scholarly journals X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling

2012 ◽  
Vol 9 (5) ◽  
pp. 3251-3279 ◽  
Author(s):  
A. Montuori ◽  
P. de Ruggiero ◽  
M. Migliaccio ◽  
S. Pierini ◽  
G. Spezie
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Coastal Circulation ◽  
Wind Fields ◽  
Sea Surface Wind ◽  
X Band ◽  
Circulation Modeling ◽  
Sar Data ◽  
Ecmwf Model

Abstract. In this paper, X-band COSMO-SkyMed© SAR wind field retrieval is investigated to force coastal circulation modeling. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed© SAR data, gathered in the Southern Tyrrhenian Sea during the Summer and Winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the Azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the Discrete Wavelet Transform Multi-Resolution Analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a Southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results clearly show that X-band COSMO-SkyMed© SAR data can be valuable in providing effective wind fields for coastal circulation modeling.

scholarly journals X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling

Ocean Science ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 121-132 ◽  
Author(s):  
A. Montuori ◽  
P. de Ruggiero ◽  
M. Migliaccio ◽  
S. Pierini ◽  
G. Spezie
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Circulation Model ◽  
Coastal Circulation ◽  
Wind Fields ◽  
Sea Surface Wind ◽  
X Band ◽  
Sar Data ◽  
Ecmwf Model

Abstract. In this paper, X-band COSMO-SkyMed© synthetic aperture radar (SAR) wind field retrieval is investigated, and the obtained data are used to force a coastal ocean circulation model. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed© SAR data, gathered in the southern Tyrrhenian Sea during the summer and winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the discrete wavelet transform multi-resolution analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results show that X-band COSMO-SkyMed© SAR data can be valuable in providing effective wind fields for coastal circulation modeling.

scholarly journals Characteristics and Applications of the Ground-Based X Band Low Elevation Angle Brightness Temperatures under Low Sea State Based on Measured Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1736
Author(s):  
Zhongqing Cao ◽  
Lixin Guo ◽  
Shifeng Kang ◽  
Xianhai Cheng ◽  
Qingliang Li ◽  
...  
Keyword(s):  
Wind Speed ◽  
Meteorological Data ◽  
Surface Wind ◽  
Elevation Angle ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Sea State ◽  
Sea Surface Wind Speed ◽  
Sea Surface Wind ◽  
X Band

In ground-based microwave radiometer remote sensing, low-elevation-angle (−3°~3°) radiation data are often discarded because they are considered to be of little value and are often difficult to model due to the complicated mechanism. Based on the observed X-band horizontal polarization low elevation angle microwave radiation data and the meteorological data at the same time, this study investigated the generation mechanism of low elevation angle brightness temperature (LEATB) and its relationship with meteorological data, i.e., temperature, humidity, and wind speed, under low sea state. As a result, one could find that the LEATB was sensitive to the atmosphere at the elevation angle between 1° to 3°, and a diurnal variation of the LEATB reached up to 10 K. This study also found a linear relationship between the LEATB and sea surface wind speed under low sea state at an elevation range from −3° to 0°, i.e., the brightness temperature decreased as the wind speed increased, which was inconsistent with the observations at the elevation angle from −10° to −5°. The variation of the LEATB difference according to the change in the over-the-horizon detection capability (OTHDC) of the shipborne microwave radar was examined to identify the reason for this phenomenon theoretically. The results showed that the LEATB difference was significantly influenced by a change in the OTHDC. Further, this study examined a remote sensing method to extract the sea surface wind speed data from experimental LEATB data under low sea state. The results demonstrated that the X-band horizontal polarization LEATBs were useful to retrieve the sea surface wind speed data at a reasonable accuracy—the root mean square error of 0.02408 m/s. Overall, this study proved the promising potential of the LEATB data for retrieving temperature profiles, humidity profiles, sea surface winds, and the OTHDC.

scholarly journals Research on Wind Speed Inversion Method for X-Band Networked SAR Satellite

2020 ◽  
Vol 8 (9) ◽  
pp. 626
Author(s):  
Yong Wan ◽  
Xiaolei Shi ◽  
Yongshou Dai ◽  
Ligang Li ◽  
Xiaojun Qu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Cost Function ◽  
Wind Direction ◽  
Incident Angle ◽  
Surface Wind ◽  
Sea Surface ◽  
Inversion Method ◽  
X Band ◽  
Direction Information ◽  
The Cost

