Validation and accuracy analysis of wind products from scatterometer onboard the HY-2B satellite

The Chinese marine dynamic environment satellite HY-2B was launched in October 2018 and carries a Ku-band scatterometer.This paper focuses on the accuracies of HY-2B scatterometer wind data during the period from November 2018 to May 2021.The HY-2B wind data are validated against global moored buoys operated by the U.S.National Data Buoy Center and Tropical Atmosphere Ocean,numerical model data by the National Centers for Environmental Prediction,and the Advanced Scatterometer data issued by the Remote Sensing System.The results showed that the wind speeds and directions observed by the HY-2B scatterometer agree well with these buoy wind measurements.The root-mean-squared errors(RMSEs)of the HY-2B wind speed and direction are 0.74 m/s and 11.74°,respectively.For low wind speeds(less than 5 m/s),the standard deviation of the HY-2B-derived wind direction is higher than 20°,which implies that the HY-2B wind direction for low wind speeds is less accurate than that for moderate to high wind speed ranges.The RMSE of the HY-2B wind speed is slightly larger in high latitude oceans(60°–90°S and 60°–90°N)than in low latitude regions.Furthermore,the dependence of the residuals on the cross-track location of wind vector cells and the stability of the HY-2B scatterometer wind products are discussed.The wind stability assessment results indicate that a clear yearly oscillation is observed for the HY-2B wind speed bias which is due to seasonal weather variations.In general,the accuracy of HY-2B winds meets the operational precision requirement and is consistent with other wind data.

Neural network wind retrieval from ERS-1/2 scatterometer data

A neural network methodology is presented to retrieve wind vectors from ERS - 1/2 scatterometer data. The wind directional ambiguities are eliminated by a circular median filter algorithm. All data come from ERS - 1/2 scatterometer data collocated pairs with CMCD4 vector. Comparing the results with CMCD4 and ECMWF wind vector,they agree well, which indicates that it is possible to extract wind vector from the ERS-1/2 scatterometer with the neural network method.

Sea ice extent retrieval with HY-2A scatterometer data and its assessment

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established. Four parameters are used for distinguishing between sea ice and ocean with Fisher＇s linear discriminant analysis method. The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013-2014 from the scatterometer aboard HY-2A （HY-2A-SCAT） backscatter data. The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder （SSMIS） sea ice concentration data. For both hemispheres, the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period. Compared with Synthetic Aperture Radar （SAR） imagery, the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge. Over some ice edge area, the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.

Astudyofanewretrievalalgorithmformeasurementofoceanicwindvectorsfieldusingsatellitemicrowavescatterometer

The Seasat-A satellite scatterometer(SASS) demonstrated very successfully that scatterometers can makeaccurate synoptic measurements of surface wind vectors field over the ocean. The technology is based on the sensitivityof microwave radar back scatter to the ocean waves in centimeter scale created by the action of the surface wind. More-over, the back scatter is anisotropic, therefore, wind speed and direction can be derived from radar measurements attwo or more different azimuths. Owing to the nonlinear nature of scatter model function and the existence of variousnoise sources in the measurements, the retrieval wind results consist of as many as four wind directions. A new algo-rithm is proposed to recover ocean wind field from the SASS normalized cross-section measurement in this paper. Comparison with those estimated from the SASS surface wind analysed by Peteherych et al . (1984) and other referencesshow agreement largely in the wind direction and more exactly in the wind speed.

Application of Tikhonov regularization method to wind retrieval from scatterometer data Ⅱ: cyclone wind retrieval with consideration of rain

According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function （called CMF＋Rain）. The CMF＋Rain model which is based on the NASA scatterometer-2 （NSCAT2） GMF is presented to compensate for the effects of rain on cyclone wind retrieval. With the multiple solution scheme （MSS）, the noise of wind retrieval is effectively suppressed, but the influence of the background increases. It will cause a large wind direction error in ambiguity removal when the background error is large. However, this can be mitigated by the new ambiguity removal method of Tikhonov regularization as proved in the simulation experiments. A case study on an extratropical cyclone of hurricane observed with SeaWinds at 25-km resolution shows that the retrieved wind speed for areas with rain is in better agreement with that derived from the best track analysis for the GMF＋Rain model, but the wind direction obtained with the two-dimensional variational （2DVAR） ambiguity removal is incorrect. The new method of Tikhonov regularization effectively improves the performance of wind direction ambiguity removal through choosing appropriate regularization parameters and the retrieved wind speed is almost the same as that obtained from the 2DVAR.

