The eddy covariance technique ascertains the exchange rate of CO2 across the interface between the atmosphere and a plant canopy by measuring the covariance between fluctuations in vertical wind velocity and CO2 mixing ratio. Two decades ago, the method was employed to study CO2 exchange of agricultural crops under ideal conditions during short field campaigns. During the past decade the eddy covariance method has emerged as an important tool for evaluating fluxes of carbon dioxide between terrestrial ecosystems and the atmosphere over the course of a year, and more. At present, the method is being applied in a nearly continuous mode to study carbon dioxide and water vapor exchange at over a hundred and eighty field sites, worldwide. The objective of this review is to assess the eddy covariance method as it is being applied by the global change community on increasingly longer time scales and over less than ideal surfaces.

The eddy covariance method is most accurate when the atmospheric conditions (wind, temperature, humidity, CO2) are steady, the underlying vegetation is homogeneous and it is situated on flat terrain for an extended distance upwind. When the eddy covariance method is applied over natural and complex landscapes or during atmospheric conditions that vary with time, the quantification of CO2 exchange between the biosphere and atmosphere must include measurements of atmospheric storage, flux divergence and advection.

Averaging CO2 flux measurements over long periods (days to year) reduces random sampling error to relatively small values. Unfortunately, data gaps are inevitable when constructing long data records. Data gaps are generally filled with values produced from statistical and empirical models to produce daily and annual sums of CO2 exchange. Filling data gaps with empirical estimates do not introduce significant bias errors because the empirical algorithms are derived from large statistical populations. On the other hand, flux measurement errors can be biased at night when winds are light and intermittent. Nighttime bias errors tend to produce an underestimate in the measurement of ecosystem respiration.

Despite the sources of errors associated with long-term eddy flux measurements, many investigators are producing defensible estimates of annual carbon exchange. When measurements come from nearly ideal sites the error bound on the net annual exchange of CO2 is less than ±50 g C m−2 yr−1. Additional confidence in long-term measurements is growing because investigators are producing values of net ecosystem productivity that are converging with independent values produced by measuring changes in biomass and soil carbon, as long as the biomass inventory studies are conducted over multiple years.

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Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future

In 1996, version 2.5 of the Coupled Ocean–Atmosphere Response Experiment (COARE) bulk algorithm was published, and it has become one of the most frequently used algorithms in the air–sea interaction community. This paper describes steps taken to improve the algorithm in several ways. The number of iterations to solve for stability has been shortened from 20 to 3, and adjustments have been made to the basic profile stability functions. The scalar transfer coefficients have been redefined in terms of the mixing ratio, which is the fundamentally conserved quantity, rather than the measured water vapor mass concentration. Both the velocity and scalar roughness lengths have been changed. For the velocity roughness, the original fixed value of the Charnock parameter has been replaced by one that increases with wind speeds of between 10 and 18 m s−1. The scalar roughness length parameterization has been simplified to fit both an early set of NOAA/Environmental Technology Laboratory (ETL) experiments and...

/pdf/bulk-parameterization-of-air-sea-fluxes-updates-and-414u3mowml.pdf

Bulk Parameterization of Air–Sea Fluxes: Updates and Verification for the COARE Algorithm

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1153&context=natrespapers

Energy balance closure at FLUXNET sites

This paper describes the various physical processes relating near-surface atmospheric and oceanographic bulk variables ; their relationship to the surface fluxes of momentum, sensible heat, and latent heat ; and their expression in a bulk flux algorithm. The algorithm follows the standard Monin-Obukhov similarity approach for near-surface meteorological measurements but includes separate models for the ocean's cool skin and the diurnal warm layer, which are used to derive true skin temperature from the bulk temperature measured at some depth near the surface. The basic structure is an outgrowth of the Liu-Katsaros-Businger [Liu et al., 1979] method, with modifications to include a different specification of the roughness/stress relationship, a gustiness velocity to account for the additional flux induced by boundary layer scale variability, and profile functions obeying the convective limit. Additionally, we have considered the contributions of the sensible heat carried by precipitation and the requirement that the net dry mass flux be zero (the so-called Webb correction [Webb et al., 1980]). The algorithm has been tuned to fit measurements made on the R/V Moana Wave in the three different cruise legs made during the Coupled Ocean-Atmosphere Response Experiment. These measurements yielded 1622 fifty-min averages of fluxes and bulk variables in the wind speed range from 0.5 to 10 m s -1 . The analysis gives statistically reliable values for the Charnock [1955] constant (a = 0.011) and the gustiness parameter (β = 1.25). An overall mean value for the latent heat flux, neutral bulk-transfer coefficient was 1.11 x 10 -3 , declining slightly with increasing wind speed. Mean values for the sensible and latent heat fluxes were 9.1 and 103.5 W m -2 ; mean values for the Webb and rain heat fluxes were 2.5 and 4.5 W m -2 . Accounting for all factors, the net surface heat transfer to the ocean was 17.9 ± 10 W m -2 .

