Numerical Study on the Wind Drag Stress in Storm Surge

2007 ◽  
Author(s):  
Jun Kong ◽  
Zhiyao Song
Keyword(s):  
Free Surface ◽  
Wind Speed ◽  
Storm Surge ◽  
Wind Stress ◽  
Yangtze Estuary ◽  
Tidal Range ◽  
Small Range ◽  
Tidal Level ◽  
Typhoon Season ◽  
Relative Wind

In estuary and coastal areas the storm surge will usually occur in typhoon season. When simulating the storm surge by numerical model, the wind speed at the height of 10m above the mean sea level will be usually used. Determining the wind drag stress on free surface reasonably plays an important role to simulate the storm surge accurately. In the past numerical models, the wind drag stress on free surface was calculated only considering the relative wind speed. There are many formulas about wind stress can be used, whereas these formulas are usually got in laboratory, where the water surface fluctuates in a small range, and the water elevation itself has not been considered in formula. Actually in some place, the astronomical tidal range is large, such as Yangtze estuary and Hangzhou bay in China, and during typhoon season, the water fluctuation range is much larger than ever there. In conventional method the wind stress will be underestimate in flood tide and be over-valuated in ebb tide without considering the fluctuation of water, so it is obviously unsuitable to take no account of the influence of tidal level on wind stress. Therefore in the intensive tide coastal area, the relationship of the relative wind speed, tidal level should be considered together. A new kind of wind stress formula has been established in this paper and been adopted in simulating the storm surge of typhoon Winnie in Yangtze estuary, and the results are better and satisfying.

scholarly journals Spatial Relation between Wind Stress and Storm Surge during Hurricanes Laura and Delta in 2020

2021 ◽  
Vol 02 (03) ◽  
pp. 1-1
Author(s):  
Shih-Ang Hsu ◽  
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Water Level ◽  
Storm Surge ◽  
Surface Analysis ◽  
Wind Stress ◽  
Spatial Relation ◽  
High Water ◽  
Mesoscale Meteorology ◽  
First Approximation

Spatial relation between wind stress and storm surge during two hurricanes in 2020 is investigated. It is found that, during Laura’s landfall, the area inside of 65 knots (34 m s -1) isotach or line of equal wind speed can produce up to 18 ft (5.5 m) inundation and during Delta, the area inside of 50 knots (26 m s -1) up to 11 ft (3.3 m) high water level above the ground. The tropical cyclone (TC) surface analysis near landfall by the Regional and Mesoscale Meteorology Branch (RAMMB) is recommended as a first approximation for coastal environmental and engineering applications during a TC.

EFFECTS OF MAXIMUM WIND SPEED RADIUS AND TRANSLATION SPEED OF SCENARIO TYPHOON ON STORM SURGE AND WAVE

2018 ◽  
Vol 74 (2) ◽  
pp. I_583-I_588
Author(s):  
Masafumi KIMIZUKA ◽  
Tomotsuka TAKAYAMA ◽  
Hiroyasu KAWAI ◽  
Masafumi MIYATA ◽  
Katsuya HIRAYAMA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Maximum Wind Speed ◽  
Translation Speed ◽  
Maximum Wind

scholarly journals Adjusting the Wind Stress Drag Coefficient in Storm Surge Forecasting Using an Adjoint Technique

2013 ◽  
Vol 30 (3) ◽  
pp. 590-608 ◽  
Author(s):  
Shiqiu Peng ◽  
Yineng Li ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Drag Coefficient ◽  
Storm Surge ◽  
Wind Stress ◽  
Weather Prediction ◽  
Ocean Model ◽  
Error Sources ◽  
Empirical Parameter ◽  
Forecasting Errors ◽  
Storm Surge Forecasting

Abstract A three-dimensional ocean model and its adjoint model are used to adjust the drag coefficient in the calculation of wind stress for storm surge forecasting. A number of identical twin experiments (ITEs) with different error sources imposed are designed and performed. The results indicate that when the errors come from the wind speed, the drag coefficient is adjusted to an “optimal value” to compensate for the wind errors, resulting in significant improvements of the specific storm surge forecasting. In practice, the “true” drag coefficient is unknown and the wind field, which is usually calculated by an empirical parameter model or a numerical weather prediction model, may contain large errors. In addition, forecasting errors may also come from imperfect model physics and numerics, such as insufficient resolution and inaccurate physical parameterizations. The results demonstrate that storm surge forecasting errors can be reduced through data assimilation by adjusting the drag coefficient regardless of the error sources. Therefore, although data assimilation may not fix model imperfection, it is effective in improving storm surge forecasting by adjusting the wind stress drag coefficient using the adjoint technique.

