scholarly journals Features of X-Band Radar Backscattering Simulation Based on the Ocean Environmental Parameters in China Offshore Seas

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2450 ◽  
Author(s):  
Tao Wu ◽  
Zhensen Wu ◽  
Jiaji Wu ◽  
Gwanggil Jeon ◽  
Liwen Ma
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Spectrum ◽  
Environmental Parameters ◽  
Reanalysis Data ◽  
Practical Significance ◽  
Scale Model ◽  
Wind Speeds ◽  
Wave Parameters ◽  
X Band

The X-band marine radar has been employed as a remote sensing tool for sea state monitoring. However, there are few literatures about sea spectra considering both the wave parameters and short wind-wave spectra in China Offshore Seas, which are of theoretical and practical significance. Based on the wave parameters acquired from the European Centre for Medium-Range Weather Forecasts reanalysis data (ERA-Interim reanalysis data) during 36 months from 2015 to 2017, a finite depth sea spectrum considering both wind speeds and ocean environmental parameters is established in this study. The wave spectrum is then built into a modified two-scale model, which can be related to the ocean environmental parameters (wind speeds and wave parameters). The final results are the mean backscattering coefficients over the variety of sea states at a given wind speed. As the model predicts, the monthly maximum backscattering coefficients in different seas change slowly (within 4 dB). In addition, the differences of the backscattering coefficients in different seas are quite small during azimuthal angles of 0° to 90° and 270° to 360° with a relative error within 1.5 dB at low wind speed (5 m/s) and 2 dB at high wind speed (10 m/s). With the method in the paper, a corrected result from the experiment can be achieved based on the relative error analysis in different conditions.

scholarly journals Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery

2017 ◽  
Vol 11 (2) ◽  
pp. 755-771 ◽  
Author(s):  
Ane S. Fors ◽  
Dmitry V. Divine ◽  
Anthony P. Doulgeris ◽  
Angelika H. H. Renner ◽  
Sebastian Gerland
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
First Year ◽  
Backscatter Signal ◽  
Noise Floor ◽  
Ice Melt ◽  
Wind Speeds ◽  
Melt Pond ◽  
Melt Ponds ◽  
X Band

Abstract. In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Co-polarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6. 2 m s−1), with a Spearman's correlation coefficient of 0. 46. At low wind speeds (0. 6 m s−1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of −0. 53. To further investigate these relations, regression fits were made both for the intermediate (R2fit = 0. 21) and low (R2fit = 0. 26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51 × 51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above  ∼  40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future.

scholarly journals History and Data Records of the Automatic Weather Station on Denali Pass (5715 m), 1990–2007

2020 ◽  
Vol 59 (12) ◽  
pp. 2113-2127
Author(s):  
Lea Hartl ◽  
Martin Stuefer ◽  
Tohru Saito ◽  
Yoshitomi Okura
Keyword(s):  
Wind Speed ◽  
Historical Record ◽  
Reanalysis Data ◽  
Meteorological Conditions ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Wind Speeds ◽  
Air Temperatures ◽  
History Of ◽  
Summit Region

AbstractWe present the data records and station history of an automatic weather station (AWS) on Denali Pass (5715 m MSL), Alaska. The station was installed by a team of climbers from the Japanese Alpine Club after a fatal accident involving Japanese climbers in 1989 and was operational intermittently between 1990 and 2007, measuring primarily air temperature and wind speed. In later years, the AWS was operated by the International Arctic Research Center of the University of Alaska Fairbanks. Station history is reconstructed from available documentation as archived by the expedition teams. To extract and preserve data records, the original datalogger files were processed. We highlight numerous challenges and sources of uncertainty resulting from the location of the station and the circumstances of its operation. The data records exemplify the harsh meteorological conditions at the site: air temperatures down to approximately −60°C were recorded, and wind speeds reached values in excess of 60 m s−1. Measured temperatures correlate strongly with reanalysis data at the 500-hPa level. An approximation of critical wind speed thresholds and a reanalysis-based reconstruction of the meteorological conditions during the 1989 accident confirm that the climbers faced extremely hazardous wind speeds and very low temperatures. The data from the Denali Pass AWS represent a unique historical record that can, we hope, serve as a basis for further monitoring efforts in the summit region of Denali.

scholarly journals The Potential Wind Power Resource in Central-South of the Constanta County

