Wind Measurements Near the Surface of Waves

2013 ◽  
Author(s):  
Alexander V. Babanin ◽  
Jason McConochie
Keyword(s):  
Surface Wind ◽  
Constant Flux ◽  
Wind Speeds ◽  
Momentum Fluxes ◽  
Wind Measurements ◽  
The Mean ◽  
Flux Layer ◽  
Logarithmic Layer ◽  
Wave Boundary

Wind-over-wave in situ measurements are typically conducted in two different fashions: either by means of wave-riding buoys, or by placing anemometers well elevated above the surface. Routinely, concept of the constant-flux layer is invoked to convert one into another as necessary. In the paper, comparisons of mean wind speeds and wind-momentum fluxes are conducted, based on measurements throughout the wave boundary layer, including wave-follower measurements very near the surface. Significant deviations from the constant-flux expectations are found. Near the surface, the fluxes are less than those obtained by extrapolation within the logarithmic-layer assumption, and the mean wind speeds are correspondingly larger. Such results have significant implications for modelling the wind-generated waves and for calibrations of remotely sensed surface wind conditions.

scholarly journals Winds near the Surface of Waves: Observations and Modeling

2018 ◽  
Vol 48 (5) ◽  
pp. 1079-1088 ◽  
Author(s):  
Alexander V. Babanin ◽  
Jason McConochie ◽  
Dmitry Chalikov
Keyword(s):  
Boundary Layer ◽  
Wind Wave ◽  
Wave Boundary Layer ◽  
Wind Speeds ◽  
Vertical Profiling ◽  
The Mean ◽  
Flux Layer ◽  
Logarithmic Layer ◽  
Wave Boundary ◽  
Lake George

AbstractThe concept of a constant-flux layer is usually employed for vertical profiling of the wind measured at some elevation near the ocean surface. The surface waves, however, modify the balance of turbulent stresses very near the surface, and therefore such extrapolations can introduce significant biases. This is particularly true for buoy measurements in extreme conditions, when the anemometer mast is within the wave boundary layer (WBL) or even below the wave crests. In this paper, field data and a WBL model are used to investigate such biases. It is shown that near the surface the turbulent stresses are less than those obtained by extrapolation using the logarithmic-layer assumption, and the mean wind speeds very near the surface, based on Lake George field observations, are up to 5% larger. The behavior is then simulated by means of a WBL model coupled with nonlinear waves, which confirmed the observations and revealed further details of complex behaviors at the wind-wave boundary layer.

scholarly journals Evaluation of the Ocean Surface Wind Speed Change following the Super Typhoon from Space-Borne GNSS-Reflectometry

2020 ◽  
Vol 12 (12) ◽  
pp. 2034 ◽  
Author(s):  
Hongsu Liu ◽  
Shuanggen Jin ◽  
Qingyun Yan
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Mean Error ◽  
Super Typhoon ◽  
The Mean ◽  
Ocean Surface Wind

Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s; the mean error was 3.57 m/s; the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.

scholarly journals Standardization of Offshore Surface Wind Speeds

2016 ◽  
Vol 55 (5) ◽  
pp. 1107-1121 ◽  
Author(s):  
Y. C. He ◽  
P. W. Chan ◽  
Q. S. Li
Keyword(s):  
Shallow Water ◽  
Surface Wind ◽  
Reference Conditions ◽  
Deep Ocean ◽  
Topographic Effects ◽  
Strong Wind ◽  
Estimation Errors ◽  
Wind Speeds ◽  
Wide Range ◽  
Wind Measurements

AbstractWind measurement offers an essential data source for a wide range of practices in the fields of meteorology and wind engineering. However, records of surface winds are usually influenced by terrain/topographic effects, and direct usage of raw data may bring in nonignorable errors for follow-up applications. A data-driven standardization scheme was recently proposed by the authors to convert the surface wind measurements over rugged terrain into their potential values corresponding to reference conditions, that is, for neutral winds at a height of 10 m above open flat terrain (z0 = 0.03 m). As a complementary part of the preceding work, this study focuses on the standardization of surface wind speeds with marine exposures. The effect of wind strength on the roughness of the sea surface is further taken into account, with emphasis on the difference between deep-ocean and shallow-water cases. As an application example, wind measurements at a buoy site near the coastal line (water depth is 14 m) are adjusted to their potential values, which are then compared with those at a nearby station. The good agreement between the two sets of results demonstrates the accuracy and effectiveness of the standardization method. It is also found that the behavior of roughness length scale over shallow water may differ noticeably from that over deep ocean, especially under strong wind conditions, and an inappropriate usage of marine roughness predictors may result in significant estimation errors.

