Uncorrelated Noise in Turbulence Measurements

Lenschow, Donald H.; Kristensen, Leif

doi:10.1175/1520-0426(1985)002<0068:unitm>2.0.co;2

Cited by 91 publications

(82 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(Source A) Due to its physical meaning, atmospheric sampling error profiles for all higherorder moments and their combinations can be calculated after estimating the profiles of by application of turbulence statistics based on the theory derived in Lenschow and Kristensen (1985); Lenschow and Stankov (1986); Lenschow et al (1994), and Mann et al (1995). (Source B) Before higher-order moments of m are calculated, it is important to investigate whether the major part of the turbulent fluctuations was resolved by the remote sensing system.…”

Section: Fig 11mentioning

confidence: 99%

“…In-situ turbulence measurements have been used for many years to study the turbulent structure of the CBL (e.g., Lenschow and Kristensen 1985). However, remote sensing techniques such as lidar and radar systems have reached the resolution and accuracy to enable profiles of turbulent variables to be measured through the lower troposphere (e.g., Kropfli 1986;Eberhard et al 1989;Angevine et al 1993;Cohn 1995;Frehlich and Cornman 2002;Hogan et al 2009).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Wulfmeyer

Pal

Turner

et al. 2010

Boundary-Layer Meteorol

111

View full text Add to dashboard Cite

High-resolution water vapour measurements made by the Atmospheric Radiation Measurement (ARM) Raman lidar operated at the Southern Great Plains Climate Research Facility site near Lamont, Oklahoma, U.S.A. are presented. Using a 2-h measurement period for the convective boundary layer (CBL) on 13 September 2005, with temporal and spatial resolutions of 10 s and 75 m, respectively, spectral and autocovariance analyses of water vapour mixing ratio time series are performed. It is demonstrated that the major part of the inertial subrange was detected and that the integral scale was significantly larger than the time resolution. Consequently, the major part of the turbulent fluctuations was resolved. Different methods to retrieve noise error profiles yield consistent results and compare well with noise profiles estimated using Poisson statistics of the Raman lidar signals. Integral scale, mixing-ratio variance, skewness, and kurtosis profiles were determined including error bars with respect to statistical and sampling errors. The integral scale ranges between 70 and 130 s at the top of the CBL. Within the CBL, up to the third order, noise errors are significantly smaller than sampling errors and the absolute values of turbulent variables, respectively. The mixing-ratio variance profile rises monotonically from ≈0.07 to ≈3.7 g 2 kg −2 in the entrainment zone. The skewness is nearly zero up to 0.6 z/z i , becomes −1 around 0.7-0.8 z/z i , crosses zero at about 0.95 z/z i , and reaches about 1.7 at 1.1 z/z i (here, z is the height and z i is the CBL depth). The noise errors are too large to derive fourth-order moments with sufficient accuracy. Consequently, to the best of our knowledge, the ARM Raman lidar is the first water vapour Raman lidar with demonstrated capability to retrieve profiles of turbulent variables up to the third order during daytime throughout the atmospheric CBL.

show abstract

Section: Fig 11mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Wulfmeyer

Pal

Turner

et al. 2010

Boundary-Layer Meteorol

111

View full text Add to dashboard Cite

show abstract

“…In theory, therefore, very low sub-pptv DMS detection limits are achievable through signal averaging. More pertinent to the subject of this paper, however, is the effect of random noise on the flux error, which has been investigated by Lenschow and Kristensen (1985) and will be addressed in Sect. 6.…”