2019 ◽  
Vol 15 (3) ◽  
pp. 1-12
Author(s):  
Emilian Boboc
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Extreme Values ◽  
Reanalysis Data ◽  
Value Theory ◽  
Physical Models ◽  
Structural Safety ◽  
Energy Yield ◽  
Wind Speeds ◽  
Mean Wind Speed

Abstract Usually, wind turbine generator’s structures or radio masts are located in wind exposed sites. The paper aims to investigate the wind conditions in the nearby area of Cobadin Commune, Constanta County, Romania at heights of 150-200m above the surface using global reanalysis data sets CFSR, ERA 5, ERA I and MERRA 2. Using the extreme value theory and the physical models of the datasets, the research focuses on the assessment of the maximum values that are expected for the wind speeds, but the wind statistics created can be used for a further wind or energy yield calculation. Without reaching the survival wind speed for wind turbine generators, with mean wind speed values higher than 7 m/s and considering the cut-in and cut-out wind speeds of 3 m/s, respectively 25 m/s, the site can be exploited in more than 90% of the time to generate electricity, thus, the paper is addressed to the investors in the energy of renewable sources. At the same time, the insights of the wind characteristics and the knowledge of the extreme values of the wind speed can be useful, not just for the designers, in the rational assessment of the structural safety of wind turbines, but also those evaluating the insured losses.

scholarly journals Spatiotemporal Dynamics of Maximum Wind Speed Using the Wind Multiplier Downscaling Method in the Yangtze River Inland Waterway from 1980 to 2017

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1216
Author(s):  
Lijun Liu ◽  
Fan Zhang
Keyword(s):  
Land Use ◽  
Wind Speed ◽  
Significant Influence ◽  
Yangtze River ◽  
Reanalysis Data ◽  
Spatiotemporal Dynamics ◽  
The Yangtze River ◽  
Maximum Wind ◽  
Wind Speeds ◽  
Inland Waterway

Wind speed affects the navigational safety of the Yangtze River, and assessing its spatiotemporal dynamics provides support for navigation management and disaster prevention. We developed a wind multiplier downscaling method integrating the effects of land use and topography, and used meteorological station observations and European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-Interim) reanalysis data for statistical downscaling in the Yangtze River inland waterway region from 1980 to 2017. Compared with reanalysis data, the downscaling products showed improved accuracy (especially at 5–10 m/s), and are consistent with site-based interannual variability observations. Increasing maximum wind speeds in the middle–downstream area was observed from 1980 to 1990, while a decreasing trend was observed from 2010 to 2017; the opposite was observed for the upstream. Land use has significant influence on wind speed, with a decreasing trend observed year by year for wind speed above grade 9. Although the proportion of grade 4–8 wind speed over water is small and the trend is not obvious, grade 9–10 wind speeds displayed an increasing trend from 2010 to 2017, indicating that changes in surface roughness have a significant influence on wind speed in the Yangtze River inland waterway.

accuracy of wind measurements on towers or stacks1,2

1967 ◽  
Vol 48 (9) ◽  
pp. 665-675 ◽  
Author(s):  
Gerald C. Gill ◽  
Lars E. Olsson ◽  
Josef Sela ◽  
Motozo Suda
Keyword(s):  
Wind Speed ◽  
Scale Model ◽  
Wind Speeds ◽  
Lattice Type ◽  
Free Air ◽  
Scale Models ◽  
The Face ◽  
Wind Measurements ◽  
Wind Tunnel Data ◽  
Undisturbed Flow

Wind sensors mounted on towers and smokestacks do not always indicate the true free-air flow. To determine the probable errors in measurements of wind speed and direction around such structures, quarter-scale models have been tested in a large wind tunnel. Data on changes in wind speed and direction were obtained by using smoke, very small wind vanes, and a scale model propeller anemometer. Most emphasis has been placed on a relatively open lattice-type tower, but a solid tower and a stack were also studied. The analysis shows that in the wake of lattice-type towers disturbance is moderate to severe, and that in the wake of solid towers and stacks there is extreme turbulence, with reversal of flow. Recommendations for locating wind sensors in the wind field relative to the supporting structure are given for each of the three structures studied. Guidelines are suggested regarding probable errors in measurements of wind speed and direction around different supporting structures, as outlined below. For an open triangular tower with equal sides D, the wake is about 1-1/2D in width for a distance downwind of at least 6D. Sensors mounted 2 D out from the corner of such a tower will usually measure speeds within ± 10° of that of the undisturbed flow for an arc of about 330°. The disturbance by very dense towers and stacks is much greater. Wind sensors mounted 3 diameters out from the face of a stack will measure wind speeds within ± 10%, and directions within ± 10° of the undisturbed flow for an arc of about 180°.