scholarly journals Assessment of Wind Pattern Accuracy from the QuikSCAT Satellite and the WRF Model along the Galician Coast (Northwest Iberian Peninsula)

2013 ◽  
Vol 141 (2) ◽  
pp. 742-753 ◽  
Author(s):  
M. C. Sousa ◽  
I. Alvarez ◽  
N. Vaz ◽  
M. Gomez-Gesteira ◽  
J. M. Dias
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Western Coast ◽  
Wind Pattern ◽  
Wind Speeds ◽  
Galician Coast ◽  
Key Factor

Abstract Surface wind along the Galician coast is a key factor allowing the analysis of important oceanographic features that are related to the great primary production in this area, as upwelling events. A comparative analysis between surface winds obtained from the Quick Scatterometer (QuikSCAT), the Weather Research and Forecasting (WRF) Model, and in situ observations from buoys along the Galician coast is carried out from November 2008 to October 2009. This comparison evaluates the accuracy of satellite and modeled data. The results show that the wind speeds derived from QuikSCAT and the WRF Model are similar along the coast, with errors ranging from 1.5 to 2 m s−1. However, QuikSCAT tends to overestimate wind speeds when compared to the buoys measurements. Regarding the wind direction, the RMSE values are about 35° for the stations under analysis. The bias presents a similar pattern between satellite and modeled data, with positive values at the western coast and negative values at the middle and northern coasts, the satellite data always being lower in absolute value than the modeled data. A spatial comparison between QuikSCAT and WRF data is also performed over the whole Galician coast to evaluate the differences between the two datasets. This comparison shows that the modeled wind speed tends to be lower than satellite winds over the entire domain, with the highest RMSE and bias values found for the wind speed and direction observed near the shoreline.

scholarly journals Evaluation of Global Reanalysis Land Surface Wind Speed Trends to Support Wind Energy Development Using In Situ Observations

2021 ◽  
Vol 60 (1) ◽  
pp. 33-50
Author(s):  
Wenxin Fan ◽  
Yi Liu ◽  
Adrian Chappell ◽  
Li Dong ◽  
Rongrong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Land Surface ◽  
Turning Point ◽  
Surface Wind ◽  
Energy Resource ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Global Reanalysis

AbstractGlobal reanalysis products are important tools across disciplines to study past meteorological changes and are especially useful for wind energy resource evaluations. Studies of observed wind speed show that land surface wind speed declined globally since the 1960s (known as global terrestrial stilling) but reversed with a turning point around 2010. Whether the declining trend and the turning point have been captured by reanalysis products remains unknown so far. To fill this research gap, a systematic assessment of climatological winds and trends in five reanalysis products (ERA5, ERA-Interim, MERRA-2, JRA-55, and CFSv2) was conducted by comparing gridcell time series of 10-m wind speed with observational data from 1439 in situ meteorological stations for the period 1989–2018. Overall, ERA5 is the closest to the observations according to the evaluation of climatological winds. However, substantial discrepancies were found between observations and simulated wind speeds. No reanalysis product showed similar change to that of the global observations, although some showed regional agreement. This discrepancy between observed and reanalysis land surface wind speed indicates the need for prudence when using reanalysis products for the evaluation and prediction of winds. The possible reasons for the inconsistent wind speed trends between reanalysis products and observations are analyzed. The results show that wind energy production should select different products for different regions to minimize the discrepancy with observations.

scholarly journals IMPROVED FORMULAS FOR ESTIMATING OFFSHORE WINDS

1984 ◽  
Vol 1 (19) ◽  
pp. 149
Author(s):  
S.A. Hsu
Keyword(s):  
Continental Shelf ◽  
Coastal Waters ◽  
Offshore Wind ◽  
Wind Data ◽  
Wind Speeds ◽  
Coastal Marine ◽  
The World ◽  
Wind Measurements ◽  
The U.S

