 |
| Titel |
Toward finding a universally applicable parameterization of the β factor for Relaxed Eddy Accumulation applications |
| VerfasserIn |
Teresa Vogl, Amy Hrdina, Christoph Thomas |
| Konferenz |
EGU General Assembly 2016
|
| Medientyp |
Artikel
|
| Sprache |
en
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250124370
|
| Publikation (Nr.) |
 EGU/EGU2016-3793.pdf |
|
|
|
|
|
| Zusammenfassung |
| The traditional eddy covariance (EC) technique requires the use of fast responding sensors
(≥ 10 Hz) that do not exist for many chemical species found in the atmosphere. In this case,
the Relaxed Eddy Accumulation (REA) method offers a means to calculate fluxes of trace
gases and other scalar quantities (Businger and Oncley, 1990) and was originally derived
from the eddy accumulation method (EA) first proposed by Desjardins (1972). While REA
lessens the requirements for sensors and sampling and thus offers practical appeal, it
introduces a dependence of the computed flux from a proportionality factor β. The accuracy
of the REA fluxes hinges upon the correct determination of β, which was found to vary
between 0.40 and 0.63 (Milne et al., 1999, Ammann and Meixner, 2002, Ruppert et al.,
2006). However, formulating a universally valid parameterization for β instead of
empirical evaluation has remained a conundrum and has been a main limitation for
REA.
In this study we take a fresh look at the dependencies and mathematical models of β by
analyzing eddy covariance (EC) data and REA simulations for two field experiments in
drastically contrasting environments: an exclusively physically driven environment in the Dry
Valleys of Antarctica, and a biologically active system in a grassland in Germany. The main
objective is to work toward a model parameterization for β that can be applied over wide
range of surface conditions and forcings without the need for empirical evaluation, which is
not possible for most REA applications.
Our study discusses two different models to define β: (i) based upon scalar-scalar similarity,
in which a different scalar is measured with fast-response sensors as a proxy for the scalar of
interest, here referred to as β0; and (ii) computed solely from the vertical wind statistics,
assuming a linear relationship between the scalar of interest and the vertical wind speed,
referred to as βw. Results are presented for the carbon-dioxide, latent and sensible heat fluxes
across the contrasting environments.
First, the choice of an appropriate scalar to calculate β0 is discussed considering the sources
and sinks of each scalar with an emphasis on the carbon dioxide flux, which shows strongly
dissimilar dynamics between the Antarctic ecosystem and the grassland. Secondly, the impact
of atmospheric stability on both β models is investigated. In a next step, we attempt to find a
physically meaningful explanation for the overestimation of the REA scalar fluxes compared
to those from EC for using βw. We do so by analyzing the probability density function
(pdf) and its statistical moments for the vertical wind speed. We found its pdf to be
non-Gaussian for the majority of cases, and detected a close to linear relationship
of its kurtosis with βw. Finally, in an attempt to provide practical guidance for
field measurements, we integrate our findings and propose an enhanced model
parameterization, and evaluate the differences between our new model and a constant
β.
Ammann, C. and Meixner, F.X. (2002) Stability dependence of the relaxed eddy
accumulation coefficient for various scalar quantities. J. Geophys. Res. 107. ACL7.1–ACL7.9
doi:10.1029/2001JD000649
Businger, J.A., Oncley, S.P. (1990) Flux measurement with conditional sampling. J.
Atmos. Ocean. Tech. 7:349–352.
Desjardins, R. L. (1972) A study of carbon-dioxide and sensible heat fluxes
using the eddy correlation technique, Ph.D. dissertation, Cornell University, 189
pp.
Desjardins, R.L. (1977) Description and evaluation of sensible heat flux detector.
Boundary-Layer Meteorol. 11:147–154.
Katul, G., Finkelstein, P. L., Clarke, J. F., and Ellestad, T. G. (1996) An Investigation of
the Conditional Sampling Methods Used to Estimate Fluxes of Active, Reactive and Passive
Scalars. J. Appl. Meteorol. 35: 1835–1845.
Milne, R., Beverland, I. J., Hargreaves, K., and Moncrieff, J. B. (1999) Variation of the
beta coefficient in the relaxed eddy accumulation method. Boundary-Layer Meteorol. 93:
211–225.
Ruppert, J. ATEM software for atmospheric turbulent exchange measurements using eddy
covariance and relaxed eddy accumulation systems: Bayreuth whole-air REA system setup,
Universität Bayreuth, Abt. Mikrometeorologie, Print, ISSN 1614-8916, Arbeitsergebnisse 28,
29 S, 2005
Ruppert, J., Thomas, C., and Foken, T. (2006) scalar similarity for relaxed eddy
accumulation methods. Boundary-Layer Meteorol. 120: 39–63. |
|
|
|
|
|
|