The first quantitative joint observation of typhoon by Chinese GF-3 SAR and HY-2A microwave scatterometer

The typhoon, as a mature tropical cyclone that develops in the western part of the North Pacific Ocean with high wind speed and heavy rainfall, is one of the most lethal and costly of natural disasters for the densely populated countries of East Asia. It can be easily detected by space-borne sensors operated at microwave, visible or infrared bands （Liu et al., 2014）. Synthetic Aperture Radar （SAR） is a kind of active imaging radar, which can detect the targets with high resolution at one-meter level. SARs can be used to extract the sea surface wind and the eyes of typhoons or hurricanes （Friedman and Li, 2000; Zhang and Perrie, 2012; Li, 2015; Jin et al., 2014; Liu et al., 2014）. As a pioneer project of Haiyang-3 （HY-3）, the Chinese C-band SAR satellite of Gaofen-3 （GF-3） was launched in August 2016 under China High-resolution Earth Observation System （CEOS）. GF-3 carries a multi-polarized C-band SAR with a highest spatial resolution of one meter, the most imaging modes in the word of twelve and a long designed lifespan of 8 years. Haiyang-2A （HY-2A）, which was launched in August 2011, is the first Chinese marine dynamic environment satellite with a main payload of Ku-band microwave scatterometer （Jiang et al., 2012; Ye et al., 2015）. One of the objectives of HY-2A scatterometer （HY-2A SCAT） is monitoring sea surface wind field of global ocean.

The study on an Antarctic sea ice identification algorithm of the HY-2A microwave scatterometer data

An Antarctic sea ice identification algorithm on the HY-2A scatterometer（HSCAT） employs backscattering coefficient（σ0） and active polarization ratio（APR） for a preliminary sea ice identification.Then standard deviation（STD） filtering and space filtering are carried out.Finally,it is used to identify sea ice.A process uses a σ0,STD threshold and an APR as sea ice indicators.The sea ice identification results are verified using the sea ice distribution data of the ASMR2 released by the National Snow and Ice Data Center as a reference.The results show very good consistence of sea ice development trends,seasonal changes,area distribution,and sea ice edge distribution of the sea ice identification results obtained by this algorithm relative to the ASMR2 sea ice results.The accuracy of a sea ice coverage is 90.8% versus the ASMR2 sea ice results.This indicates that this algorithm is reliable.

Wave effects on the retrieved wind field from the advanced scatterometer(ASCAT)

To improve retrieval accuracy, this paper studies wave effects on retrieved wind field from a scatterometer. First, the advanced scatterometer （ASCAT） data and buoy data of the National Data Buoy Center （NDBC） are collocated. Buoy wind speed is converted into neutral wind at 10 m height. Then, ASCAT data are com- pared with the buoy data for the wind speed and direction. Subsequently, the errors between the ASCAT and the buoy wind as a function of each wave parameter are used to analyze the wave effects. Wave param- eters include dominant wave period （dpd）, significant wave height （swh）, average wave period （apd） and the angle between the dominant wave direction （dwd） and the wind direction. Collocated data are divided into sub-datasets according to the different intervals of each wave parameter. A root mean square error （RMSE） for the wind speed and a mean absolute error （MAE） for the wind direction are calculated from the sub-datasets, which are considered as the function of wave parameters. Finally, optimal wave conditions on wind retrieved from the ASCAT are determined based on the error analyses. The results show the ocean wave parameters have correlative relationships with the RMSE of the retrieved wind speed and the MAE of the retrieved wind direction. The optimal wave conditions are presented in terms of dpd, swh, apd and angle.