Differences in onshore and offshore wind speeds have long been known to exist [see, e.g., (2), (15), (16)]. Marine meteorologists in the weather services are required to forecast offshore winds. Many studies related to coastal marine sciences and engineering require wind data or estimates for offshore regions. Yet in situ measurements over water are often lacking. Traditionally, wind measurements over land, preferably near coasts, have been used to estimate offshore winds. However, because simultaneous onshore and offshore observations do not always exist, systematic studies such as simple comparisons between these two environments are also lacking. Only recently the U.S. National Oceanic and Atmospheric Administration (NOAA) deployed a network of buoys for longer term measurements over the continental shelf as well as farther offshore. All of these buoys are located in or near U.S. coastal waters. However, there are still vast regions in other parts of the world where such a network does not exist.

scholarly journals The Eyewall-Penetration Reconnaissance Observation of Typhoon Longwang (2005) with Unmanned Aerial Vehicle, Aerosonde

2008 ◽  
Vol 25 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Po-Hsiung Lin ◽  
Cheng-Shang Lee
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Doppler Radar ◽  
Surface Wind ◽  
Wind Retrieval ◽  
Aerial Vehicle ◽  
Wind Measurements ◽  
Wind Profiles ◽  
Outer Perimeter ◽  
Local Weather

Abstract In this paper, a successful eye-penetration reconnaissance flight by an unmanned aerial vehicle, Aerosonde, into Typhoon Longwang (2005) and the preliminary analyses of the collected data are presented. The 10-h flight is diagnosed through four flight legs. The wind field measured along flight leg 1 provides the tangential and radial wind profiles from the outer perimeter into the eye of the typhoon at the 700-hPa layer. A vertical sounding was taken in the eye along flight leg 2 and the derived surface pressure in the eyewall is close to the estimates made by the local weather agencies. Along flight leg 3, the strongest winds during the whole flight mission were measured. These in situ wind measurements by Aerosonde are consistent with the winds observed by the Hua-lien Doppler weather radar. The maximum 10-min (1 min) wind along flight leg 3 when Aerosonde was flying around the eyewall region is 58.6 m s−1 (62 m s−1). The maximum sustained surface wind derived from this maximum wind speed is also close to the estimates made by the local weather agencies. In conclusion, this successful mission demonstrates that the Aerosonde with a trained crew can play a role in severe weather monitoring and the Aerosonde’s measurement can serve as an independent check for Doppler radar wind retrieval.

scholarly journals The Probability Distribution of Sea Surface Wind Speeds. Part I: Theory and SeaWinds Observations

2006 ◽  
Vol 19 (4) ◽  
pp. 497-520 ◽  
Author(s):  
Adam Hugh Monahan
Keyword(s):  
Standard Deviation ◽  
Probability Density Function ◽  
Probability Distribution ◽  
Probability Density ◽  
Density Function ◽  
Surface Wind ◽  
Sea Surface ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
The Mean

Abstract The probability distribution of sea surface wind speeds, w, is considered. Daily SeaWinds scatterometer observations are used for the characterization of the moments of sea surface winds on a global scale. These observations confirm the results of earlier studies, which found that the two-parameter Weibull distribution provides a good (but not perfect) approximation to the probability density function of w. In particular, the observed and Weibull probability distributions share the feature that the skewness of w is a concave upward function of the ratio of the mean of w to its standard deviation. The skewness of w is positive where the ratio is relatively small (such as over the extratropical Northern Hemisphere), the skewness is close to zero where the ratio is intermediate (such as the Southern Ocean), and the skewness is negative where the ratio is relatively large (such as the equatorward flank of the subtropical highs). An analytic expression for the probability density function of w, derived from a simple stochastic model of the atmospheric boundary layer, is shown to be in good qualitative agreement with the observed relationships between the moments of w. Empirical expressions for the probability distribution of w in terms of the mean and standard deviation of the vector wind are derived using Gram–Charlier expansions of the joint distribution of the sea surface wind vector components. The significance of these distributions for improvements to calculations of averaged air–sea fluxes in diagnostic and modeling studies is discussed.

