The eddy covariance (also known as eddy correlation and eddy flux) is a key atmospheric measurement technique to measure and calculate vertical turbulent fluxes within atmospheric boundary layers. The method analyses high-frequency wind and scalar atmospheric data series, gas, energy, and momentum, [1] which yields values of fluxes of these properties. It is a statistical method used in meteorology and other applications (micrometeorology, oceanography, hydrology, agricultural sciences, industrial and regulatory applications, etc.) to determine exchange rates of trace gases over natural ecosystems and agricultural fields, and to quantify gas emissions rates from other land and water areas. It is frequently used to estimate momentum, heat, water vapour, carbon dioxide and methane fluxes. [2] [3] [4] [5] [6] [7]
The technique is also used extensively for verification and tuning of global climate models, mesoscale and weather models, complex biogeochemical and ecological models, and remote sensing estimates from satellites and aircraft. The technique is mathematically complex, and requires significant care in setting up and processing data. To date,[ when? ] there is no uniform terminology or a single methodology for the eddy covariance technique, but much effort is being made by flux measurement networks (e.g., FluxNet, Ameriflux, ICOS, CarboEurope, Fluxnet Canada, OzFlux, NEON, and iLEAPS) to unify the various approaches.
The technique has additionally proven applicable under water to the benthic zone for measuring oxygen fluxes between the sea floor and overlying water. [8] In these environments, the technique is generally known as the eddy correlation technique, or just eddy correlation. Oxygen fluxes are extracted from raw measurements largely following the same principles as used in the atmosphere, and they are typically used as a proxy for carbon exchange, which is important for local and global carbon budgets. For most benthic ecosystems, eddy correlation is the most accurate technique for measuring in-situ fluxes. The technique's development and its applications under water remains a fruitful area of research. [9] [10] [11] [12] [13]
Air flow can be imagined as a horizontal flow of numerous rotating eddies, that is, turbulent vortices of various sizes, with each eddy having horizontal and vertical components. The situation looks chaotic, but vertical movement of the components can be measured from the tower.
At one physical point on the tower, at time 1, eddy 1 moves parcel of air c1 down at speed . Then, at time 2, eddy 2 moves parcel c2 up at speed . Each parcel has gas concentration, pressure, temperature, and humidity. If these factors, along with the speed are known, we can determine the flux. For example, if one knew how many molecules of water went down with eddies at time 1, and how many molecules went up with eddies at time 2, at the same point, one could calculate the vertical flux of water at this point over this time. So, vertical flux can be presented as a covariance of the vertical wind velocity and the concentration of the entity of interest.
The 3D wind and another variable (usually gas concentration, temperature or momentum) are decomposed into mean and fluctuating components. The covariance is calculated between the fluctuating component of the vertical wind and the fluctuating component of gas concentration. The measured flux is proportional to the covariance.
The area from which the detected eddies originate is described probabilistically and called a flux footprint. [14] The flux footprint area is dynamic in size and shape, changing with wind direction, thermal stability and measurements height, and has a gradual border.
The effect of sensor separation, finite sampling length, sonic path averaging, as well as other instrumental limitations, affect frequency response of the measurement system and may need a co-spectral correction, especially noticeable with closed-path instruments and at low heights below 1 to 1.5 m.
In mathematical terms, "eddy flux" is computed as a covariance between instantaneous deviation in vertical wind speed () from the mean value () and instantaneous deviation in gas concentration, mixing ratio (), from its mean value (), multiplied by mean air density (). Several mathematical operations and assumptions, including Reynolds decomposition, are involved in getting from physically complete equations of the turbulent flow to practical equations for computing "eddy flux," as shown below.
As of 2011 there were many software programs [15] to process eddy covariance data and derive quantities such as heat, momentum, and gas fluxes. The programs range significantly in complexity, flexibility, number of allowed instruments and variables, help system and user support. Some programs are open-source software, while others are closed-source or proprietary.
Examples include commercial software with free licence for non-commercial use such as EddyPro; open-source free programs such as ECO2S, InnFLUX, [16] and ECpack; free closed-source packages such as EdiRe, TK3, Alteddy, and EddySoft.