Application of the Tikhonov regularization method to wind retrieval from scatterometer data I.Sensitivity analysis and simulation experiments

Scatterometer is an instrument which provides all-day and large-scale wind field information, and its application especially to wind retrieval always attracts meteorologists. Certain reasons cause large direction error, so it is important to find where the error mainly comes. Does it mainly result from the background field, the normalized radar cross-section （NRCS） or the method of wind retrieval？ It is valuable to research. First, depending on SDP2.0, the simulated ＇true＇ NRCS is calculated from the simulated ＇true＇ wind through the geophysical mode] function NSCAT2. The simulated background field is configured by adding a noise to the simulated ＇true＇ wind with the non-divergence constraint. Also, the simulated ＇measured＇ NRCS is formed by adding a noise to the simulated ＇true＇ NRCS. Then, the sensitivity experiments are taken, and the new method of regularization is used to improve the ambiguity removal with simulation experiments. The results show that the accuracy of wind retrieval is more sensitive to the noise in the background than in the measured NRCS; compared with the two-dimensional variational （2DVAR） ambiguity removal method, the accuracy of wind retrieval can be improved with the new method of Tikhonov regularization through choosing an appropriate regularization parameter, especially for the case of large error in the background. The work will provide important information and a new method for the wind retrieval with real data.

Comparison of sea surface wind field measured by HY-2A scatterometer and WindSat in global oceans

In this study, we present a comprehensive comparison of the sea surface wind ?eld measured by scatterometer(Ku-band scatterometer) aboard the Chinese HY-2 A satellite and the full-polarimetric radiometer WindSat aboard the Coriolis satellite. The two datasets cover a four-year period from October2011 to September 2015 in the global oceans. For the sea surface wind speed, the statistical comparison indicates good agreement between the HY-2 A scatterometer and WindSat with a bias of nearly 0 m/s and a root mean square error(RMSE) of 1.13 m/s. For the sea surface wind direction, a bias of 1.41° and an RMSE of 20.39° were achieved after excluding the data collocated with opposing directions. Furthermore,discrepancies in sea surface wind speed measured by the two sensors in the global oceans were investigated.It is found that the larger dif ferences mainly appear in the westerlies in the both hemispheres. Both the bias and RMSE show latitude dependence, i.e., they have signi?cant latitudinal ?uctuations.

The Performance of Dual-Frequency Polarimetric Scatterometer in Sea Surface Wind Retrieval

The wind retrieval performance of HY-2 A scanning scatterometer operating at Ku-band in HH and VV polarizations has been well evaluated in the wind speed range of 0–25 m s^-1.In order to obtain more accurate ocean wind field,a potential extension of dual-frequency(C-band and Ku-band)polarimetric measurements is investigated for both low and very high wind speeds,from 5 to 45 m s^-1.Based on the geophysical model functions of C-band and Ku-band,the simulation results show that the polarimetric measurements of Ku-band can improve the wind vector retrieval over the entire scatterometer swath,especially in nadir area,with the wind direction root-mean-square error(RMSE)less than 12?in the wind speed range of 5–25 m s^-1.Furthermore,the results also show that C-band cross-polarization plays a very important role in improving the wind speed retrieval,with the wind speed retrieval accuracy better than 2 m s^-1 for all wind conditions(0–45 m s^-1).For extreme winds,the C-band HH backscatter coefficients modeled by CMOD5.N(H)and the ocean co-polarization ratio model at large incidence are used to retrieve sea surface wind vector.This result reveals that there is a big decrease of wind direction retrieval RMSE for extreme wind fields,and the retrieved result of C-band HH polarization is nearly the same as that of C-band VV polarization for low-to-high wind speed(5–25 m s^-1).Thus,to improve the wind retrieval for all wind conditions,the dual-frequency polarimetric scatterometer with C-band and Ku-band horizontal polarization in inner beam,and C-band horizontal and Ku-band vertical polarization in outer beam,can be used to measure ocean winds.This study will contribute to the wind retrieval with merged satellites data and the future spaceborne scatterometer.

