scholarly journals Quantification of surface energy fluxes from a small water body using scintillometry and eddy covariance

2014 ◽  
Vol 50 (1) ◽  
pp. 494-513 ◽  
Author(s):  
Ryan McGloin ◽  
Hamish McGowan ◽  
David McJannet ◽  
Freeman Cook ◽  
Andrey Sogachev ◽  
...  
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Water Body ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Small Water ◽  
Small Water Body

Using Spatial Eddy Covariance to Investigate Energy Balance Closure over a Heterogeneous Ecosystem

2020 ◽  
Author(s):  
Brian Butterworth ◽  
Ankur Desai ◽  
Sreenath Paleri ◽  
Stefan Metzger ◽  
David Durden ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Energy Balance ◽  
Surface Energy ◽  
Atmospheric Boundary Layer ◽  
Eddy Covariance ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Land Surface Heterogeneity

<p>Land surface heterogeneity influences patterns of sensible and latent heat flux, which in turn affect processes in the atmospheric boundary layer. However, gridded atmospheric models often fail to incorporate the influence of land surface heterogeneity due to differences between the temporal and spatial scales of models compared to the local, sub-grid processes. Improving models requires the scaling of surface flux measurements; a process made difficult by the fact that surface measurements usually find an imbalance in the energy budget.</p><p>The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was an observational experiment designed to investigate how the atmospheric boundary layer responds to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges. The campaign was conducted from June – October 2019, measuring surface energy fluxes over a heterogeneous forest ecosystem as fluxes transitioned from latent heat-dominated summer through sensible heat-dominated fall. Observations were made by ground, airborne, and satellite platforms within the 10 x 10 km study region, which was chosen to match the scale of a typical model grid cell. The spatial distribution of energy fluxes was observed by an array of 20 eddy covariance towers and a low-flying aircraft. Mesoscale atmospheric properties were measured by a suite of LiDAR and sounding instruments, measuring winds, water vapor, temperature, and boundary layer development. Plant phenology was measured in-situ and mapped remotely using hyperspectral imaging.</p><p>The dense set of multi-scale observations of land-atmosphere exchange collected during the CHEESEHEAD field campaign permits combining the spatial and temporal distribution of energy fluxes with mesoscale surface and atmospheric properties. This provides an unprecedented data foundation to evaluate theoretical explanations of energy balance non-closure, as well as to evaluate methods for scaling surface energy fluxes for improved model-data comparison. Here we show how fluxes calculated using a spatial eddy covariance technique across the 20-tower network compare to those of standard temporal eddy covariance fluxes in order to characterize of the spatial representativeness of single tower eddy covariance measurements. Additionally, we show how spatial EC fluxes can be used to better understand the energy balance over heterogeneous ecosystems.</p>

scholarly journals Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

2018 ◽  
Author(s):  
Andrei Serafimovich ◽  
Stefan Metzger ◽  
Jörg Hartmann ◽  
Katrin Kohnert ◽  
Donatella Zona ◽  
...  
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Land Surface ◽  
Response Functions ◽  
Sensible Heat ◽  
Environmental Response ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land–surface models we investigated spatial patterns of energy fluxes in relation to land–surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

scholarly journals Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

2018 ◽  
Vol 18 (13) ◽  
pp. 10007-10023 ◽  
Author(s):  
Andrei Serafimovich ◽  
Stefan Metzger ◽  
Jörg Hartmann ◽  
Katrin Kohnert ◽  
Donatella Zona ◽  
...  
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Land Surface ◽  
Response Functions ◽  
Sensible Heat ◽  
Environmental Response ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high-resolution flux maps. In order to support the evaluation of coupled atmospheric–land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the Polar 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modeled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modeled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and they provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

scholarly journals Measurement of Surface Energy Fluxes from Two Rangeland Sites and Comparison with a Multilayer Canopy Model

2012 ◽  
Vol 13 (3) ◽  
pp. 1038-1051 ◽  
Author(s):  
Gerald N. Flerchinger ◽  
Michele L. Reba ◽  
Danny Marks
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Sensible Heat Flux ◽  
Theory Approach ◽  
Turbulent Transfer ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Transfer Equations ◽  
K Theory ◽  
Canopy Model

