The near-surface wind field over the Antarctic continent

2004 ◽  
Vol 24 (15) ◽  
pp. 1973-1982 ◽  
Author(s):  
N. P. M. van Lipzig ◽  
J. Turner ◽  
S. R. Colwell ◽  
M. R. van Den Broeke
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Near Surface ◽  
Antarctic Continent ◽  
The Antarctic ◽  
Surface Wind Field

The Effects of Vertical Stratification and Land Use Data on Numerical Simulation of Wind Energy Resources

2014 ◽  
Vol 535 ◽  
pp. 135-140
Author(s):  
Yuan Chang Deng ◽  
Zhen Cao Zou
Keyword(s):  
Numerical Simulation ◽  
Land Use ◽  
Wind Field ◽  
Wind Profile ◽  
Surface Wind ◽  
Wrf Model ◽  
Vertical Stratification ◽  
Near Surface ◽  
Wind Field Simulation ◽  
Surface Wind Field

By adjusting the distribution of vertical layers and increasing its number in WRF model, this paper mainly studies the effects of vertical stratification on the near surface wind field and vertical profile simulation. The test outcomes show that moderately increasing vertical layers can effectively improve the near surface wind field simulation results, while it has little influence on the numeral and changing trend of high vertical wind profile. Considering both accuracy and efficiency, it is recommended to set 10~15 layers below 300m. On the basis of this research, instead of USGS data by using the MODIS_30S data, the data underlying surface land in Shenzhen and HK area are updated. Comparative results between the two schemes, due to the roughness and drag coefficient of difference types of surface are not identical; the surface data has a significant impact on wind field and wind profile simulation. Using the MODIS land use data which is more consistent with the actual situation can improve the accuracy of numerical simulation.

scholarly journals Reconstruction of Near-Surface Tornado Wind Fields from Forest Damage

2010 ◽  
Vol 49 (7) ◽  
pp. 1517-1537 ◽  
Author(s):  
Veronika Beck ◽  
Nikolai Dotzek
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Forest Damage ◽  
Wind Fields ◽  
Tree Model ◽  
Translation Speed ◽  
Near Surface ◽  
Additional Information ◽  
Secondary Vortices ◽  
Surface Wind Field

Abstract Tornado intensity is usually inferred from the damage produced. To foster postevent tornado intensity assessments, the authors present a model to reconstruct near-surface wind fields from forest damage patterns. By comparing the structure of observed and simulated damage patterns, essential parameters to describe a tornado near-surface wind field are derived, such as the ratio Gmax between circular and translational velocity, and the deflection angle α between peak wind and pressure gradient. The model consists of a wind field module following the Letzmann analytical tornado model and a tree module based on the mechanistic HWIND tree model to assess tree breakage. Using this method, the velocity components of the near-surface wind field, the track of the tornado center, and the spatial distribution of the Fujita scale along and across the damage path can be assessed. Necessary requirements to apply the model are knowledge of the tornado translation speed (e.g., from radar observations) and a detailed analysis of the forest damage patterns. One of the key findings of this analysis is that the maximum intensity of the tornado is determinable with an uncertainty of only (Gmax + 1) times the variability of the usually well-known tornado translation speed. Further, if Letzmann’s model is applied and the translation speed of the tornado is known, the detailed tree model is unnecessary and could be replaced by an average critical velocity for stem breakage υcrit independent of the tree species. Under this framework, the F3 and F2 ratings of the tornadoes in Milosovice, Czech Republic, on 30 May 2001 and Castellcir, Spain, on 18 October 2006, respectively, could be verified. For the Milosovice event, the uncertainty in peak intensity was only ±6.0 m s−1. Additional information about the structure of the near-surface wind field in the tornado and several secondary vortices was also gained. Further, this model allows for distinguishing downburst damage patterns from those of tornadoes.

scholarly journals Wind field reconstruction with adaptive random Fourier features