Section: Backgrounds and Detection Limitmentioning

confidence: 99%

Determining the sea-air flux of dimethylsulfide by eddy correlation using mass spectrometry

et al. 2010

View full text Add to dashboard Cite

Abstract. Mass spectrometric measurement of DMS by atmospheric pressure ionization with an isotopically labeled standard (APIMS-ILS) is a sensitive method with sufficient bandpass for direct flux measurements by eddy correlation. Use of an isotopically labeled internal standard greatly reduces instrumental drift, improving accuracy and precision. APIMS-ILS has been used in several recent campaigns to study ocean-atmosphere gas transfer and the chemical budget of DMS in the marine boundary layer. This paper provides a comprehensive description of the method and errors associated with DMS flux measurement from ship platforms. The APIMS-ILS instrument used by most groups today has a sensitivity of 100-200 counts s −1 pptv −1 , which is shown to be more than sufficient for flux measurement by eddy covariance. Mass spectral backgrounds (blanks) are determined by stripping DMS from ambient air with gold. The instrument is found to exhibit some high frequency signal loss, with a half-power frequency of ≈1 Hz, but a correction based on an empirically determined instrument response function is presented. Standard micrometeorological assumptions of steady state and horizontal uniformity are found to be appropriate for DMS flux measurement, but rapid changes in mean DMS mixing ratio may serve as a warning that measured flux does not represent the true surface flux. In addition, bias in surface flux estimates arising from the flux divergence is not generally significant in the surface layer, but under conditions of lowered inversion and high flux may become so. The effects of error in motion corrections and of vertical motion within the surface layer concentration gradient are discussed and the estimated maximum error from these effects is ≤18%.

show abstract

“…But the associated statistical error directly affects the magnitude of the minimal resolvable flux. A procedure proposed by Lenschow and Kristensen (1985) was used to calculate the effective detection limit for the ozone flux to be ∼0.45 nmol m −2 s −1 .…”

Section: Eddy Covariance Data Processingmentioning

confidence: 99%

Seasonal variation of ozone deposition to a tropical rain forest in southwest Amazonia

et al. 2007

View full text Add to dashboard Cite

Abstract. Within the project EUropean Studies on Trace gases and Atmospheric CHemistry as a contribution toLarge-scale Biosphere-atmosphere experiment in Amazonia (LBA-EUSTACH), we performed tower-based eddy covariance measurements of O 3 flux above an Amazonian primary rain forest at the end of the wet and dry season. Ozone deposition revealed distinct seasonal differences in the magnitude and diel variation. In the wet season, the rain forest was an effective O 3 sink with a mean daytime (midday) maximum deposition velocity of 2.3 cm s −1 , and a corresponding O 3 flux of −11 nmol m −2 s −1 . At the end of the dry season, the ozone mixing ratio was about four times higher (up to maximum values of 80 ppb) than in the wet season, as a consequence of strong regional biomass burning activity. However, the typical maximum daytime deposition flux was very similar to the wet season. This results from a strong limitation of daytime O 3 deposition due to reduced plant stomatal aperture as a response to large values of the specific humidity deficit. As a result, the average midday deposition velocity in the dry burning season was only 0.5 cm s −1 . The large diel ozone variation caused large canopy storage effects that masked the true diel variation of ozone deposition mechanisms in the measured eddy covariance flux, and for which corrections had to be made. In general, stomatal aperture was sufficient to explain the largest part of daytime ozone deposition. However, during nighttime, chemical reaction with nitrogen monoxide (NO) was found to contribute substantially to the O 3 sink in the rain forest canopy. Further contributions Correspondence to: U. Rummel (udo.rummel@dwd.de) were from non-stomatal plant uptake and other processes that could not be clearly identified.Measurements, made simultaneously on a 22 years old cattle pasture enabled the spatially and temporally direct comparison of O 3 dry deposition values from this site with typical vegetation cover of deforested land in southwest Amazonia to the results from the primary rain forest. The mean ozone deposition to the pasture was found to be systematically lower than that to the forest by 30% in the wet and 18% in the dry season.

show abstract

Uncorrelated Noise in Turbulence Measurements

Cited by 91 publications

References 11 publications

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Can Water Vapour Raman Lidar Resolve Profiles of Turbulent Variables in the Convective Boundary Layer?

Determining the sea-air flux of dimethylsulfide by eddy correlation using mass spectrometry

Seasonal variation of ozone deposition to a tropical rain forest in southwest Amazonia

Contact Info

Product

Resources

About