scholarly journals Accuracy Comparison of Coastal Wind Speeds between WRF Simulations Using Different Input Datasets in Japan

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2754 ◽  
Author(s):  
Takeshi Misaki ◽  
Teruo Ohsawa ◽  
Mizuki Konagaya ◽  
Susumu Shimada ◽  
Yuko Takeyama ◽  
...  
Keyword(s):  
Wind Speed ◽  
Input Data ◽  
Dynamical Downscaling ◽  
Mesoscale Model ◽  
Grid Point ◽  
Japan Meteorological Agency ◽  
Scale Model ◽  
The Sea Of Japan ◽  
Wind Speeds ◽  
Lidar Measurements

In order to improve the accuracy of the wind speed simulated by a mesoscale model for the wind resource assessment in coastal areas, this study evaluated the effectiveness of using the Japan Meteorological Agency (JMA)’s latest and finest (2 km × 2 km) grid point value (GPV) data, produced from the local forecast model (LFM) as input data to the mesoscale model. The evaluation was performed using wind lidar measurements at two sites located on the coasts of the Sea of Japan and Pacific Ocean. The accuracy of the LFM–GPV was first compared with that of two products from the JMA Meso Scale Model (MSM) (5 km × 5 km): MSM-GPV and mesoscale analysis (MANAL). Consequently, it was shown that LFM–GPV exhibited the most accurate wind speeds against lidar measurements. Next, dynamical downscaling simulations were performed using the weather research and forecasting model (WRF) forced by the three datasets above, and their results were compared. As compared to the GPVs, it was found that the WRF dynamical downscaling simulation using them as input can improve the accuracy of the coastal wind speeds. This was attributed to the advantage of the WRF simulation to improve the negative bias from the input data, especially for the winds blowing from the sea sectors. It was also found that even if the LFM–GPV is used as an input to the WRF simulation, it does not always reproduce more accurate wind speeds, as compared to the simulations using the other two datasets. This result is partly owing to the tendency of WRF to overestimate the wind speed over land, thus obscuring the higher accuracy of the LFM–GPV. It was also shown that the overestimation tendency cannot be improved by only changing the nudging methods or the planetary boundary layer schemes in WRF. These results indicate that it may be difficult to utilize the LFM–GPV in the WRF wind simulation, unless the overestimation tendency of WRF itself is improved first.

scholarly journals Visibility during Blowing Snow Events over Arctic Sea Ice

2008 ◽  
Vol 23 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Qiang Huang ◽  
John Hanesiak ◽  
Sergiy Savelyev ◽  
Tim Papakyriakou ◽  
Peter A. Taylor
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Relative Error ◽  
Arctic Sea Ice ◽  
Regression Equations ◽  
Blowing Snow ◽  
Wind Speeds ◽  
Mean Relative Error ◽  
Drifting Snow ◽  
Strong Relation

Abstract A field study on visibility during Arctic blowing snow events over sea ice in Franklin Bay, Northwest Territories, Canada, was carried out from mid-January to early April 2004 during the Canadian Arctic Shelf Exchange Study (CASES) 2003–04 expedition. Visibilities at two heights, wind and temperature profiles, plus blowing and drifting snow particle flux at several heights were monitored continually during the study period. Good relations between visibility and wind speed were found in individual events of ground blowing snow with coefficients of determination >0.9. Regression equations relating 1.5-m height visibility to 10-m wind speed can be used for predicting visibility with a mean relative error in the range of 19%–32%. Similar regression functions obtained from the data for observed visibility of less than 1 km could predict visibilities more accurately for more extreme visibility reductions and wind speeds (>9.5 m s−1) with mean relative error ranging from 15% to 26%. For the event of ground blowing snow, a simple power law relationship between wind speed and visibility is sufficient for operational purposes. A poorer relationship was observed in the event of blowing snow with concurrent precipitating snow. A theoretical visibility model developed by Pomeroy and Male fit well with observed visibilities if using a mean radius of 50 μm and an alpha value of 10. The predicted visibility had a mean relative error of 30.5% and root-mean-square error of 1.3 km. The observed visibility at 1.5 m had a strong relation with particle counter readings, with an R2 of 0.92, and was consistent among all events.

