Mingsen Lin

The HY-2 satellite and its preliminary assessment

Abstract The HY-2 satellite was successfully launched on 16 August 2011. It carried four microwave instruments into space for operationally observing dynamic ocean environment parameters on a global scale. The HY-2 satellite altimeter provides sea surface height (SSH), significant wave height (SWH), sea surface wind (SSW) speed, and polar ice sheet elevation, while the HY-2 satellite scatterometer provides SSW fields. At the same time, other oceanic and atmospheric parameters such as sea surface temperature (SST) and wind speed, water vapor and liquid water content can also be obtained by its onboard scanning microwave radiometer. In this paper, we show the data processing methods of the HY-2 satellites payloads. The preliminary results show that wind vector, SSH, SWH, and SST conform to the designed technical specifications.

The validation of the significant wave height product of HY-2 altimeter-primary results

The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height (SWH) is validated by the data from the South China Sea (SCS) field experiment, National Data Buoy Center (NDBC) buoys and Jason-1/2 altimeters, and is corrected using a linear regression with in-situ measurements. Compared with NDBC SWH, the HY-2 SWH show a RMS of 0.36 m, which is similar to Jason-1 and Jason-2 SWH with the RMS of 0.35mand 0.37mrespectively; the RMS of corrected HY-2 SWH is 0.27 m, similar to 0.27 m and 0.23 m of corrected Jason-1 and Jason-2 SWH. Therefore the accuracy of HY-2 SWH products is close to that of Jason-1/2 SWH, and the linear regression function derived can improve the accuracy of HY-2 SWH products.

First six months quality assessment of HY-2A SCAT wind products using in situ measurements

The first Chinese microwave ocean environment satellite HY-2A, carrying a Ku-band scatteromenter (SCAT), was successfully launched in August 2011. The first quality assessment of HY-2A SCAT wind products is presented through the comparison of the first 6 months operationally released SCAT products with in situ data. The in situ winds from the National Data Buoy Center (NDBC) buoys, R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform, were converted to the 10 m equivalent neutral winds. The temporal and spatial differences between the HY-2A SCAT and the in situ observations were limited to less than 5 min and 12.5 km. For HY-2A SCAT wind speed products, the comparison and analysis using the NDBC buoys yield a bias of −0.49 m/s, a root mean square error (RMSE) of 1.3 m/s and an increase negative bias with increasing wind speed observation above 3m/s. Although less accurate of HY-2A SCAT wind direction at low winds, the RMSE of 19.19° with a bias of 0.92° is found for wind speeds higher than 3 m/s. These results are found consistent with those from R/Vs and oil platform comparisons. Moreover, the NDBC buoy comparison results also suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of 2012. The encouraging assessment results over the first 6 months show that wind products from HY-2A SCAT will be useful for scientific community.

Validation of Chinese HY-2 satellite radar altimeter significant wave height

Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height (SWH) for more than three years (October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center (NDBC) in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error (RMSE) and mean bias of HY-2 SWH is 0.38 m and (–0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data,the RMSE and the mean bias is 0.36m and (–0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and (0.00±0.26) m, respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than –0.31m before April 2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2 SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.

A preliminary assessment of the sea surface wind speed production of HY-2 scanning microwave radiometer

A scanning microwave radiometer (RM) was launched on August 16, 2011, on board HY-2 satellite. The six-month long global sea surface wind speeds observed by the HY-2 scanning microwave radiometer are preliminarily validated using in-situ measurements and WindSat observations, respectively, from January to June 2012. The wind speed root-mean-square (RMS) difference of the comparisons with in-situ data is 1.89 m/s for themeasurements of NDBC and 1.72 m/s for the recent four-month data measured by PY30-1 oil platform, respectively. On a global scale, the wind speeds of HY-2 RM are compared with the sea surface wind speeds derived from WindSat, the RMS difference of 1.85 m/s for HY-2 RM collocated observations data set is calculated in the same period as above. With analyzing the global map of a mean difference between HY-2 RM and WindSat, it appears that the bias of the sea surface wind speed is obviously higher in the inshore regions. In the open sea, there is a relatively higher positive bias in the mid-latitude regions due to the overestimation of wind speed observations, while the wind speeds are underestimated in the Southern Ocean by HY-2 RM relative to WindSat observations.

SST Dependence of Ku- and C-Band Backscatter Measurements

The normalized radar cross section (NRCS) measured by satellite ocean radar systems is representative of the sea surface roughness at the scale of gravity-capillary waves, which are not only dominated by winds, but also modulated by some secondary factors such as sea surface temperature (SST) and sea surface salinity (SSS). In this paper, the variations of NRCS due to SST changes, depending on scatterometer radar frequency, polarization, and incidence angle, are investigated on the basis of a physics-based radar backscatter model and a dataset of collocated ASCAT C-band and RapidScat Ku-band scatterometer measurements. The study shows that the SST effects are substantial at Ku-band, but rather negligible for C-band NRCS measurements. Furthermore, the SST effects are wind speed dependent and more pronounced in VV polarization and at higher incidence angles. SSS effects, due to dielectric constant, surface tension, and dynamic viscosity variations, on scatterometer winds are limited (within 1%). This study concludes that it is necessary to take SST into account in scatterometer wind retrieval for radar wavelengths smaller than C-band.