Joint Monitoring of Ground and Sky for Cereal Crops Based on Scatterometer Measurement and ASAR Images

The joint monitoring of the ground and sky for cereal crops based on microwave data has become a popular method for researches on earth surface objects. Focused on the sensitivity of backscatter from the scatterometer measurement and advanced synthetic aperture radar (ASAR) images to cereal parameters of rice, nine acquisitions, including rice parameters related eco-physiological variables and scattering coefficients, have been carried over the paddy field corresponding to rice growth stages. This paper analyzes the relationship between the corresponding backscatter to the cereal parameters based on the measurement at the interesting bands, polarizations, and incidence angels. Further, a modified water cloud model is built based on the ground measurement and advanced integrated equation model (AIEM), and then cereal parameters from ASAR images are retrieved and verified. The research results show that the sensitivity of backscatter to cereals from the sensor of the radar scatterometer could be helpful to build the retrieve model for synthetic aperture radar (SAR) images, which can achieve the scientific goals of the joint monitoring of ground and sky for cereal crops.

Variational assimilation in combination with a regularization method for sea level pressure retrieval from QuikSCAT scatterometer data Ⅱ:simulation experiment and actual case study

The sea level pressure field can be computed from sea surface winds retrieved from satellite microwave scatterometer measurements, based on variational assimilation in combination with a regularization method given in part I of this paper. First, the validity of the new method is proved with a simulation experiment. Then, a new processing procedure for the sea level pressure retrieval is built by combining the geostrophic wind, which is computed from the scatterometer 10-meter wind using the University of Washington planetary boundary layer model using this method. Finally, the feasibility of the method is proved using an actual case study.

An advanced wind vector retrieval algorithm for the rotating fan-beam scatterometer

The rotating fan-beam scatterometer （RFSCAT） is a new type of satellite scatterometer that is proposed approximately 10 a ago. However, similar to other rotating scatterometers, relatively larger wind retrieval errors occur in the nadir and outer regions compared with the middle regions of the swath. For the RFSCAT with the given parameters, a wind direction retrieval accuracy decreases by approximately 9 in the outer regions compared with the middle region. To address this problem, an advanced wind vector retrieval algorithm for the RFSCAT is presented. The new algorithm features an adaptive extension of the range of wind direction for each wind vector cell position across the whole swath according to the distribution histogram of a retrieved wind direction bias. One hundred orbits of Level 2A data are simulated to validate and evaluate the new algorithm. Retrieval experiments demonstrate that the new advanced algorithm can effectively improve the wind direction retrieval accuracy in the nadir and outer regions of the RFSCAT swath. Approximately 1.6 and 9 improvements in the wind direction retrieval are achieved for the wind vector cells located at the nadir and the edge point of the swath, respectively.

Variational assimilation in combination with the regularization method for sea level pressure retrieval from QuikSCAT scatterometer data I:Theoretical frame construction

A new method of constructing a sea level pressure field from satellite microwave scatterometer measurements is presented. It is based on variational assimilation in combination with a regularization method using geostrophic vorticity to construct a sea level pressure field from scatterometer data that are given in this paper, which offers a new idea for the application of scatterometer measurements. Firstly, the geostrophic vorticity from the scatterometer data is computed to construct the observation field, and the vorticity field in an area and the sea level pressure on the borders are assimilated. Secondly, the gradient of sea level pressure （semi-norm） is used as the stable functional to educe the adjoint system, the adjoint boundary condition and the gradient of the cost functional in which a weight parameter is introduced for the harmony of the system and the Tikhonov regularization techniques in inverse problem are used to overcome the ill-posedness of the assimilation. Finally, the iteration method of the sea level pressure field is developed.

System for Control, Data Collection and Processing in 8 mm Portable Microwave Radiometer-Scatterometer

In this paper we describe a system used to control,collect and process data in an 8 mm portable microwave radiometer scatterometer .We focus on hardware and software design of the system based on a PIC16F874 chip. The system has been successfully used in an 8 mm portable microwave radiometer scatterometer. Compared with other similar systems, the system modularization, miniaturization and intelligentization are improved so as to meet portable instrument requirements.