scholarly journals Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements

2020 ◽  
Vol 13 (6) ◽  
pp. 3487-3506
Author(s):  
Sebastian Landwehr ◽  
Iris Thurnherr ◽  
Nicolas Cassar ◽  
Martin Gysel-Beer ◽  
Julia Schmale
Keyword(s):  
Wind Speed ◽  
Computational Fluid Dynamic ◽  
Wind Direction ◽  
Fluid Dynamic ◽  
Reanalysis Data ◽  
Correction Factors ◽  
Flow Distortion ◽  
Near Surface ◽  
Wind Speeds ◽  
Relative Wind

Abstract. At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near-surface turbulence. Therefore, processes related to near-surface turbulence and wave breaking, such as sea spray emission and air–sea gas exchange, are often parameterised with wind speed. Thus, shipborne wind speed measurements provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects near the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, lose their validity due to changes in the structures near the anemometer and, thus, require frequent re-evaluation, which is costly in either computational power or ship time. Here, we evaluate if global atmospheric reanalysis data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition onboard the R/V Akademik Tryoshnikov, which are compared to ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +22 % and -17∘ to +11∘ respectively. The resulting error in the true wind speed is +11.5 % on average but ranges from −4 % to +41 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to ±5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model biases in the correction factors. We show that this problem can be somewhat mitigated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify computational fluid dynamic studies of airflow distortion on research vessels.

scholarly journals Assessing Wind Data from Reanalyses for the Upper Midwest

2019 ◽  
Vol 58 (3) ◽  
pp. 429-446 ◽  
Author(s):  
Jacob J. Coburn
Keyword(s):  
Wind Speed ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Wind Data ◽  
Upper Midwest ◽  
Wind Speeds ◽  
Potential Applications ◽  
Mitigate Climate Change ◽  
Wind Resource

AbstractWind is an important atmospheric variable that is receiving increased attention as the world seeks to shift from carbon-based fuels in order to mitigate climate change. This has resulted in increased need for more temporally and spatially continuous wind information, which is often met through the use of reanalysis data. However, limited work has been done to assess the long-term accuracy of the wind data against observations in the context of specific applications. This study focuses on the representation of daily and monthly average 10-m wind speed data in the upper Midwest by six global reanalysis datasets. The accuracy of the datasets was assessed using several measures of skill, as well as the associated wind speed distributions and long-term trends. While it was found that higher resolution and complexity in more recent generations of reanalyses produced more accurate simulations of wind in the region, important biases remained. High variability in the observed data resulted in lower correlations at the monthly time scale. As with previous research, linear trends calculated from the reanalyzed wind speeds were significantly underestimated compared to observed trends. While it is expected that future improvements in model resolution, physics, and data assimilation will further improve wind representation in reanalyses, accounting for the differences between the available datasets and their associated biases will be important for potential applications of the output, particularly wind resource assessment.

scholarly journals Cyclone Wind Retrieval Based on X-Band SAR-Derived Wave Parameter Estimation

2020 ◽  
Vol 37 (10) ◽  
pp. 1907-1924
Author(s):  
Weizeng Shao ◽  
Yuyi Hu ◽  
Ferdinando Nunziata ◽  
Valeria Corcione ◽  
Maurizio Migliaccio ◽  
...  
Keyword(s):  
Wind Speed ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Hurricane Sandy ◽  
Wave Parameter ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Research Division ◽  
X Band ◽  
Sar Imagery

AbstractIn this study, a method for retrieving wind speed from synthetic aperture radar (SAR) imagery collected under extreme weather conditions is proposed. The rationale for this approach relies on the fact that, although copolarized channels exhibit saturation for wind speed >~20 m s−1, the wave growth can be successfully exploited to gather information on wind speed under extreme weather conditions. Hence, in this study, the intrinsic relationship among the wind-wave triplets [wind speed at 10 m above the sea surface, significant wave height (SWH), and peak wave period] is exploited in order to retrieve wind speeds under tropical cyclone conditions. Experiments, undertaken on actual X-band TerraSAR-X (TS-X) SAR images of tropical cyclones (Typhoon Megi, Hurricane Sandy, and Hurricane Miriam) and using collocated WAVEWATCH-III (WW3) simulations, revealed the robustness of the proposed approach, which resulted in a root-mean-square error (RMSE) of 2.54 m s−1 when comparing the retrieved wind speeds with the values from products delivered by the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD). However, the applicability of the algorithm herein will be further confirmed at very strong storms.

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