2021 ◽  
Vol 477 (2255) ◽  
Author(s):  
Jonas Kiessling ◽  
Emanuel Ström ◽  
Raúl Tempone
Keyword(s):  
Wind Field ◽  
Spatial Interpolation ◽  
Surface Wind ◽  
Sobolev Norm ◽  
Near Surface ◽  
Distance Weighting ◽  
Random Fourier Features ◽  
Sparse Set ◽  
Surface Wind Field ◽  
Inverse Distance

We investigate the use of spatial interpolation methods for reconstructing the horizontal near-surface wind field given a sparse set of measurements. In particular, random Fourier features is compared with a set of benchmark methods including kriging and inverse distance weighting. Random Fourier features is a linear model β ( x ) = ∑ k = 1 K β k   e i ω k x approximating the velocity field, with randomly sampled frequencies ω k and amplitudes β k trained to minimize a loss function. We include a physically motivated divergence penalty | ∇ ⋅ β ( x ) | 2 , as well as a penalty on the Sobolev norm of β . We derive a bound on the generalization error and a sampling density that minimizes the bound. We then devise an adaptive Metropolis–Hastings algorithm for sampling the frequencies of the optimal distribution. In our experiments, our random Fourier features model outperforms the benchmark models.

scholarly journals Factors Controlling the Near-Surface Wind Field in Antarctica*

2003 ◽  
Vol 131 (4) ◽  
pp. 733-743 ◽  
Author(s):  
M. R. van den Broeke ◽  
N. P. M. van Lipzig
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Near Surface ◽  
Surface Wind Field

scholarly journals ESTIMATING NEAR-SURFACE WIND FIELD BY AERIAL THERMAL IMAGE VELOCIMETRY

2017 ◽  
Vol 73 (4) ◽  
pp. I_457-I_462
Author(s):  
Motoyuki HIJIKATA ◽  
Atsushi INAGAKI ◽  
Manabu KANDA ◽  
Yukihiko YAMASHITA
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Thermal Image ◽  
Near Surface ◽  
Image Velocimetry ◽  
Surface Wind Field

scholarly journals An Observational Study of Hurricane Boundary Layer Small-Scale Coherent Structures

2008 ◽  
Vol 136 (8) ◽  
pp. 2871-2893 ◽  
Author(s):  
Sylvie Lorsolo ◽  
John L. Schroeder ◽  
Peter Dodge ◽  
Frank Marks
Keyword(s):  
Boundary Layer ◽  
Observational Study ◽  
Wind Field ◽  
Relative Frequency ◽  
Surface Wind ◽  
High Energy ◽  
Small Scale ◽  
Near Surface ◽  
Hurricane Boundary Layer ◽  
Surface Wind Field

Abstract Data with high temporal and spatial resolution from Hurricanes Isabel (2003) and Frances (2004) were analyzed to provide a detailed study of near-surface linear structures with subkilometer wavelengths of the hurricane boundary layer (HBL). The analysis showed that the features were omnipresent throughout the data collection, displayed a horizontal and vertical coherency, and maintained an average orientation of 7° left of the low-level wind. A unique objective wavelength analysis was conducted, where wavelength was defined as the distance between two wind maxima or minima perpendicular to the features’ long axis, and revealed that although wavelengths as large as 1400 m were observed, the majority of the features had wavelengths between 200 and 650 m. The assessed wavelengths differ from those documented in a recent observational study. To evaluate the correlation between the features and the underlying near-surface wind field, time and spectral analyses were completed and ground-relative frequency distributions of the features were retrieved. High-energy regions of the power spectral density (PSD) determined from near-surface data were collocated with the features’ ground-relative frequency, illustrating that the features have an influence on the near-surface wind field. The additional energy found in the low-frequency range of the PSDs was previously identified as characteristic of the hurricane surface flow, suggesting that the features are an integral component of the HBL flow.

Sign in / Sign up

Export Citation Format

Share Document