Xuetong Xie

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.

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.

A modified wind vector retrieval algorithm for polarimetric scatterometer

Experiments and theoretical analysis demonstrate that the polarimetric scatterometer has the potential in enhancing the accuracy of the wind vector retrieval. However, currently, there is no special wind vector retrieval algorithm for the polarimetric scatterometer. Based on the distribution characteristic of the objective function, a modified wind vector retrieval algorithm was designed for the conically scanning polarimetric scatterometer in this paper. Simulation experiments indicated that this algorithm could further improve the retrieval precision of the polarimetric scatterometer in comparison with the traditional algorithm, especially in the nadir- and outer-swath. By extending the wind direction range for the first and second ambiguity in the nadir- and outer-swath, the algorithm can effectively reduce the uncertainty of the wind direction solutions with error magnitude of 0° to 15°. Up to 2° improvement in wind direction retrieval can be achieved in the nadir track.

Automated typhoon identification from quikscat wind data

An automated typhoon identification algorithm using QuikSCAT wind data is developed. The histogram features of the wind speed and wind direction of typhoon is used for a coarse identification, and then a more precise identification which makes use of the circulation property of typhoon is applied to the wind data which can pass the coarse identification, so that the typhoon observed by QuikSCAT can be identified automatically. As an example, the identification method is applied to identify typhoon Morakat 2009 from a sequence of QuikSCAT wind data distributed by PO.DACC, the results show that the typhoon can be correctly identified with our method, which demonstrates the feasibility and usefulness of our method.

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.

A Novel Integrated Algorithm for Wind Vector Retrieval from Conically Scanning Scatterometers

Due to the lower efficiency and the larger wind direction error of traditional algorithms, a novel integrated wind retrieval algorithm is proposed for conically scanning scatterometers. The proposed algorithm has the dual advantages of less computational cost and higher wind direction retrieval accuracy by integrating the wind speed standard deviation (WSSD) algorithm and the wind direction interval retrieval (DIR) algorithm. It adopts wind speed standard deviation as a criterion for searching possible wind vector solutions and retrieving a potential wind direction interval based on the change rate of the wind speed standard deviation. Moreover, a modified three-step ambiguity removal method is designed to let more wind directions be selected in the process of nudging and filtering. The performance of the new algorithm is illustrated by retrieval experiments using 300 orbits of SeaWinds/QuikSCAT L2A data (backscatter coefficients at 25 km resolution) and co-located buoy data. Experimental results indicate that the new algorithm can evidently enhance the wind direction retrieval accuracy, especially in the nadir region. In comparison with the SeaWinds L2B Version 2 25 km selected wind product (retrieved wind fields), an improvement of 5.1° in wind direction retrieval can be made by the new algorithm for that region.

A wind direction extension based algorithm for scatterometer wind vector retrieval

According to the lower efficiency and larger wind direction errors in the nadir region of the swath, a new combined wind retrieval algorithm is proposed for conically scanning scatterometer in this paper. The presented algorithm has the dual advantages of both higher efficiency and higher wind direction retrieval accuracy by combining the wind speed standard deviation algorithm and the wind direction interval retrieval(DIR) algorithm. It adopts wind speed standard deviation as criterion for searching possible wind vector solutions and retrieves potential wind direction interval for the first and second ambiguities based on the change rate of the wind speed standard deviation. Some SeaWinds L2A data and collocated buoy data were used to validate the algorithm. Retrieval experiments indicated that the algorithm can significantly reduce the wind direction retrieval errors in the nadir region.

Satellite SAR observation of the sea surface wind field caused by rain cells

Rain cells or convective rain, the dominant form of rain in the tropics and subtropics, can be easy detected by satellite Synthetic Aperture Radar (SAR) images with high horizontal resolution. The footprints of rain cells on SAR images are caused by the scattering and attenuation of the rain drops, as well as the downward airflow. In this study, we extract sea surface wind field and its structure caused by rain cells by using a RADARSAT-2 SAR image with a spatial resolution of 100 m for case study. We extract the sea surface wind speeds from SAR image by using CMOD4 geophysical model function with outside wind directions of NCEP final operational global analysis data, Advance Scatterometer (ASCAT) onboard European MetOp-A satellite and microwave scatterometer onboard Chinese HY-2 satellite, respectively. The root-mean-square errors (RMSE) of these SAR wind speeds, validated against NCEP, ASCAT and HY-2, are 1.48 m/s, 1.64 m/s and 2.14 m/s, respectively. Circular signature patterns with brighter on one side and darker on the opposite side on SAR image are interpreted as the sea surface wind speed (or sea surface roughness) variety caused by downdraft associated with rain cells. The wind speeds taken from the transect profile which superposes to the wind ambient vectors and goes through the center of the circular footprint of rain cell can be fitted as a cosine or sine curve in high linear correlation with the values of no less than 0.80. The background wind speed, the wind speed caused by rain cell and the diameter of footprint of the rain cell with kilometers or tens of kilometers can be acquired by fitting curve. Eight cases interpreted and analyzed in this study all show the same conclusion.

A study on wind vector retrieval algorithm for rotating fan-beam scatterometer

Rotating fan-beam scatterometer (RFSCAT) is a new type of satellite scatterometer that was proposed about one decade ago.However, just as other rotating scatterometers, relatively larger wind retrieval errors occur in the nadir and outer regions than in the middle regions of the swath. In order to address this problem, a modified wind vector retrieval algorithm for RFSCAT is presented in this paper. The new algorithm is featured with adaptively extending the range of wind direction for each wind vector cell position across the whole swath according to the distribution histogram of the retrieved wind direction bias. Simulation experiments demonstrated that the new established algorithm can effectively improve the wind direction retrieval accuracy in the nadir and outer regions of the RFSCAT swath.