Abstract Rangelands are often characterized by a patchy mosaic of vegetation types, making measurement and modeling of surface energy fluxes particularly challenging. The purpose of this study was to evaluate surface energy fluxes measured using three eddy covariance systems above and within two rangeland vegetation sites and use the data to improve simulations of turbulent energy fluxes in a multilayer plant canopy model: the Simultaneous Heat and Water (SHAW) model. Model modifications included adjustment of the wind profile roughness parameters for sparse canopies, extending the currently used K-theory approach to include influence of the roughness sublayer and stability functions within the canopy, and in a separate version of the model, introducing Lagrangian far-field turbulent transfer equations (L theory) in lieu of the K-theory approach. There was relatively little difference in simulated energy fluxes for the aspen canopy using L-theory versus K-theory turbulent transfer equations, but L theory tracked canopy air temperature profiles better during the growing season. Upward sensible heat flux was observed above aspen trees, within the aspen understory, and above sagebrush throughout the active snowmelt season. Model simulations confirmed the observed upward sensible flux during snowmelt was due to solar heating of the aspen limbs and sagebrush. Thus, the eddy covariance (EC) systems were unable to properly quantify fluxes at the snow surface when vegetation was present. Good agreement between measured and modeled energy fluxes suggest that they can be measured and simulated reliably in these complex environments, but care must be used in the interpretation of the results.

scholarly journals Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

2014 ◽  
Vol 11 (3) ◽  
pp. 4857-4908 ◽  
Author(s):  
R. Guzinski ◽  
H. Nieto ◽  
R. Jensen ◽  
G. Mendiguren
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Spatial Resolution ◽  
Land Surface ◽  
Agricultural Landscape ◽  
Remotely Sensed ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Coniferous Plantation ◽  
Agricultural Site

Abstract. In this study we evaluate a methodology for disaggregating land surface energy fluxes estimated with the Dual Time Difference (DTD) model which uses the day and night polar orbiting satellites observations of Land Surface Temperature (LST) as a remotely sensed input. The DTD model is run with MODIS input data at a spatial resolution of around 1 km while the disaggregation uses Landsat observations of LST to produce fluxes at a nominal spatial resolution of 30 m. The higher resolution modeled fluxes can be directly compared against eddy-covariance based flux tower measurements to ensure more accurate model validation and also provide a better visualization of fluxes' spatial patterns in heterogeneous areas allowing for development of, for example, more efficient irrigation practices. The disaggregation technique is evaluated in an area covered by the Danish Hydrological Observatory (HOBE), in the west of the Jutland peninsula, and the modeled fluxes are compared against measurements from two flux towers: first one in a heterogeneous agricultural landscape and second one in a homogeneous conifer plantation. The results indicate that the disaggregated fluxes have greatly improved accuracy as compared to high resolution fluxes derived directly with Landsat data without the disaggregation. At the agricultural site the disaggregated fluxes display negligible bias and almost perfect correlation (r > 0.90) with Eddy Covariance based measurements, while at the plantation site the results are encouraging but not ideal. In addition we introduce a modification to the DTD model by replacing the "parallel" configuration of the resistances to sensible heat exchange by the "series" configuration. The later takes into account the in-canopy air temperature and substantially improves the accuracy of the DTD model.

scholarly journals Comparison of FASST and SNTHERM in Three Snow Accumulation Regimes

2008 ◽  
Vol 9 (6) ◽  
pp. 1443-1463 ◽  
Author(s):  
Susan Frankenstein ◽  
Anne Sawyer ◽  
Julie Koeberle
Keyword(s):  
Surface Energy ◽  
Single Layer ◽  
Soil Strength ◽  
Snow Accumulation ◽  
Dynamic State ◽  
Energy Fluxes ◽  
One Dimensional ◽  
Surface Energy Fluxes ◽  
Snow Model ◽  
Surface Ice

Abstract Numerical experiments of snow accumulation and depletion were carried out as well as surface energy fluxes over four Cold Land Processes Experiment (CLPX) sites in Colorado using the Snow Thermal model (SNTHERM) and the Fast All-Season Soil Strength model (FASST). SNTHERM is a multilayer snow model developed to describe changes in snow properties as a function of depth and time, using a one-dimensional mass and energy balance. The model is intended for seasonal snow covers and addresses conditions found throughout the winter, from initial ground freezing in the fall to snow ablation in the spring. It has been used by many researchers over a variety of terrains. FASST is a newly developed one-dimensional dynamic state-of-the-ground model. It calculates the ground’s moisture content, ice content, temperature, and freeze–thaw profiles as well as soil strength and surface ice and snow accumulation/depletion. Because FASST is newer and not as well known, the authors wanted to determine its use as a snow model by comparing it with SNTHERM, one of the most established snow models available. It is demonstrated that even though FASST is only a single-layer snow model, the RMSE snow depth compared very favorably against SNTHERM, often performing better during the accumulation phase. The surface energy fluxes calculated by the two models were also compared and were found to be similar.

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