Abstract Measurements made in the Columbia River Basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP 2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modelled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin-Obukhov similarity and (ii) a modified Priestley-Taylor (P-T) algorithm with physically based ecophysiological constraints which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP 2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various timescales based on the modelled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP 2, a hybrid approach can be used for similar flux-tower sites and field campaigns.
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Bulk Transfer Coefficients Estimated From Eddy‐Covariance Measurements Over Lakes and Reservoirs
The drag coefficient, Stanton number and Dalton number are of particular importance for estimating the surface turbulent fluxes of momentum, heat and water vapor using bulk parameterization. Although these bulk transfer coefficients have been extensively studied over the past several decades in marine and large‐lake environments, there are no studies analyzing their variability for smaller lakes. Here, we evaluated these coefficients through directly measured surface fluxes using the eddy‐covariance technique over more than 30 lakes and reservoirs of different sizes and depths. Our analysis showed that the transfer coefficients (adjusted to neutral atmospheric stability) were generally within the range reported in previous studies for large lakes and oceans. All transfer coefficients exhibit a substantial increase at low wind speeds (<3 m s−1), which was found to be associated with the presence of gusts and capillary waves (except Dalton number). Stanton number was found to be on average a factor of 1.3 higher than Dalton number, likely affecting the Bowen ratio method. At high wind speeds, the transfer coefficients remained relatively constant at values of 1.6·10−3, 1.4·10−3, 1.0·10−3, respectively. We found that the variability of the transfer coefficients among the lakes could be associated with lake surface area. In flux parameterizations at lake surfaces, it is recommended to consider variations in the drag coefficient and Stanton number due to wind gustiness and capillary wave roughness while Dalton number could be considered as constant at all wind speeds.
more » « less- Award ID(s):
- 2025982
- NSF-PAR ID:
- 10492663
- Publisher / Repository:
- Journal of Geophysical Research: Atmospheres
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 128
- Issue:
- 2
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)The hydrodynamics within small boreal lakes have rarely been studied, yet knowing whether turbulence at the air-water interface and in the water column scales with metrics developed elsewhere is essential for computing metabolism and fluxes of climate-forcing trace gases. We instrumented a humic, 4.7 ha, boreal lake with 2 meteorological stations, 3 thermistor arrays, an infra-red (IR) camera to quantify surface divergence, obtained turbulence as dissipation rate of turbulent kinetic energy (ε) using an acoustic Doppler velocimeter and a temperature-gradient microstructure profiler, and conducted chamber measurements for short periods to obtain fluxes and gas transfer velocities (k). Near-surface ε varied from 10-8 m2 s-3 to 10-6 m2 s-3 for the 0 to 4 m s-1 winds and followed predictions from Monin-Obukhov similarity theory. The coefficient of eddy diffusivity in the mixed layer was up to 10-3 m2 s-1 on the windiest afternoons, an order of magnitude less other afternoons, and near molecular at deeper depths. The upper thermocline upwelled when Lake numbers (LN) dropped below 4 facilitating vertical and horizontal exchange. k computed from a surface renewal model using ε agreed with values from chambers and surface divergence and increased linearly with wind speed. Diurnal thermoclines formed on sunny days when winds were < 3 m s-1, a condition that can lead to elevated near-surface ε and k. Results extend scaling approaches developed in the laboratory and for larger water bodies, illustrate turbulence and k are greater than expected in small wind-sheltered lakes, and provide new equations to quantify fluxes.more » « less
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null (Ed.)Wake-induced aerodynamics of yawed circular cylinders with smooth and grooved surfaces in a tandem arrangement was studied. This pair of cylinders represent sections of stay-cables with smooth surfaces and high-voltage power conductors with grooved surfaces that are vulnerable to flow-induced structural failure. The study provides some insight for a better understanding of wake-induced loads and galloping problem of bundled cables. All experiments in this study were conducted using a pair of stationary section models of circular cylinders in a wind tunnel subjected to uniform and smooth flow. The aerodynamic force coefficients and vortex-shedding frequency of the downstream model were extracted from the surface pressure distribution. For measurement, polished aluminum tubes were used as smooth cables; and hollow tubes with a helically grooved surface were used as power conductors. The aerodynamic properties of the downstream model were captured at wind speeds of about 6-23 m/s (Reynolds number of 5×10^4 to 2.67×10^5 for smooth cable and 2×10^4 to 1.01×10^5 for grooved cable) and yaw angles ranging from 0º to 45º while the upstream model was fixed at various spacing between the two model cylinders. The results showed that the Strouhal number of yawed cable is less than the non-yawed case at a given Reynolds number, and its value is smaller than the Strouhal number of a single cable. Additionally, compared to the single smooth cable, it was observed that there was a reduction of drag coefficient of the downstream model, but no change in a drag coefficient of the downstream grooved case in the range of Reynolds number in this study.more » « less
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This dataset contains three netcdf files that pertain to monthly, seasonal, and annual fields of surface wind stress, wind stress curl, and curl-derived upwelling velocities over the Northwest Atlantic (80-45W, 30-45N) covering a forty year period from 1980 to 2019. Six-hourly surface (10 m) wind speed components from the Japanese 55-year reanalysis (JRA-55; Kobayashi et al., 2015) were processed from 1980 to 2019 over a larger North Atlantic domain of 100W to 10E and 10N to 80N. Wind stress was computed using a modified step-wise formulation, originally based on (Gill, 1982) and a non-linear drag coefficient (Large and Pond, 1981), and later modified for low speeds (Trenberth et al., 1989). See Gifford (2023) for more details.
