Seeing the Unseen: 3 Best Practices to Optimize Your Eddy Flux Measurements

What is around you that you cannot see with your naked eye?

This question might invoke images of distant galaxies, known only by state-of-the-art telescopes. Or, perhaps, you think about infrared or ultraviolet light, only visible through specialized cameras. Maybe microorganisms studied through a microscope in science classes come to mind.

But if you’re a micrometeorologist, you most likely think of surface fluxes. Despite being undetectable with our eyes, they’re always there.

Measuring fluxes isn’t as simple as setting up a sensor and walking away. Anyone who has worked in the field knows that even small oversights can make or break the quality of the data.

This is especially true in micrometeorology, where techniques such as the eddy-covariance method are used to quantify the exchange of energy and gases like water, carbon dioxide, and methane between the earth’s surface and the atmosphere. Flux is the movement of energy or mass over a specified area and time. Because fluxes in the atmosphere are primarily driven by turbulent eddies of all sizes, the measurements are sensitive to instrument design. Even minor measurement errors can accumulate over time or propagate through the intensive raw-data-processing steps, leading to biases in the final reported value of fluxes.

In a recent conversation with Edward Swiatek, Campbell Scientific’s Micrometeorology Principal Application Engineer, we thoughtfully considered how to optimize an eddy-covariance station configuration using currently available sensors. In this blog article, I’ll share some of these considerations with you.

Tip #1: Select an eddy-covariance system design that is most suitable for your application.

Is an open-path or a closed-path eddy-covariance system better for your application? To answer this, we will use the infamous engineering adage: it depends.

Both open-path and closed-path gas analyzers offer distinct benefits and trade-offs. The table below summarizes common advantages and disadvantages of each design:

As you may know, eddies often differ in size depending on their distance from the earth’s surface.

• Near the surface, turbulence is dominated by high-frequency eddies, which are smaller eddies. Open-path eddy-covariance sensors typically have a better frequency response at the higher end of the frequency spectrum, meaning that they can better measure small eddies and are therefore more suitable over short-canopy ecosystems, such as agricultural fields or native grass.
• On the opposite end of the spectrum, where large eddies dominate—such as over forest canopies—a closed-path eddy-covariance system may be ideal.

Tip #2: Achieve true timing precision in eddy-covariance measurements.

Picture this: you’re sitting in a stunning concert hall, listening to a world-class orchestra. The symphony begins with the string section's rich notes, joined seamlessly by the oboe and trumpet, with each note perfectly aligned. Then, a snare drum is added, but every beat is late. Instantly, the harmony unravels, and the music feels…off.

In the same way, eddy-covariance systems must make their measurements simultaneously. True to the name, the eddy-covariance method is a measure of how two quantities—vertical wind and scalar (temperature and gas) variations—change together. The magnitude of the covariance is a measure of the flux intensity, and the sign indicates the flux direction.

Measurements that are not made simultaneously under-report the covariance, resulting in underestimated fluxes and, therefore, inaccurate data. The importance of synchronized measurements is covered in Fratini, et al. (2018).¹ Swiatek added, “If you can’t achieve simultaneous measurements, you’ve already corrupted your data.” He went on to explain that there are three ways to ensure simultaneous measurements:

1. Preferred – Use a sonic anemometer and gas analyzer that are measured with a common set of electronics. Alternatively, use instrumentation with internal clocks that can be continuously regulated to a time standard, such as a global positioning system (GPS). This will ensure that the measurements are essentially made simultaneously.
2. Alternative – Use a stand-alone sonic anemometer and gas analyzer that support a measurement trigger command from the data-acquisition system. The command will drive the measurement cycle for both sensors rather than relying on the instrument’s clocks, which are prone to drift.
3. Least Preferred – Use stand-alone sonic anemometers and gas analyzers running on their own internal clocks at the fastest measurement frequency and output frequency. Because all clocks drift over time, it isn't possible to ensure that the measurements from those two sensors are made simultaneously.

Tip #3: Use sensors with horizontal symmetry to minimize flow distortion.

Eddy-covariance sensors measure turbulence. When sensors are installed in the field, their very presence affects the wind field—both the mean and turbulence flow. The only way to mitigate flow distortion caused by the sensors, mounting hardware, and tower is to mount the turbulence sensors to point into the direction of the prevailing wind.

Better sensor installation in the field requires better sensor design. A key consideration in sensor design is horizontal symmetry for both the sonic and gas analyzers, as suggested by Wyngaard (1988).² Sensors designed with horizontal symmetry divide the mean airflow symmetrically over the top and bottom of the instrument, thereby “cancelling out” the mean flow distortion caused by the sensor’s geometry.

Measuring the Invisible

As invisible as they may be, fluxes shape our environment in powerful ways. Measuring them with precision requires more than just deploying an instrument. It also requires careful sensor selection and system design, attention to detail, and an understanding of how every component in your system influences your data quality.

By applying the principles in this article, micrometeorologists can reduce uncertainty, protect data integrity, and further understand the complex exchanges between the earth’s surface and the atmosphere.

The better we measure the world around us, the better we can understand it.

Our micrometeorologists take pride in providing researchers with the most reliable data possible. Start the conversation and connect with one of our experts today!

Credits: Edward Swiatek of Campbell Scientific, Inc. contributed to this article.

References

¹ Fratini, G., Sabbatini, S., Ediger, K., Riensche, B., Burba, G., Nicolini, G., Vitale, D., and Papale, D. (2018). Eddy covariance flux errors due to random and systematic timing errors during data acquisition. Biogeosciences, 5473-5487.

² Wyngaard, J. (1988). The Effects of Probe-Induced Flow Distortion on Atmospheric Turbulence Measurements: Extension to Scalars. Journal of the Atmospheric Sciences, 3400-3412.