scholarly journals SST-Induced Surface Wind Variations over the Brazil–Malvinas Confluence: Satellite and In Situ Observations*

2005 ◽  
Vol 18 (17) ◽  
pp. 3470-3482 ◽  
Author(s):  
Hiroki Tokinaga ◽  
Youichi Tanimoto ◽  
Shang-Ping Xie
Keyword(s):  
Boundary Layer ◽  
Surface Wind ◽  
Vertical Mixing ◽  
Near Surface ◽  
Surface Stability ◽  
Wind Speeds ◽  
The North ◽  
Weak Surface ◽  
Divergence Pattern

Abstract The confluence of the Brazil–Malvinas Currents maintains strong sea surface temperature (SST) fronts in the midlatitude southwestern Atlantic year-round. SST effects on near-surface stability and surface wind variations are examined in this region using satellite and in situ datasets. Satellite observations show strong (weak) surface wind speeds over the warm Brazil (cold Malvinas) Current. A novel feature of this study is the construction of a high-resolution surface meteorological dataset that is based on historical ship observations. Analysis of this new in situ dataset reveals an increased (reduced) sea–air temperature difference over the Brazil (Malvinas) Current, indicating destabilization (stabilization) in the atmospheric boundary layer. These results are consistent with the SST-induced vertical mixing mechanism for wind adjustment. The SST effect on the near-surface atmosphere is observed both in the climatology and on interannual time scales in the Brazil–Malvinas confluence. Along a zonal SST front at 49°S northeast of the Malvinas/Falkland Islands, there is a collocated line of surface wind divergence, with moderate convergence to the north. Vertical mixing does not explain this divergence pattern because the prevailing surface winds are westerly, blowing in parallel with the front. An additional mechanism is proposed for boundary layer wind adjustment.

Near-Surface Eddy Heat and Momentum Fluxes in the Antarctic Circumpolar Current in Drake Passage

2011 ◽  
Vol 41 (7) ◽  
pp. 1385-1407 ◽  
Author(s):  
Yueng-Djern Lenn ◽  
Teresa K. Chereskin ◽  
Janet Sprintall ◽  
Julie L. McClean
Keyword(s):  
Antarctic Circumpolar Current ◽  
Surface Wind ◽  
Drake Passage ◽  
Heat Fluxes ◽  
Momentum Balance ◽  
Secondary Importance ◽  
Near Surface ◽  
Momentum Fluxes ◽  
The Mean ◽  
Circumpolar Current

Abstract The authors present new estimates of the eddy momentum and heat fluxes from repeated high-resolution upper-ocean velocity and temperature observations in Drake Passage and interpret their role in the regional Antarctic Circumpolar Current (ACC) momentum balance. The observations span 7 yr and are compared to eddy fluxes estimated from a 3-yr set of output archived from an eddy-resolving global Parallel Ocean Program (POP) numerical simulation. In both POP and the observations, the stream-averaged cross-stream eddy momentum fluxes correspond to forcing consistent with both a potential vorticity flux into the axis of the Subantarctic Front (SAF) and a sharpening of all three main ACC fronts through Drake Passage. Further, the POP analysis indicates that the mean momentum advection terms reflect the steering of the mean ACC fronts and are not fully balanced by the eddy momentum forcing, which instead impacts the strength and number of ACC fronts. The comparison between POP and observed eddy heat fluxes was less favorable partly because of model bias in the water mass stratification. Observed cross-stream eddy heat fluxes are generally surface intensified and poleward in the ACC fronts, with values up to approximately −290 ± 80 kW m−2 in the Polar and Southern ACC Fronts. Interfacial form stresses FT, derived from observed eddy heat fluxes in the SAF, show little depth dependence below the Ekman layer. Although FT appears to balance the surface wind stress directly, the estimated interfacial form stress divergence is only an order of magnitude greater than the eddy momentum forcing in the SAF. Thus, although the eddy momentum forcing is of secondary importance in the momentum balance, its effect is not entirely negligible.

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