scholarly journals Optimizing Window Length for Turbulent Heat Flux Calculations from Airborne Eddy Covariance Measurements under Near Neutral to Unstable Atmospheric Stability Conditions

2018 ◽  
Vol 10 (5) ◽  
pp. 670 ◽  
Author(s):  
Yibo Sun ◽  
Li Jia ◽  
Qiting Chen ◽  
Chaolei Zheng
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Atmospheric Stability ◽  
Turbulent Heat Flux ◽  
Stability Conditions ◽  
Turbulent Heat ◽  
Window Length ◽  
Eddy Covariance Measurements

scholarly journals Evaluating and improving modeled turbulent heat fluxes across the North American Great Lakes

2018 ◽  
Vol 22 (10) ◽  
pp. 5559-5578 ◽  
Author(s):  
Umarporn Charusombat ◽  
Ayumi Fujisaki-Manome ◽  
Andrew D. Gronewold ◽  
Brent M. Lofgren ◽  
Eric J. Anderson ◽  
...  
Keyword(s):  
Heat Flux ◽  
Great Lakes ◽  
Eddy Covariance ◽  
North American ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
The North ◽  
Turbulent Heat Fluxes ◽  
North American Great Lakes ◽  
Eddy Covariance Measurements

Abstract. Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the North American Great Lakes. These fluxes can be measured in situ using eddy covariance techniques and are regularly included as a component of lake–atmosphere models. To help ensure accurate projections of lake temperature, circulation, and regional meteorology, we validated the output of five algorithms used in three popular models to calculate surface heat fluxes: the Finite Volume Community Ocean Model (FVCOM, with three different options for heat flux algorithm), the Weather Research and Forecasting (WRF) model, and the Large Lake Thermodynamic Model. These models are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system. We isolated only the code for the heat flux algorithms from each model and drove them using meteorological data from four over-lake stations within the Great Lakes Evaporation Network (GLEN), where eddy covariance measurements were also made, enabling co-located comparison. All algorithms reasonably reproduced the seasonal cycle of the turbulent heat fluxes, but all of the algorithms except for the Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm showed notable overestimation of the fluxes in fall and winter. Overall, COARE had the best agreement with eddy covariance measurements. The four algorithms other than COARE were altered by updating the parameterization of roughness length scales for air temperature and humidity to match those used in COARE, yielding improved agreement between modeled and observed sensible and latent heat fluxes.

scholarly journals A multi-season investigation of glacier surface roughness lengths through in situ and remote observation

2019 ◽  
Vol 13 (3) ◽  
pp. 1051-1071 ◽  
Author(s):  
Noel Fitzpatrick ◽  
Valentina Radić ◽  
Brian Menounos
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Wind Direction ◽  
Roughness Length ◽  
Turbulent Heat Flux ◽  
Turbulent Heat ◽  
Glacier Surface ◽  
Roughness Lengths ◽  
Order Of Magnitude

Abstract. The roughness length values for momentum, temperature, and water vapour are key inputs to the bulk aerodynamic method for estimating turbulent heat flux. Measurements of site-specific roughness length are rare for glacier surfaces, and substantial uncertainty remains in the values and ratios commonly assumed when parameterising turbulence. Over three melt seasons, eddy covariance observations were implemented to derive the momentum and scalar roughness lengths at several locations on two mid-latitude mountain glaciers. In addition, two techniques were developed in this study for the remote estimation of momentum roughness length, utilising lidar-derived digital elevation models with a 1×1 m resolution. Seasonal mean momentum roughness length values derived from eddy covariance observations at each location ranged from 0.7 to 4.5 mm for ice surfaces and 0.5 to 2.4 mm for snow surfaces. From one season to the next, mean momentum roughness length values over ice remained relatively consistent at a given location (0–1 mm difference between seasonal mean values), while within a season, temporal variability in momentum roughness length over melting snow was found to be substantial (> an order of magnitude). The two remote techniques were able to differentiate between ice and snow cover and return momentum roughness lengths that were within 1–2 mm (≪ an order of magnitude) of the in situ eddy covariance values. Changes in wind direction affected the magnitude of the momentum roughness length due to the anisotropic nature of features on a melting glacier surface. Persistence in downslope wind direction on the glacier surfaces, however, reduced the influence of this variability. Scalar roughness length values showed considerable variation (up to 2.5 orders of magnitude) between locations and seasons and no evidence of a constant ratio with momentum roughness length or each other. Of the tested estimation methods, the Andreas (1987) surface renewal model returned scalar roughness lengths closest to those derived from eddy covariance observations. Combining this scalar method with the remote techniques developed here for estimating momentum roughness length may facilitate the distributed parameterisation of turbulent heat flux over glacier surfaces without in situ measurements.