Synthetic aperture radar (SAR) can extract sea surface wind speed information. To extract wind speed information through the geophysical model function (GMF), the corresponding wind direction information must be input. This article introduces some concepts about networked SAR satellites. The networked satellites enable multiple SARs to observe the same sea surface at different incidence angles at the same time. Aiming at the X-band networked SAR data with different incident angles, the cost function is established by using the GMF. By minimizing the cost function, accurate wind speed information can be extracted without inputting wind direction information. When the noise is small, the wind direction information is introduced, and the accuracy of the extracted wind speed will be improved. When the noise is less than 1 dB and the incident angle is greater than 30°, the root-mean-square error (RMSE) of the wind speed extracted by this method is basically less than 2 m/s.

An algorithm for the retrieval of sea surface wind fields using X-band TerraSAR-X data

2012 ◽  
Vol 33 (23) ◽  
pp. 7310-7336 ◽  
Author(s):  
Yongzheng Ren ◽  
Susanne Lehner ◽  
Stephan Brusch ◽  
Xiaoming Li ◽  
Mingxia He
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Wind Fields ◽  
Sea Surface Wind ◽  
X Band

scholarly journals Ocean Surface Wind Speed Retrieval Using Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data

2019 ◽  
Vol 11 (16) ◽  
pp. 1876
Author(s):  
He Fang ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Tao Xie ◽  
Shahid Khurshid ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Ocean Surface ◽  
Synthetic Aperture ◽  
Ocean Surface Wind ◽  
Sar Data ◽  
Relative Wind ◽  
Aperture Radar

We investigated the use of C-band RADARSAT Constellation Mission (RCM) synthetic aperture radar (SAR) for retrieval of ocean surface wind speeds by using four new channels (right circular transmit, vertical receive (RV); right circular transmit, horizontal receive (RH); right circular transmit, left circular transmit (RL); and right circular transmit, right circular receive (RR)) in compact polarimetry (CP) mode. Using 256 buoy measurements collocated with RADARSAT-2 fine beam quad-polarized scenes, RCM CP data was simulated using a “CP simulator”. Provided that the relative wind direction is known, our results demonstrate that wind speed can be retrieved from RV, RH and RL polarization channels using existing C-band model (CMOD) geophysical model function (GMF) and polarization ratio (PR) models. Simulated RR-polarized radar returns have a strong linear relationship with speed and are less sensitive to relative wind direction and incidence angle. Therefore, a model is proposed for the RR-polarized synthetic aperture radar (SAR) data. Our results show that the proposed model can provide an efficient methodology for wind speed retrieval.

scholarly journals Analyzing Sea Surface Wind Distribution Characteristics of Tropical Cyclone Based on Sentinel-1 SAR Images

2021 ◽  
Vol 13 (22) ◽  
pp. 4501
Author(s):  
Yuan Gao ◽  
Jie Zhang ◽  
Changlong Guan ◽  
Jian Sun
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Sea Surface ◽  
Cross Polarization ◽  
Wind Fields ◽  
Sar Images ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Motion Speed ◽  
Wind Distribution

The spaceborne synthetic aperture radar (SAR) cross-polarization signal remains sensitive to sea surface wind speed with high signal-to-noise ratio under tropical cyclone (TC) conditions. It has the capability of observing TC intensity and size information over the ocean with large coverage and high spatial resolution. In this paper, TC wind distribution characteristics were studied based on SAR images. We collected 41 Sentinel-1A/B cross-polarization images covering TC eye, which were acquired between 2016 and 2020. For each case, sea surface wind speeds were retrieved by the modified MS1A model in a spatial resolution of 1 km. After deriving the value and location of maximum wind speed, wind fields were simulated symmetrically within a 200 km radius. Two new methodologies were proposed to calculate the decay index and the symmetry index based on the retrieved and simulated wind fields. Characteristics of the two indices were analyzed with respect to maximum wind. In addition, the maximum and averaged wind speeds of the right, back and left side of the motion direction were compared with TC intensity and storm motion speed. Statistical results indicate that right-side wind speed is the strongest for maximum and average, the wind difference between the left and right side is dependent on storm motion speed.

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