scholarly journals High-Resolution Hurricane Vector Winds from C-Band Dual-Polarization SAR Observations

2014 ◽  
Vol 31 (2) ◽  
pp. 272-286 ◽  
Author(s):  
Biao Zhang ◽  
William Perrie ◽  
Jun A. Zhang ◽  
Eric W. Uhlhorn ◽  
Yijun He
Keyword(s):  
Cost Function ◽  
Surface Wind ◽  
Band Model ◽  
Retrieval Model ◽  
Dual Polarization ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Geophysical Model ◽  
Consistency Results ◽  
Geophysical Model Function

Abstract This study presents a new approach for retrieving hurricane surface wind vectors utilizing C-band dual-polarization (VV, VH) synthetic aperture radar (SAR) observations. The copolarized geophysical model function [C-band model 5.N (CMOD5.N)] and a new cross-polarized wind speed retrieval model for dual polarization [C-band cross-polarized ocean surface wind retrieval model for dual-polarization SAR (C-2POD)] are employed to construct a cost function. Minimization of the cost function allows optimum estimates for the wind speeds and directions. The wind direction ambiguities are removed using a parametric two-dimensional sea surface inflow angle model. To evaluate the accuracy of the proposed method, two RADARSAT-2 SAR images of Hurricanes Bill and Bertha are analyzed. The retrieved wind speeds and directions are compared with collocated Quick Scatterometer (QuikSCAT) winds, showing good consistency. Results suggest that the proposed method has good potential to retrieve hurricane surface wind vectors from dual-polarization SAR observations.

scholarly journals Validation of NOAA CyGNSS Wind Speed Product with the CCMP Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1832
Author(s):  
Xiaohui Li ◽  
Dongkai Yang ◽  
Jingsong Yang ◽  
Guoqi Han ◽  
Gang Zheng ◽  
...  
Keyword(s):  
Wind Speed ◽  
Comprehensive Evaluation ◽  
Surface Wind ◽  
Temporal Analysis ◽  
Satellite System ◽  
Wind Retrieval ◽  
Sea Surface Wind ◽  
Geophysical Model ◽  
Geophysical Model Function ◽  
Global Navigation Satellite

The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CyGNSS) mission was launched in December 2016, which can remotely sense sea surface wind with a relatively high spatio-temporal resolution for tracking tropical cyclones. In recent years, with the gradual development of the geophysical model function (GMF) for CyGNSS wind retrieval, different versions of CyGNSS Level 2 products have been released and their performance has gradually improved. This paper presents a comprehensive evaluation of CyGNSS wind product v1.1 produced by the National Oceanic and Atmospheric Administration (NOAA). The Cross-Calibrated Multi-Platform (CCMP) analysis wind (v02.0 and v02.1 near real time) products produced by Remote Sensing Systems (RSS) were used as the reference. Data pairs between the NOAA CyGNSS and RSS CCMP products were processed and evaluated by the bias and standard deviation SD. The CyGNSS dataset covers the period between May 2017 and December 2020. The statistical comparisons show that the bias and SD of CyGNSS relative to CCMP-nonzero collocations when the flag of CCMP winds is nonzero are –0.05 m/s and 1.19 m/s, respectively. The probability density function (PDF) of the CyGNSS winds coincides with that of CCMP-nonzero. Furthermore, the average monthly bias and SD show that CyGNSS wind is consistent and reliable generally. We found that negative deviation mainly appears at high latitudes in both hemispheres. Positive deviation appears in the China Sea, the Arabian Sea, and the west of Africa and South America. Spatial–temporal analysis demonstrates the geographical anomalies in the bias and SD of the CyGNSS winds, confirming that the wind speed bias shows a temporal dependency. The verification and comparison show that the remotely sensed wind speed measurements from NOAA CyGNSS wind product v1.1 are in good agreement with CCMP winds.

scholarly journals Wind Speed Retrieval from Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data for Marine Application