The Importance of Relative Wind Speed in Estimating Air–Sea Turbulent Heat Fluxes in Bulk Formulas: Examples in the Bohai Sea

2020 ◽  
Vol 37 (4) ◽  
pp. 589-603 ◽  
Author(s):  
Xiangzhou Song
Keyword(s):  
Boundary Layer ◽  
Heat Flux ◽  
Wind Speed ◽  
Bohai Sea ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Surface Currents ◽  
The Bohai Sea ◽  
Turbulent Heat Fluxes ◽  
Relative Wind

AbstractSea surface currents are commonly neglected when estimating the air–sea turbulent heat fluxes in bulk formulas. Using buoy observations in the Bohai Sea, this paper investigated the effects of near-coast multiscale currents on the quantification of turbulent heat fluxes, namely, latent heat flux (LH) and sensible heat flux (SH). The maximum current reached 1 m s−1 in magnitude, and a steady northeastward current of 0.16 m s−1 appeared in the southern Bohai Strait. The predominant tidal signal was the semidiurnal current, followed by diurnal components. The mean absolute surface wind was from the northeast with a speed of approximately 3 m s−1. The surface winds at a height of 11 m were dominated by the East Asian monsoon. As a result of upwind flow, the monthly mean differences in LH and SH between the estimates with and without surface currents ranged from 1 to 2 W m−2 in July (stable boundary layer) and November (unstable boundary layer). The hourly differences were on average 10 W m−2 and ranged from 0 to 24 W m−2 due to changes in the relative wind speed by high-frequency rotating surface tidal currents. The diurnal variability in LH/SH was demonstrated under stable and unstable boundary conditions. Observations provided an accurate benchmark for flux comparisons. The newly updated atmospheric reanalysis products MERRA-2 and ERA5 were superior to the 1° OAFlux data at this buoy location. However, future efforts in heat flux computation are still needed to, for example, consider surface currents and resolve diurnal variations.

CFD Study on Free-Surface Influence on Tidal Turbines in Hydraulic Structures

2015 ◽  
Author(s):  
Aldo Tralli ◽  
Arnout C. Bijlsma ◽  
Wilbert te Velde ◽  
Pieter de Haas
Keyword(s):  
Free Surface ◽  
Storm Surge ◽  
Field Measurements ◽  
Hydraulic Structures ◽  
Generic Structure ◽  
Tidal Turbines ◽  
Computational Fluid Dynamics Cfd ◽  
The Impact ◽  
Method Model ◽  
Blade Element

In order to estimate the impact on energy production and environment of tidal turbines placed in or near hydraulic structures like discharge sluices or storm surge barriers, a Computational Fluid Dynamics (CFD) study has been carried out on the relation between (head) loss induced by the turbines and their gross power production. CFD computations have been performed for Tocardo T2 turbines, using STAR-CCM+. Simulations of a single turbine in free flow conditions compare favorably with results of Blade Element Momentum (BEM) computations, in terms of torque and thrust. This BEM method model had been previously validated against both CFD data and field measurements. Then, a series of tests has been performed in a “virtual tow tank”, including the effect of the free surface and the blockage by side and bottom walls. These computations provide a base for a first estimate of the effect of turbines on the discharge capacity of a generic structure. This is considered to be the first step in a more general approach in which ultimately the effect of tidal turbines in the Eastern Scheldt Storm Surge Barrier will be assessed.

