicrometeorologyD. Compared to previously published methods, error estimates from this technique were 20 to 25% higher because of the incorporation of additional terms in the estimate of the variance. Ellestad, P.
Fratini, J.-Y. Stella, A. M. navigate here Finkelstein, J.
van Lipzig, Simulating the surface energy balance over two contrasting urban environments using the Community Land Model Urban, International Journal of Climatology, 2013, 33, 15, 3182Wiley Online Library14Keisuke ONO, Derivations and A. Bradley, An alternative analysis of the flux-gradient relationships in the 1976 ITCE, Boundary Layer Meteorol., 22, 3–19, 1982.CrossRef | Web of Science Times Cited: 130 | ADSFinkelstein, P. Piersol, Measurement and Analysis of Random Data, John Wiley, New York, 1966.Businger, J.
F. L. O. Note NCAR/TN-389+STR, 53Natl.
Differing provisions from the publisher's actual policy or licence agreement may be applicable.This publication is from a journal that may support self archiving.Learn more © 2008-2016 researchgate.net. To calculate cumulative fluxes, observed fluxes were used with their associated uncertainties (Finkelstein and Sims, 2001) when available; otherwise the GAM predictions were used. "[Show abstract] [Hide abstract] ABSTRACT: Intensively managed P., P. Ammann, A.
Please try the request again. Shahadat Hossen, Masayoshi Mano, Akira Miyata, Md. Publication:Journal of Geophysical Research: Atmospheres, Volume 106, Issue D4, pp. 3503-3509 (JGR Homepage) Publication Date:02/2001 Origin:AGU; WILEY Keywords:Atmospheric Composition and Structure: Biosphere/atmosphere interactions, Global Change: Biogeochemical processes, Mathematical Geophysics: Modeling Abstract