/pdf/bulk-parameterization-of-air-sea-fluxes-for-tropical-ocean-1mceyr1e2a.pdf

Bulk parameterization of air‐sea fluxes for Tropical Ocean‐Global Atmosphere Coupled‐Ocean Atmosphere Response Experiment

Publisher Summary The chapter has described the measurement system and the procedure followed for the computation of the fluxes and the procedure of flux summation, including data gap filling strategy, night flux corrections and error estimation. It begins with the introduction of estimates of the annual net carbon and water exchange of forests using the EUROFLUX methodology. The chapter then provides us with the theory and moves on to discuss the eddy covariance system and its sonic anemometer, temperature fluctuation measurements, infrared gas analyser, air transport system, and tower instrumentation. Additional measurements are also given in the chapter. Data acquisition and its computation and correction is discussed next in the chapter by giving its general procedure, half-hourly means (co-)variances and uncorrected fluxes, intercomparison of software, and correction for frequency response losses. The chapter has also discussed about quality control and four criteria are investigated here for the same. Spatial representativeness of measured fluxes and summation procedure are reviewed. The chapter then moves on to the discussion of data gap filling through interpolation and parameterization and neural networks. Corrections to night-time data and error estimation are also explored in the chapter. Finally, the chapter closes with conclusions.

Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology

When the atmospheric turbulent flux of a minor constituent such as CO2 (or of water vapour as a special case) is measured by either the eddy covariance or the mean gradient technique, account may need to be taken of variations of the constituent's density due to the presence of a flux of heat and/or water vapour. In this paper the basic relationships are discussed in the context of vertical transfer in the lower atmosphere, and the required corrections to the measured flux are derived.

If the measurement involves sensing of the fluctuations or mean gradient of the constituent's mixing ratio relative to the dry air component, then no correction is required; while with sensing of the constituent's specific mass content relative to the total moist air, a correction arising from the water vapour flux only is required. Correspondingly, if in mean gradient measurements the constituent's density is measured in air from different heights which has been pre-dried and brought to a common temperature, then again no correction is required; while if the original (moist) air itself is brought to a common temperature, then only a correction arising from the water vapour flux is required.

If the constituent's density fluctuations or mean gradients are measured directly in the air in situ, then corrections arising from both heat and water vapour fluxes are required.

These corrections will often be very important. That due to the heat flux is about five times as great as that due to an equal latent heat (water vapour) flux. In CO2 flux measurements the magnitude of the correction will commonly exceed that of the flux itself. The correction to measurements of water vapour flux will often be only a few per cent but will sometimes exceed 10 per cent.

Correction of flux measurements for density effects due to heat and water vapour transfer

By analyses of profile data for the superadiabatic surface layer from the Johns Hopkins group (U.S.A.) in 1953 and from Swinbank and co-workers (Australia) in 1962–64, mean profile forms which give a close representation of the data are adopted.

For the profiles of U, θ, and r the gradients initially pass from z−1 dependence through a smooth transition at z/|L| ⋍ 0.03 towards z−4/3 dependence. The corresponding ‘1m4/3’ form adopted is broadly similar to the O'KEYPS, Businger-Dyer, and BWIB (Kansas) U profiles, but its change of gradient with increasing instability is a little more rapid than for these three. This form is maintained, with KH/KM remaining constant, up to z/|L| ⋍ 0.27.

For larger z/|L|, KH/KM increases, |∂θ/|z and |∂r/∂z| falling relatively more rapidly and ∂U/∂ relaively less rapidly. Intermittent near-vanishing of |∂θ/∂z| is observed over intervals of a few minutes. Approaching z/|L| values around 1 (the data limit) the profiles, while not tightly defined by the data, are suitably represented by a continuing z−4/3 dependence with KH /Km nearly twice its near-neutral value.

The analyses and results are independent of the von Karman constants kukθ and kr (a possible dependence on the ratio kθ/ku in relation to the stability parameter being avoided by use of a modified from of Obukhov's lenght). The do not provide values of these three constants and the adopted forms remain unaffected by any future assignment of these values.

E. K. Webb

Papers

Correction of flux measurements for density effects due to heat and water vapour transfer

Profile relationships in the superadiabatic surface layer