Effect of the Wind Drag Estimation Methods on Numerical Storm Surge Modeling

2019 ◽  
Author(s):  
C. Gowri Shankar ◽  
Manasa Ranjan Behera
Keyword(s):  
Real Time ◽  
Storm Surge ◽  
Wind Stress ◽  
Evaluation Method ◽  
Tide Gauge ◽  
Wave Model ◽  
Estimation Methods ◽  
Computational Accuracy ◽  
In Situ Data

Abstract Tropical cyclones have always proved the extent of its catastrophe on several occurrences over the years. In particular, the Bay of Bengal (BoB) basin in the Northern Indian Ocean has produced such historic devastating events, thereby mandating accurate real-time predictions. Numerical modeling of storm surge has always been an arduous task, as it is integrated with various uncertain factors. Among those, the major governing component being the wind forcing or the wind stress — that signifies, the computational accuracy of simulated surge and wave parameters. The present study is aimed at analysing the most suited wind drag evaluation method for real-time predictions of storm surge along the BoB. Cyclone Phailin (2013) was considered for the numerical simulations. To evaluate the wind drag coefficient, three most extensively used linear empirical relations along with the enhanced Wave Boundary Layer Model (e_WBLM) were used. The surge was subsequently simulated (using the coupled hydrodynamic circulation and wave model: ADCIRC and SWAN, respectively), individually for each of the above wind stress methods to obtain the corresponding storm surge (residual) and the storm wave features. The modeled values were further validated with the in-situ data obtained from tide gauge station and buoys respectively. It was quite intuitively observed that, e_WBLM based results correlated well with the in-situ values than its linear counterparts since, the former pragmatically includes the effects of air-sea interaction at high wind speeds in the model. The e_WBLM-based computation of significant wave heights (Hs) in deep as well as shallow water, nevertheless enabled efficient and reasonably-reliable estimations of the peak incidents.

Spray Application Efficiency from a Multi-Rotor Unmanned Aerial Vehicle Configured for Aerial Pesticide Application

2019 ◽  
Vol 62 (6) ◽  
pp. 1447-1453 ◽  
Author(s):  
Brian Richardson ◽  
Carol A. Rolando ◽  
Mark O. Kimberley ◽  
Tara M. Strand
Keyword(s):  
Wind Speed ◽  
Unmanned Aerial Vehicle ◽  
Droplet Size ◽  
Small Range ◽  
Surprising Result ◽  
Spray Application ◽  
Size Classes ◽  
Fine Droplet ◽  
Application Efficiency ◽  
Aerial Vehicle

HighlightsThe swath pattern was measured from an Agras MG-1 UAV spraying fine and extra-coarse droplet spectra.The recommended lane separation of 3.6 m did not differ for the two droplet size classes tested in this study.The applied spray deposited within the swath was higher with extra-coarse (>90%) than with fine (73%) droplets.There was potential for substantial downwind drift with fine droplets, even when flying close to the ground at low speed.Abstract. While there is increasing interest in the use of small, multi-rotor UAVs for application of agrichemicals, there is also uncertainty about their performance. Consequently, the purpose of this study was to quantify the performance of an Agras MG-1 with modified nozzle positions that, at the time of writing, was being used for commercial spraying in New Zealand. The approach was to release spray from the UAV along a single 50 m line. Spray deposits were measured using horizontal collectors placed on the ground in three 15 m transects centered on, and perpendicular to, the flight line. Airborne deposits were measured with a 10 m mast that supported spherical samplers at 1 m vertical intervals. Analysis of deposition data was undertaken to quantify factors influencing overall swath pattern variability, lane separation associated with a coefficient of variation (CV) of deposition of 30%, and spray application efficiency, which is the proportion of applied spray deposited within the swath. For two droplet size classes (extra-coarse and fine), the lane separation associated with a CV of 30% was about 3.6 m, with no significant effect of droplet size. This is a surprising result and may reflect the relatively small range of environmental conditions experienced during the field tests, including wind speed, which was relatively low for all tests. We speculate that this result may also be a consequence of the strong downwash. The swath width was positively correlated with wind speed. Spray efficiency was shown to be high (>90%) for the extra-coarse droplets but dropped significantly (73%) with the fine droplet spectrum. Combining in-swath deposition with the amount of airborne spray sampled in a 10 m vertical profile close to the edge of the swath accounted for 98.0% of the spray released with the extra-coarse spectrum but only 88.6% of the spray with the fine droplet spectrum. These results highlight that even with UAVs flying relatively close to the ground at a low forward speed, there is potential for substantial drift downwind of the swath when using smaller droplet size classes. Overall, the swath pattern was reasonably consistent across the two droplet size classes and for the narrow range of operational and meteorological conditions tested. Keywords: Aerial spraying, Pesticides, Spray application efficiency, Spray deposition, Swath pattern, UAV, Unmanned aerial vehicle.

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