2019 ◽  
Vol 11 (14) ◽  
pp. 1682 ◽  
Author(s):  
Torsten Geldsetzer ◽  
Shahid K. Khurshid ◽  
Kerri Warner ◽  
Filipe Botelho ◽  
Dean Flett
Keyword(s):  
Wind Speed ◽  
Low Noise ◽  
Quality Data ◽  
Band Model ◽  
Data Set ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Geophysical Model ◽  
The Right ◽  
Quality Threshold

RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys on the West and East coasts of Canada. Wind speeds up to 18 m/s were included. CP and linear polarization parameters were related to the C-band model (CMOD) geophysical model functions CMOD-IFR2 and CMOD5n. These were evaluated for their wind retrieval potential in each RCM mode. The CP parameter Conformity was investigated to establish a data-quality threshold (>0.2), to ensure high-quality data for model validation. An accuracy analysis shows that the first Stokes vector (SV0) and the right-transmit vertical-receive backscatter (RV) parameters were as good as the VV backscatter with CMOD inversion. SV0 produced wind speed retrieval accuracies between 2.13 m/s and 2.22 m/s, depending on the RCM mode. The RCM Medium Resolution 50 m mode produced the best results. The Low Resolution 100 m and Low Noise modes provided similar results. The efficacy of SV0 and RV imparts confidence in the continuity of robust wind speed retrieval with RCM CP data. Three image-based case studies illustrate the potential for the application of CP parameters and RCM modes in operational wind retrieval systems. The results of this study provide guidance to direct research objectives once RCM is launched. The results also provide guidance for operational RCM data implementation in Canada’s National SAR winds system, which provides near-real-time wind speed estimates to operational marine forecasters and meteorologists within Environment and Climate Change Canada.

scholarly journals Towards the Sea Wind Measurement with the Airborne Scatterometer Having the Rotating-Beam Antenna Mounted over Fuselage

2021 ◽  
Vol 13 (24) ◽  
pp. 5165
Author(s):  
Alexey Nekrasov ◽  
Alena Khachaturian
Keyword(s):  
Remote Sensing ◽  
Surface Wind ◽  
Rotating Beam ◽  
Partial Shading ◽  
Wind Measurement ◽  
Wind Retrieval ◽  
Sea Surface Wind ◽  
Geophysical Model ◽  
Geophysical Model Function ◽  
Sea Wind

Extension of the existing airborne radars’ applicability is a perspective approach to the remote sensing of the environment. Here we investigate the capability of the rotating-beam radar installed over the fuselage for the sea surface wind measurement based on the comparison of the backscatter with the respective geophysical model function (GMF). We also consider the robustness of the proposed approach to the partial shading of the underlying water surface by the aircraft nose, tail, and wings. The wind retrieval algorithms have been developed and evaluated using Monte-Carlo simulations. We find our results promising both for the development of new remote sensing systems as well as the functional enhancement of existing airborne radars.

scholarly journals Intercalibration of Backscatter Measurements among Ku-Band Scatterometers Onboard the Chinese HY-2 Satellite Constellation

2021 ◽  
Vol 13 (23) ◽  
pp. 4783
Author(s):  
Zhixiong Wang ◽  
Juhong Zou ◽  
Youguang Zhang ◽  
Ad Stoffelen ◽  
Wenming Lin ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Surface Wind ◽  
Double Difference ◽  
Satellite Orbits ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Geophysical Model ◽  
Geophysical Model Function ◽  
Nwp Model ◽  
Ku Band

The Chinese HY-2D satellite was launched on 19 May 2021, carrying a Ku-band scatterometer. Together with the operating scatterometers onboard the HY-2B and HY-2C satellites, the HY-2 series scatterometer constellation was built, constituting different satellite orbits and hence opportunity for mutual intercomparison and intercalibration. To achieve intercalibration of backscatter measurements for these scatterometers, this study presents and performs three methods including: (1) direct comparison using collocated measurements, in which the nonlinear calibrations can also be derived; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over the global oceans, in which a geophysical model function and numerical weather prediction (NWP) model winds are needed. The results obtained using the three methods are comparable, i.e., the differences among them are within 0.1 dB. The intercalibration results are validated by comparing the HY-2 series scatterometer wind speeds with NWP model wind speeds. The curves of wind speed bias for the HY-2 series scatterometers are quite similar, particularly in wind speeds ranging from 4 to 20 m/s. Based on the well-intercalibrated backscatter measurements, consistent sea surface wind products from HY-2 series scatterometers can be produced, and greatly benefit data applications.