A routine operational backscattering coefficient regrouping algorithm for a HY-2A scatterometer

The routine operational sigma0 regrouping method is proposed for a HY-2 A scatterometer（HSCAT） that maps time-ordered sigma0 s and related parameters into a subtrack aligned grid of wind vector cells（WVCs）. The regrouping method consists of two critical steps： ground grid generation and sigma0 resampling. The HSCAT uses subtrack swath coordinates, in which the nadir track of the satellite represents the center and the designated positions are specified in terms of a pair of along-track and cross-track coordinates. To calculate the subtrack coordinates for each sigma0, a ＂triangle marking＂ resampling method is developed. Three points, including the point of intersection, the center of a pulse footprint, and the origin of the subtrack coordinate system, form a right triangle; the length of the two right-angled sides is used to represent the cross-track and the along-track coordinates in the subtrack coordinate system. In addition, a nadir point interpolation correction is used to ensure the operation of the regrouping algorithm when the nadir point positional information is missing. To illustrate the ability of the proposed regrouping algorithm, the distribution of the WVC positions and wind vector retrieval results are analyzed, which show that the proposed regrouping algorithm meets the requirements for high-quality sea surface wind field retrieval.

Assimilation of HY-2A scatterometer sea surface wind data in a 3DVAR data assimilation system-A case study of Typhoon Bolaven

The scatterometer （SCAT） on-board China＇s HY-2A satellite has the capability to provide high resolution wind vector information over the global ocean surface. These wind vector data produced by the HY-2A scatterometer （HY-2A SCAT） are available to the data assimilation system with real-time information of high accuracy. In this paper, two experiments are designed to investigate the impact of HY-2A SCAT data in the three- dimensional variational assimilation system for the Weather Research and Forecast model （WRF 3DVAR）. The powerful Typhoon Bolaven, which struck South Korea in August 2012, is selected for this case study. The results clearly demonstrate that HY-2A SCAT data can effectively complement the scarce observations over the ocean surface and improve the prediction of the wind and pressure fields of a typhoon. The case study of Typhoon Bolaven exhibits the significant and positive impact of HY- 2A SCAT data on the numerical prediction of the tropical cyclone track.

Assimilation of HY-2A Scatterometer Ambiguous Winds Based on Feature Thinning

This paper focuses on the data assimilation methods for sea surface winds, based on the level-2B HY-2A satellite microwave scatterometer wind products. We propose a new feature thinning method, which is herein used to screen scatterometer winds while maintaining the key structure of the wind field in the process of data thinning for highresolution satellite observations. We also accomplish feeding the ambiguous wind solutions directly into the data assimilation system, thus making better use of the retrieved information while simplifying the assimilation process of the scatterometer products. A numerical simulation experiment involving Typhoon Danas shows that our method gives better results than the traditional approach. This method may be a valuable alternative for operational satellite data assimilation.

ONSET OF THE 1998 SUMMER MONSOON IN THE SOUTH CHINA SEA-EVIDENCE FROM SATELLITE MICROWAVE SCATTEROMETER

Weekly averaged winds observed by satellite microwave scatterometer on board ERS-2 are analyzed to reveal the onset process of the 1998 South China Sea (SCS) summer monsoon.The seatterometer data sets are firstly validated by field wind observation from a buoy located at 114.41°E,12.98°N during the same period.Results of the analysis suggest that in 1998,onset of the SCS summer monsoon started in the third week of May (May 18-May 2zi),and the summer monsoon was fully established in late May.Onset of the 1998 summer monsoon is associated with the eastward withdrawal of the North Pacific trade wind system,the development of Indian monsoon,and the occurrence of cross equatorial airflow.However,the SCS summer monsoon also shows its own independence in the mature phase.Local ocean-atmosphere and land-atmosphere interactions may also influence the onset and development of the SCS summer monsoon.