Common uses:
Novel uses:
Remote sensing is an approach to modeling evapotranspiration using an energy balance and the latent heat flux to find evapotranspiration rates. Evapotranspiration (ET) is a part of the water cycle, and accurate ET readings are important to local and global models to manage water resources. ET rates are an important part of research in hydrology related fields, as well as for farming practices. MOD16 is an example of a program which measures ET best for temperate climates. [1] [17]
Micrometeorology focuses climate study on the specific vegetation canopy scale, again with applications to hydrological and ecologic research. In this context, eddy covariance can be used to measure heat mass flux in the boundary surface layer, or in the boundary layer surrounding the vegetation canopy. The effects of turbulence may for example be of specific interest to climate modelers or those studying the local ecosystem. Wind speed, turbulence, and mass (heat) concentration are values that could be recorded in a flux tower. Through measurements related to eddy covariance properties such as roughness coefficients may be empirically calculated, with applications to modeling. [18]
Wetland vegetation varies widely and varies from plant to plant ecologically. Primary plant existence in wetlands can be monitored by using eddy covariance technology in conjunction with nutrient supply information by monitoring net CO2 and H2O fluxes. Readings can be taken from flux towers over a number of years to determine water use efficiency among others. [19]
Fluxes of greenhouse gasses from vegetation and agricultural fields can be measured by eddy covariance as referenced in micrometeorology section above. By measuring vertical turbulent flux of gas states of H2O, CO2, heat, and CH4 among other volatile organic compounds monitoring equipment can be used to infer canopy interaction. Landscape wide interpretations can be then inferred using the above data. High operational cost, weather limitations (some equipment is better suited for certain climates), and their resulting technical limitations may limit measurement accuracy. [20]
Vegetation production models require accurate ground observations, in this context from eddy covariant flux measurement. Eddy covariance is used to measure the net primary production, and gross primary productions of plant populations. Advancements in technology have allowed for minor fluctuations resulting in a scale of 100-2000 meter measurements of air mass and energy readings. Study of the carbon cycle on vegetated growth and production is vitally important to both growers and scientists. Using such information carbon flux between ecosystems and the atmosphere can be observed, with applications ranging from climate change to weather models. [1]
The true eddy accumulation technique can be used to measure fluxes of trace gases for which there are no fast enough analysers available, thus where the eddy covariance technique is unsuitable. The basic idea is that upwards moving air parcels (updrafts) and downwards moving air parcels (downdrafts) are sampled proportionally to their velocity into separate reservoirs. A slow response gas analyser can then be used to quantify the average gas concentrations in both updraft and downdraft reservoirs. [21] [22]
The main difference between the true and the relaxed eddy accumulation technique is that the latter samples air with a constant flow rate that is not proportional to the vertical wind speed. [23] [24] [25]
In meteorology, an anemometer is a device that measures wind speed and direction. It is a common instrument used in weather stations. The earliest known description of an anemometer was by Italian architect and author Leon Battista Alberti (1404–1472) in 1450.
Evaporation is a type of vaporization that occurs on the surface of a liquid as it changes into the gas phase. A high concentration of the evaporating substance in the surrounding gas significantly slows down evaporation, such as when humidity affects rate of evaporation of water. When the molecules of the liquid collide, they transfer energy to each other based on how they collide. When a molecule near the surface absorbs enough energy to overcome the vapor pressure, it will escape and enter the surrounding air as a gas. When evaporation occurs, the energy removed from the vaporized liquid will reduce the temperature of the liquid, resulting in evaporative cooling.
Evapotranspiration (ET) refers to the combined processes which move water from the Earth's surface into the atmosphere. It covers both water evaporation and transpiration. Evapotranspiration is an important part of the local water cycle and climate, and measurement of it plays a key role in water resource management agricultural irrigation.
In fluid dynamics, turbulence or turbulent flow is fluid motion characterized by chaotic changes in pressure and flow velocity. It is in contrast to laminar flow, which occurs when a fluid flows in parallel layers with no disruption between those layers.
Sensible heat is heat exchanged by a body or thermodynamic system in which the exchange of heat changes the temperature of the body or system, and some macroscopic variables of the body or system, but leaves unchanged certain other macroscopic variables of the body or system, such as volume or pressure.
The surface layer is the layer of a turbulent fluid most affected by interaction with a solid surface or the surface separating a gas and a liquid where the characteristics of the turbulence depend on distance from the interface. Surface layers are characterized by large normal gradients of tangential velocity and large concentration gradients of any substances transported to or from the interface.
In fluid dynamics, eddy diffusion, eddy dispersion, or turbulent diffusion is a process by which fluid substances mix together due to eddy motion. These eddies can vary widely in size, from subtropical ocean gyres down to the small Kolmogorov microscales, and occur as a result of turbulence. The theory of eddy diffusion was first developed by Sir Geoffrey Ingram Taylor.
FLUXNET is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. FLUXNET is a global 'network of regional networks' that serves to provide an infrastructure to compile, archive and distribute data for the scientific community. The most recent FLUXNET data product, FLUXNET2015, is hosted by the Lawrence Berkeley National Laboratory (USA) and is publicly available for download. Currently there are over 1000 active and historic flux measurement sites.