scholarly journals In Situ and Satellite Evaluation of Air–Sea Flux Variation near Ocean Temperature Gradients

2016 ◽  
Vol 29 (4) ◽  
pp. 1583-1602 ◽  
Author(s):  
Amanda Plagge ◽  
James B. Edson ◽  
Douglas Vandemark
Keyword(s):  
Heat Flux ◽  
Similarity Theory ◽  
Atmospheric Stability ◽  
Correlation Coefficients ◽  
Turbulent Heat Flux ◽  
Gradient Force ◽  
Turbulent Heat ◽  
Pressure Gradient Force ◽  
Coupling Coefficients ◽  
Flux Variation

Abstract Observations of ocean–atmosphere coupling across persistent mesoscale sea surface temperature (SST) gradients are used to examine the controls of atmospheric stability, pressure gradient force, and heat flux that are considered central to oft-observed coupling between wind and SST. Moored air–sea flux measurements near the Gulf Stream are combined with QuikSCAT satellite scatterometer equivalent neutral wind (ENW) data to assess correlations between SST, air–sea fluxes, pressure, and wind perturbations at scales of 10–100 days. The net effect of ocean fronts meandering past the site enabled buoy observation of SST impacts on wind, with coupling coefficients of 0.3–0.5 similar to past studies. Wind stress–SST and ENW–SST correlation coefficients are slightly higher, and roughly 20% of the ENW perturbation is attributed to stratification impacts predicted by Monin–Obukhov (MO) similarity theory. Significantly higher correlation is observed when relating wind or stress perturbations to buoyant heat flux variation. Atmospheric pressure perturbation with SST of order 0.5 hPa °C−1 is observed, as well as high negative correlation between wind and pressure variations. Length and time scales associated with the coupling indicate that peak correlations occur at 50–70 days and 300–500 km, consistent with mesoscale meander scales. Coupling coefficient values vary significantly depending on analysis time scale and exhibit a range near to recently observed interbasin variability. This variability is attributed to the extent of oceanic length scales permitted in the analysis. Together, results affirm the central role of SST-induced turbulent heat flux in controlling pressure field adjustments and thereby the wind perturbations over SST fronts.

scholarly journals Estimating evaporation with thermal UAV data and two-source energy balance models

2016 ◽  
Vol 20 (2) ◽  
pp. 697-713 ◽  
Author(s):  
H. Hoffmann ◽  
H. Nieto ◽  
R. Jensen ◽  
R. Guzinski ◽  
P. Zarco-Tejada ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
High Resolution ◽  
Eddy Covariance ◽  
Land Surface ◽  
Weather Conditions ◽  
Heat Fluxes ◽  
Thermal Camera ◽  
Model Input ◽  
Eddy Covariance Measurements

Abstract. Estimating evaporation is important when managing water resources and cultivating crops. Evaporation can be estimated using land surface heat flux models and remotely sensed land surface temperatures (LST), which have recently become obtainable in very high resolution using lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this study a thermal camera was mounted on a UAV and applied into the field of heat fluxes and hydrology by concatenating thermal images into mosaics of LST and using these as input for the two-source energy balance (TSEB) modelling scheme. Thermal images are obtained with a fixed-wing UAV overflying a barley field in western Denmark during the growing season of 2014 and a spatial resolution of 0.20 m is obtained in final LST mosaics. Two models are used: the original TSEB model (TSEB-PT) and a dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model, the DTD model accounts for the bias that is likely present in remotely sensed LST. TSEB-PT and DTD have already been well tested, however only during sunny weather conditions and with satellite images serving as thermal input. The aim of this study is to assess whether a lightweight thermal camera mounted on a UAV is able to provide data of sufficient quality to constitute as model input and thus attain accurate and high spatial and temporal resolution surface energy heat fluxes, with special focus on latent heat flux (evaporation). Furthermore, this study evaluates the performance of the TSEB scheme during cloudy and overcast weather conditions, which is feasible due to the low data retrieval altitude (due to low UAV flying altitude) compared to satellite thermal data that are only available during clear-sky conditions. TSEB-PT and DTD fluxes are compared and validated against eddy covariance measurements and the comparison shows that both TSEB-PT and DTD simulations are in good agreement with eddy covariance measurements, with DTD obtaining the best results. The DTD model provides results comparable to studies estimating evaporation with similar experimental setups, but with LST retrieved from satellites instead of a UAV. Further, systematic irrigation patterns on the barley field provide confidence in the veracity of the spatially distributed evaporation revealed by model output maps. Lastly, this study outlines and discusses the thermal UAV image processing that results in mosaics suited for model input. This study shows that the UAV platform and the lightweight thermal camera provide high spatial and temporal resolution data valid for model input and for other potential applications requiring high-resolution and consistent LST.