After the six-hourly zonal and meridional wind stresses were calculated, the zonal change in meridional stress (curlx) and the negative meridional change in zonal stress (curly) were found using NumPy’s gradient function in Python (Harris et al., 2020) over the larger North Atlantic domain (100W-10E, 10-80N). The curl (curlx + curly) over the study domain (80-45W, 10-80N) is then extracted, which maintain a constant order of computational accuracy in the interior and along the boundaries for the smaller domain in a centered-difference gradient calculation.
The monthly averages of the 6-hour daily stresses and curls were then computed using the command line suite climate data operators (CDO, Schulzweida, 2022) monmean function. The seasonal (3-month average) and annual averages (12-month average) were calculated in Python using the monthly fields with NumPy (NumPy, Harris et al., 2020).
Corresponding upwelling velocities at different time-scales were obtained from the respective curl fields and zonal wind stress by using the Ekman pumping equation of the study by Risien and Chelton (2008; page 2393). Please see Gifford (2023) for more details.
The files each contain nine variables that include longitude, latitude, time, zonal wind stress, meridional wind stress, zonal change in meridional wind stress (curlx), the negative meridional change in zonal wind stress (curly), total curl, and upwelling. Units of time begin in 1980 and are months, seasons (JFM etc.), and years to 2019. The longitude variable extends from 80W to 45W and latitude is 30N to 45N with uniform 1.25 degree resolution.
Units of stress are in Pascals, units of curl are in Pascals per meter, and upwelling velocity is described by centimeters per day. The spatial grid is a 29 x 13 longitude x latitude array.
Filenames:
monthly_windstress_wsc_upwelling.nc: 480 time steps from 80W to 45W and 30N to 45N.
seasonal_windstress_wsc_upwelling.nc: 160 time steps from 80W to 45W and 30N to 45N.
annual_windstress_wsc_upwelling.nc: 40 time steps from 80W to 45W and 30N to 45N.
Please contact igifford@earth.miami.edu for any queries. {"references": ["Gifford, I.H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gill, A. E. (1982). Atmosphere-ocean dynamics (Vol. 30). Academic Press.", "Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357\u2013362 (2020). DOI: 10.1038/s41586-020-2649-2.", "Japan Meteorological Agency/Japan (2013), JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, https://doi.org/10.5065/D6HH6H41, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colo. (Updated monthly.)", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48.", "Large, W.G. and Pond, S., 1981. Open ocean momentum flux measurements in moderate to strong winds.\u202fJournal of physical oceanography,\u202f11(3), pp.324-336.", "Risien, C.M. and Chelton, D.B., 2008. A global climatology of surface wind and wind stress fields from eight years of QuikSCAT scatterometer data.\u202fJournal of Physical Oceanography,\u202f38(11), pp.2379-2413.", "Schulzweida, Uwe. (2022). CDO User Guide (2.1.0). Zenodo. https://doi.org/10.5281/zenodo.7112925.", "Trenberth, K.E., Large, W.G. and Olson, J.G., 1989. The effective drag coefficient for evaluating wind stress over the oceans.\u202fJournal of Climate,\u202f2(12), pp.1507-1516."]} -
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Abstract The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10−3for wind speeds of 25–55 m s−1. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2022JD037219