An improved wind retrieval algorithm for the HY-2A scatterometer

Since January 2012, the National Satellite Ocean Application Service has released operational wind products from the HY-2A scatterometer (HY2-SCAT), using the maximum-likelihood estimation (MLE) method with a median filter. However, the quality of the winds retrieved from HY2-SCAT depends on the sub-satellite cross-track location, and poor azimuth separation in the nadir region causes particularly low-quality wind products in this region. However, an improved scheme, i.e., a multiple solution scheme (MSS) with a two-dimensional variational analysis method (2DVAR), has been proposed by the Royal Netherlands Meteorological Institute to overcome such problems. The present study used the MSS in combination with a 2DVAR technique to retrieve wind data from HY2-SCAT observations. The parameter of the empirical probability function, used to indicate the probability of each ambiguous solution being the “true” wind, was estimated based on HY2-SCAT data, and the 2DVAR method used to remove ambiguity in the wind direction. A comparison between MSS and ECMWF winds showed larger deviations at both low wind speeds (below 4 m/s) and high wind speeds (above 17 m/s), whereas the wind direction exhibited lower bias and good stability, even at high wind speeds greater than 24 m/s. The two HY2-SCAT wind data sets, retrieved by the standard MLE and the MSS procedures were compared with buoy observations. The RMS error of wind speed and direction were 1.3 m/s and 17.4°, and 1.3 m/s and 24.0° for the MSS and MLE wind data, respectively, indicating that MSS wind data had better agreement with the buoy data. Furthermore, the distributions of wind fields for a case study of typhoon Soulik were compared, which showed that MSS winds were spatially more consistent and meteorologically better balanced than MLE winds.

Wind retrieval processing for HY-2A microwave scatterometer

The research constructed a retrieval algorithm of routine wind fields for microwave scatterometer onboard HY-2A (HY-2A/SACT). To prepare the sigma0 measurements for conducting wind vectors retrieval, the time ordered L1B product was regrouped to the sub-track aligned wind vector cells (WVCs). Besides, the authors utilized an extension land and ice mask to simplify the surface flag process. The maximum-likelihood estimator (MLE) was applied to retrieve wind vector for each WVC with the NSCAT-2 as geophysical model function (GMF). Furthermore, to greatly improve the ambiguity removal skill, the research used circular median filter to remove the ambiguities, and the NCEP wind field as a background to re-initialized wind field comprising of ambiguous wind vectors. Wind vectors observed by HY-2A/SACT were evaluated by comparing with NDBC buoy observations. The RMS difference for wind speed was less than 2 m/s or 10%; while the RMS difference for wind direction was less than 20°comparing with wind direction. This result showed that the wind products provided by HY-2A/SCAT are able to meet the requirements of science and routine meteo users.

Coastal wind field retrieval from polarimetric synthetic aperture radar

Coastal winds are strongly influenced by topology and discontinuity between land and sea surfaces. Wind assessment from remote sensing in such a complex area remains a challenge. Space-borne scatterometer does not provide any information about the coastal wind field, as the coarse spatial resolution hampers the radar backscattering. Synthetic aperture radar (SAR) with a high spatial resolution and all-weather observation abilities has become one of the most important tools for ocean wind retrieval, especially in the coastal area. Conventional methods of wind field retrieval from SAR, however, require wind direction as initial information, such as the wind direction from numerical weather prediction models (NWP), which may not match the time of SAR image acquiring. Fortunately, the polarimetric observations of SAR enable independent wind retrieval from SAR images alone. In order to accurately measure coastal wind fields, this paper proposes a new method of using co-polarization backscattering coefficients from polarimetric SAR observations up to polarimetric correlation backscattering coefficients, which are acquired from the conjugate product of co-polarization backscatter and cross-polarization backscatter. Co-polarization backscattering coefficients and polarimetric correlation backscattering coefficients are obtained form Radarsat-2 single-look complex (SLC) data.The maximum likelihood estimation is used to gain the initial results followed by the coarse spatial filtering and fine spatial filtering. Wind direction accuracy of the final inversion results is 10.67 with a wind speed accuracy of 0.32 m/s. Unlike previous methods, the methods described in this article utilize the SAR data itself to obtain the wind vectors and do not need external wind directional information. High spatial resolution and high accuracy are the most important features of the method described herein since the use of full polarimetric observations contains more information about the space measured. This article is a useful addition to the work of independent SAR wind retrieval. The experimental results herein show that it is feasible to employ the co-polarimetric backscattering coefficients and the polarimetric correlation backscattering coefficients for coastal wind field retrieval.

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China, which was launched on 16th August 2011. A scanning microwave radiometer (RM) is carried for sea surface temperature (SST), sea surface wind speed, columnar water vapor and columnar cloud liquid water detection. In this paper, the initial SST product of RM was validated with in-situ data of National Data of Buoy Center (NDBC) mooring and Argo buoy. The validation results indicate the accuracy of RMSST is better than 1.7°C. The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed. Then, the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements. Based on the results of assessment and errors analysis, the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.