Fluid Mechanics and Heat Transfer Measurements in Transitional Boundary Layers Conditionally Sampled on Intermittency

1994 ◽  
Vol 116 (3) ◽  
pp. 405-416 ◽  
Author(s):  
J. Kim ◽  
T. W. Simon ◽  
M. Kestoras
Keyword(s):  
Heat Flux ◽  
Plate Boundary ◽  
Turbulent Heat Flux ◽  
Transitional Flow ◽  
Turbulent Heat ◽  
Mean Velocity ◽  
Power Spectral ◽  
Turbulent Characteristics ◽  
Transition Models ◽  
Prandtl Numbers

An experimental investigation of transition on a flat-plate boundary layer was performed. Mean and turbulence quantities, including turbulent heat flux, were sampled according to the intermittency function. Such sampling allows segregation of the signal into two types of behavior—laminarlike and turbulentlike. Results show that during transition these two types of behavior cannot be thought of as separate Blasius and fully turbulent profiles, respectively. Thus, simple transition models in which the desired quantity is assumed to be an average, weighted on intermittency, of the laminar and fully turbulent values may not be entirely successful. Deviation of the flow identified as laminarlike from theoretical laminar behavior is due to a slow recovery after the passage of a turbulent spot, while deviation of the flow identified as turbulentlike from fully turbulent characteristics is possibly due to an incomplete establishment of the fully turbulent power spectral distribution. Measurements were taken for two levels of free-stream disturbance—0.32 and 1.79 percent. Turbulent Prandtl numbers for the transitional flow, computed from measured shear stress, turbulent heat flux, and mean velocity and temperature profiles, were less than unity.

An explicit algebraic Reynolds-stress and scalar-flux model for stably stratified flows

2013 ◽  
Vol 723 ◽  
pp. 91-125 ◽  
Author(s):  
W. M. J. Lazeroms ◽  
G. Brethouwer ◽  
S. Wallin ◽  
A. V. Johansson
Keyword(s):  
Heat Flux ◽  
Kinetic Energy ◽  
Temperature Gradient ◽  
Reynolds Stress ◽  
Turbulent Heat Flux ◽  
Turbulent Heat ◽  
Homogeneous Shear ◽  
Self Consistent ◽  
The Mean ◽  
Homogeneous Shear Flow

AbstractThis work describes the derivation of an algebraic model for the Reynolds stresses and turbulent heat flux in stably stratified turbulent flows, which are mutually coupled for this type of flow. For general two-dimensional mean flows, we present a correct way of expressing the Reynolds-stress anisotropy and the (normalized) turbulent heat flux as tensorial combinations of the mean strain rate, the mean rotation rate, the mean temperature gradient and gravity. A system of linear equations is derived for the coefficients in these expansions, which can easily be solved with computer algebra software for a specific choice of the model constants. The general model is simplified in the case of parallel mean shear flows where the temperature gradient is aligned with gravity. For this case, fully explicit and coupled expressions for the Reynolds-stress tensor and heat-flux vector are given. A self-consistent derivation of this model would, however, require finding a root of a polynomial equation of sixth-order, for which no simple analytical expression exists. Therefore, the nonlinear part of the algebraic equations is modelled through an approximation that is close to the consistent formulation. By using the framework of a$K\text{{\ndash}} \omega $model (where$K$is turbulent kinetic energy and$\omega $an inverse time scale) and, where needed, near-wall corrections, the model is applied to homogeneous shear flow and turbulent channel flow, both with stable stratification. For the case of homogeneous shear flow, the model predicts a critical Richardson number of 0.25 above which the turbulent kinetic energy decays to zero. The channel-flow results agree well with DNS data. Furthermore, the model is shown to be robust and approximately self-consistent. It also fulfils the requirements of realizability.

Sign in / Sign up

Export Citation Format

Share Document