The MEMO model is a Eulerian non-hydrostatic prognostic mesoscale model for wind-flow simulation. It was developed by the Aristotle University of Thessaloniki in collaboration with the Universität Karlsruhe. The MEMO Model together with the photochemical dispersion model MARS are the two core models of the European zooming model (EZM). This model belongs to the family of models designed for describing atmospheric transport phenomena in the local-to-regional scale, frequently referred to as mesoscale air pollution models.
LI-COR Biosciences is an international biotech company which designs, manufactures, and markets instruments, measurement systems, and software for biological and environmental research, and develops relevant measurement methodologies and techniques.
Microscale meteorology or micrometeorology is the study of short-lived atmospheric phenomena smaller than mesoscale, about 1 kilometre (0.6 mi) or less. These two branches of meteorology are sometimes grouped together as "mesoscale and microscale meteorology" (MMM) and together study all phenomena smaller than synoptic scale; that is they study features generally too small to be depicted on a standard weather map. These include small and generally fleeting cloud "puffs" and other small cloud features. Microscale meteorology controls the most important mixing and dilution processes in the atmosphere. Important topics in microscale meteorology include heat transfer and gas exchange between soil, vegetation, and/or surface water and the atmosphere caused by near-ground turbulence. Measuring these transport processes involves use of micrometeorological towers. Variables often measured or derived include net radiation, sensible heat flux, latent heat flux, ground heat storage, and fluxes of trace gases important to the atmosphere, biosphere, and hydrosphere.
The Penman-Monteith equation approximates net evapotranspiration (ET) from meteorological data as a replacement for direct measurement of evapotranspiration. The equation is widely used, and was derived by the United Nations Food and Agriculture Organization for modeling reference evapotranspiration ET0.
Flux footprint is an upwind area where the atmospheric flux measured by an instrument is generated. Specifically, the term flux footprint describes an upwind area "seen" by the instruments measuring vertical turbulent fluxes, such that heat, water, gas and momentum transport generated in this area is registered by the instruments. Another frequently used term, fetch, usually refers to the distance from the tower when describing the footprint.
Turbulent diffusion is the transport of mass, heat, or momentum within a system due to random and chaotic time dependent motions. It occurs when turbulent fluid systems reach critical conditions in response to shear flow, which results from a combination of steep concentration gradients, density gradients, and high velocities. It occurs much more rapidly than molecular diffusion and is therefore extremely important for problems concerning mixing and transport in systems dealing with combustion, contaminants, dissolved oxygen, and solutions in industry. In these fields, turbulent diffusion acts as an excellent process for quickly reducing the concentrations of a species in a fluid or environment, in cases where this is needed for rapid mixing during processing, or rapid pollutant or contaminant reduction for safety.
Monin–Obukhov (M–O) similarity theory describes the non-dimensionalized mean flow and mean temperature in the surface layer under non-neutral conditions as a function of the dimensionless height parameter, named after Russian scientists A. S. Monin and A. M. Obukhov. Similarity theory is an empirical method that describes universal relationships between non-dimensionalized variables of fluids based on the Buckingham π theorem. Similarity theory is extensively used in boundary layer meteorology since relations in turbulent processes are not always resolvable from first principles.
The convective planetary boundary layer (CPBL), also known as the daytime planetary boundary layer, is the part of the lower troposphere most directly affected by solar heating of the Earth's surface.
Elizabeth Pattey is a principal research scientist at Agriculture and Agri-Food Canada (AAFC) and the leader of the micrometeorology laboratory at the Ottawa Research and Development Centre. Her research supports nationwide improvement in the environmental performance of agriculture, in support of the United Nations' Framework Convention on Climate Change and Canada’s Clean Air Act. She is the co-author for over 80 peer-reviewed scientific publications, and her areas of expertise include trace gas flux measurement techniques, process-based models, and remote-sensing applications.
George Burba is an American bio-atmospheric scientist, author, and inventor.
BAITSSS is biophysical Evapotranspiration (ET) computer model that determines water use, primarily in agriculture landscape, using remote sensing-based information. It was developed and refined by Ramesh Dhungel and the water resources group at University of Idaho's Kimberly Research and Extension Center since 2010. It has been used in different areas in the United States including Southern Idaho, Northern California, northwest Kansas, Texas, and Arizona.
The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) was a five-year scientific research program that investigated aspects of phytoplankton dynamics in ocean ecosystems, and how such dynamics influence atmospheric aerosols, clouds, and climate. The study focused on the sub-arctic region of the North Atlantic Ocean, which is the site of one of Earth's largest recurring phytoplankton blooms. The long history of research in this location, as well as relative ease of accessibility, made the North Atlantic an ideal location to test prevailing scientific hypotheses in an effort to better understand the role of phytoplankton aerosol emissions on Earth's energy budget.
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