Advances in the True Eddy Accumulation Method: New theory, implementation, and field results

The true eddy accumulation method (TEA) provides direct measurements of ecosystem-level fluxes for a wide range of atmospheric constituents. TEA utilizes conditional sampling to overcome the requirement for a fast sensor response usually demanded by the state-of-the-art eddy covariance method (EC). However, the assumptions and conditions required for the TEA method are often not met. Here we explore the limitations caused by the assumption of zero mean vertical wind velocity during the averaging interval and by the fixed accumulation interval. We extend the theory of TEA method to non-zero vertical wind velocity by employing information about the scalar transport. We further derive a new method with adaptive time varying accumulation intervals. The new method, termed short-time eddy accumulation (STEA), was successfully implemented and deployed to measure CO2 fluxes over an agricultural field in Braunschweig, Germany. The measured fluxes matched very well against a conventional EC system (slope of 1.05, R2 of 0.87). We provide a detailed description of the setup and operation of the STEA system in the flow-through mode, devise an empirical correction for the effect of buffer volumes, and describe the important considerations for the successful operation of the STEA method. The new theory developments reduce the bias and uncertainty in the measured fluxes and create new ways to design eddy accumulation systems with finer control over sampling and accumulation. The results encourage the application of TEA and STEA for measuring fluxes of more challenging atmospheric constituents such as reactive species as well as other constituents where no fast gas analyzers are available.

Avaliação da Similaridade entre as flutuações turbulentas de escalares em ambiente de lago

This paper presents an evaluation of scalar similarity and scalar flux similarity of measurements above the water surface of the Itaipu hydroelectric reservoir. The scalars studied were: CO2 mixing ratio (rc), air temperature (θ), specific air humidity (q) and the vertical wind velocity (w). With the variance method it was found that the vertical wind velocity is in agreement with Monin-Obukhov Similarity Theory. On the other hand, the other scalars presented larger deviations in relation to the theoretical prediction. The worst results were for air temperature and mixing ratio of CO2. The most similar scalars were θ and q, with the most frequent correlation coefficient varying in the range [0.55:0.64] for measurements in unstable atmospheric conditions and in the [−0.85:−0.75] range for measurements under stable atmospheric conditions. Regarding the scalar fluxes, they presented greater similarity to each other than the scalars themselves.

Compressibility of air effects on eddy accumulation flux measurements

<p>Eddy accumulation is a direct flux measurement technique for trace gas exchange between the land surface and the atmosphere. Eddy accumulation complements the now common eddy covariance method in its ability to measure even small fluxes accurately with slow response gas analyzers and being power efficient. However, the physically most direct way of eddy accumulation, also known as true eddy accumulation (TEA), requires the sampling of air at a rate proportional to the vertical wind velocity at a fast rate of typically 10 Hz or more. Lack of suitable methods for high-speed air sampling has been a primary limitation for the practical application of eddy accumulation in the past. The compressibility of air causes a variation of pressure inside the sampling system, which affects the ability to control the sample flow rate accurately, potentially compromising the derived flux measurements. It is therefore essential to quantify the effect of compressibility on fluxes and understand the parameters which allow for mitigating the effect at the design stage.<br>In this study, we present successful true eddy accumulation measurements over the old-growth forest at the Fluxnet site Hainich (DE-Hai) and quantify the compressibility effects on fluxes. Performing simulations on high-frequency data of CO<sub>2</sub> and vertical wind velocity for a range of system configurations, we are able to quantify the impact of compressibility on fluxes and explain why our measurements were successful. We find that different system configurations lead to flux changes over a representative range of 1 to 25 percent of the flux. Key controlling parameters are the size and arrangement of internal buffer volumes and the appropriate control of the inlet flow rate sampling device as a function of internal and external pressure states. This knowledge allows to mitigate compressibility effects and design accurate true eddy accumulation flux measurements for a range of atmospheric constituents.</p>

Vertical wind velocity measurements using a five-hole probe with remotely piloted aircraft to study aerosol–cloud interactions

The importance of vertical wind velocities (in particular positive vertical wind velocities or updrafts) in atmospheric science has motivated the need to deploy multi-hole probes developed for manned aircraft in small remotely piloted aircraft (RPA). In atmospheric research, lightweight RPAs (< 2.5 kg) are now able to accurately measure atmospheric wind vectors, even in a cloud, which provides essential observing tools for understanding aerosol–cloud interactions. The European project BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) focuses on these specific interactions. In particular, vertical wind velocity at cloud base is a key parameter for studying aerosol–cloud interactions. To measure the three components of wind, a RPA is equipped with a five-hole probe, pressure sensors, and an inertial navigation system (INS). The five-hole probe is calibrated on a multi-axis platform, and the probe–INS system is validated in a wind tunnel. Once mounted on a RPA, power spectral density (PSD) functions and turbulent kinetic energy (TKE) derived from the five-hole probe are compared with sonic anemometers on a meteorological mast. During a BACCHUS field campaign at Mace Head Atmospheric Research Station (Ireland), a fleet of RPAs was deployed to profile the atmosphere and complement ground-based and satellite observations of physical and chemical properties of aerosols, clouds, and meteorological state parameters. The five-hole probe was flown on straight-and-level legs to measure vertical wind velocities within clouds. The vertical velocity measurements from the RPA are validated with vertical velocities derived from a ground-based cloud radar by showing that both measurements yield model-simulated cloud droplet number concentrations within 10 %. The updraft velocity distributions illustrate distinct relationships between vertical cloud fields in different meteorological conditions.

Measurements of Rainfall Velocity and Raindrop Size Distribution Using Coherent Doppler Lidar

Rainfall velocity, raindrop size distribution (DSD), and vertical wind velocity were simultaneously observed with 2.05- and 1.54-μm coherent Doppler lidars during convective and stratiform rain events. A retrieval method is based on identifying two separate spectra from the convolution of the aerosol and precipitation Doppler lidar spectra. The vertical wind velocity was retrieved from the aerosol spectrum peak and then the terminal rainfall velocity corrected by the vertical air motion from the precipitation spectrum peak was obtained. The DSD was derived from the precipitation spectrum using the relationship between the raindrop size and the terminal rainfall velocity. A comparison of the 1-min-averaged rainfall velocity from Doppler lidar measurements at a minimum range and that from a collocated ground-based optical disdrometer revealed high correlation coefficients of over 0.89 for both convective and stratiform rain events. The 1-min-averaged DSDs retrieved from the Doppler lidar spectrum using parametric and nonparametric methods are also in good agreement with those measured with the optical disdrometer with a correlation coefficient of over 0.80 for all rain events. To retrieve the DSD, the parametric method assumes a mathematical function for the DSD and the nonparametric method computes the direct deconvolution of the measured Doppler lidar spectrum without assuming a DSD function. It is confirmed that the Doppler lidar can retrieve the rainfall velocity and DSD during relatively heavy rain, whereas the ratio of valid data significantly decreases in light rain events because it is extremely difficult to separate the overlapping rain and aerosol peaks in the Doppler spectrum.