scholarly journals Ocean Wind Retrieval Models for RADARSAT Constellation Mission Compact Polarimetry SAR

2018 ◽  
Vol 10 (12) ◽  
pp. 1938 ◽  
Author(s):  
Tianqi Sun ◽  
Guosheng Zhang ◽  
William Perrie ◽  
Biao Zhang ◽  
Changlong Guan ◽  
...  
Keyword(s):  
Cross Sections ◽  
Quadratic Function ◽  
Retrieval Model ◽  
Retrieval Models ◽  
Wind Retrieval ◽  
Geophysical Model ◽  
Radar Cross Sections ◽  
Geophysical Model Function ◽  
Ocean Wind

We propose two new ocean wind retrieval models for right circular-vertical (RV) and right circular-horizontal (RH) polarizations respectively from the compact-polarimetry (CP) mode of the RADARSAT Constellation Mission (RCM), which is scheduled to be launched in 2019. For compact RV-polarization (right circular transmit and vertical receive), we build the wind retrieval model (denoted CoVe-Pol model) by employing the geophysical model function (GMF) framework and a sensitivity analysis. For compact RH polarization (right circular transmit and horizontal receive), we build the wind retrieval model (denoted the CoHo-Pol model) by using a quadratic function to describe the relationship between wind speed and RH-polarized normalized radar cross-sections (NRCSs) along with radar incidence angles. The parameters of the two retrieval models are derived from a database including wind vectors measured by in situ National Data Buoy Center (NDBC) buoys and simulated RV- and RH-polarized NRCSs and incidence angles. The RV- and RH-polarized NRCSs are generated by a RCM simulator using C-band RADARSAT-2 quad-polarized synthetic aperture radar (SAR) images. Our results show that the two new RCM CP models, CoVe-Pol and CoHo-POL, can provide efficient methodologies for wind retrieval.

scholarly journals Comparison of C-Band Scatterometer CMOD5.N Equivalent Neutral Winds with ECMWF

2010 ◽  
Vol 27 (4) ◽  
pp. 721-736 ◽  
Author(s):  
Hans Hersbach
Keyword(s):  
Wind Speed ◽  
Incidence Angle ◽  
Surface Wind ◽  
Empirical Relation ◽  
Band Model ◽  
Neutral Wind ◽  
Model Function ◽  
Geophysical Model ◽  
Geophysical Model Function ◽  
Residual Stability

Abstract This article describes the evaluation of a C-band geophysical model function called C-band model 5.N (CMOD5.N). It is used to provide an empirical relation between backscatter as sensed by the spaceborne European Remote Sensing Satellite-2 (ERS-2) and Advanced Scatterometer (ASCAT) scatterometers and equivalent neutral ocean vector wind at 10-m height (neutral surface wind) as function of scatterometer incidence angle. CMOD5.N embodies a refit of CMOD5, a C-band model function, which was previously derived to obtain nonneutral surface wind, in such a way that its 28 tunable coefficients lead, for a given backscatter observation, to an enhancement of 0.7 m s−1 in wind speed. The value of 0.7 m s−1 is chosen to be independent of wind speed and incidence angle, and it incorporates the average difference between neutral and nonneutral wind (∼0.2 m s−1) and for a known bias of CMOD5 (∼0.5 m s−1) when compared to buoy wind data. The quality of the CMOD5.N fit is successfully tested for the Active Microwave Instrument (AMI) scatterometer on ERS-2 and ASCAT instrument on Meteorological Operational-A (MetOp-A) for July 2007 and January 2008. ASCAT and ERS-2 wind speed obtained from CMOD5.N compares well on average with operational neutral wind from the European Centre for Medium-Range Weather Forecasts (ECMWF). In comparison with nonneutral wind, the local, seasonally dependent biases between scatterometer and ECMWF model are reduced. Besides effects introduced by sea state, orography, and ocean currents, a residual stability-dependent bias between scatterometer and neutral wind remains, which is likely connected to a nonoptimality in the ECMWF boundary layer formalism that is reported in the literature.

scholarly journals A Wind Speed Retrieval Model for Sentinel-1A EW Mode Cross-Polarization Images

2019 ◽  
Vol 11 (2) ◽  
pp. 153 ◽  
Author(s):  
Yuan Gao ◽  
Changlong Guan ◽  
Jian Sun ◽  
Lian Xie
Keyword(s):  
Wind Speed ◽  
Incidence Angle ◽  
Surface Wind ◽  
European Space Agency ◽  
Sea Surface ◽  
Cross Polarization ◽  
Retrieval Model ◽  
Sar Images ◽  
Wind Speeds ◽  
Sea Surface Wind

In contrast to co-polarization (VV or HH) synthetic aperture radar (SAR) images, cross-polarization (CP for VH or HV) SAR images can be used to retrieve sea surface wind speeds larger than 20 m/s without knowing the wind directions. In this paper, a new wind speed retrieval model is proposed for European Space Agency (ESA) Sentinel-1A (S-1A) Extra-Wide swath (EW) mode VH-polarized images. Nineteen S-1A images under tropical cyclone condition observed in the 2016 hurricane season and the matching data from the Soil Moisture Active Passive (SMAP) radiometer are collected and divided into two datasets. The relationships between normalized radar cross-section (NRCS), sea surface wind speed, wind direction and radar incidence angle are analyzed for each sub-band, and an empirical retrieval model is presented. To correct the large biases at the center and at the boundaries of each sub-band, a corrected model with an incidence angle factor is proposed. The new model is validated by comparing the wind speeds retrieved from S-1A images with the wind speeds measured by SMAP. The results suggest that the proposed model can be used to retrieve wind speeds up to 35 m/s for sub-bands 1 to 4 and 25 m/s for sub-band 5.

scholarly journals Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models

2018 ◽  
Vol 10 (9) ◽  
pp. 1448 ◽  
Author(s):  
He Fang ◽  
Tao Xie ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Jingsong Yang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Synthetic Aperture ◽  
Northwest Pacific ◽  
Sar Images ◽  
Retrieval Models ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Aperture Radar

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.

scholarly journals Preliminary Analysis of Wind Retrieval Based on GF-3 Wave Mode Images

2018 ◽  
Author(s):  
Lei Wang ◽  
Bing Han ◽  
Xinzhe Yuan ◽  
Bin Lei ◽  
Chibiao Ding ◽  
...  
Keyword(s):  
Wind Speed ◽  
Incidence Angle ◽  
Surface Wind ◽  
Wave Mode ◽  
Azimuth Angle ◽  
Calibration Constant ◽  
Wind Fields ◽  
Wind Retrieval ◽  
Geophysical Model ◽  
The Cross

In this paper, we analyze the measurements of the normalized radar cross-section(NRCS) in Wave Mode for Chinese C-band Gaofen-3(GF-3) synthetic aperture radar (SAR). Based on 2779 images from GF-3 quad-polarization SAR in Wave Mode and collocated wind vectors from ERA-Interim, we verify the feasibility of using ocean surface wind fields and VV-polarized NRCS to perform normalized calibration. The method uses well-validated empirical C-band geophysical model function (CMOD4) to estimate the calibration constant for each beam. The Amazon rainforest experiment results show that the accuracy of obtained calibration constant meets the requirements. In addition, the relationship between cross-pol NRCS and wind vectors is discussed. The cross-pol NRCS increases linearly with wind speed and it has an approximate cosine modulation with the wind direction when the wind speed is greater than 8m/s. The cross-polarized system noise floor is low enough to ignore it in wind retrieval. Furthermore, we also investigate the properties of the polarization ratio, denoted PR, and show that it is dependent on incidence angle and azimuth angle. Two empirical models of the PR are fitted, one as a function of incidence angle only, the other with additional dependence on azimuth angle. Assessments show that the σ_VV^0 retrieved from new PR models as well as σ_HH^0 is in good agreement with σ_VV^0 extracted from SAR images directly. And it is also shown that considering the azimuth angle can improve polarization conversion accuracy.

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