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Chinese Physics B 2011年第3期20卷 274-283页

作者：钟剑黄思训杜华栋张亮 Institute of Meteorology PLA University of Science and Technology

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.

关键词： scatterometer variational optimization analysis wind retrieval regularization method

wind vector retrieval algorithm from spaceborne lidar data

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Acta Oceanologica Sinica 2014年第3期33卷 129-135页

作者： WANG Tianyu PAN Delu HE Xianqiang WANG Difeng State Key Laboratory of Satellite Ocean Environment Dynamics the Second Institute of OceanographyState Oceanic Administration

The principal purpose of this paper is to extract entire sea surface wind＇s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white caps and subsurface water. wind speeds are obtained through empirical relationship with sea surface mean square slopes. wind directions are derived from relationship between wind speeds and wind directions im plied in CMOD5n geophysical models function （GMF）. Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted （IDW） from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC＇s TAO buoy-laying area as survey region in camparison with buoys＇ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error （RMSE） less than 2m/s and wind direction＇s RMSE less than 21 degree.

关键词： remote sensing spaceborne Lidar wind retrieval GMF

An Integrating VAP Method for Single-Doppler Radar wind retrieval

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Acta meteorologica Sinica 2009年第2期23卷 166-174页

作者：梁旭东王斌 Laboratory of Typhoon Forecast Technique Shanghai Typhoon Institute of CMA LASG Institute of Atmospheric PhysicsChinese Academy of Sciences

Some traditional methods, such as the velocity-azimuth display （VAD） and the velocity-azimuth processing （VAP）, have been widely used to retrieve the 3-D wind field from single-Doppler radar data because of their relative conceptual and practical simplicity. The advantage of VAD is that it is not affected by small-scale perturbations of the radial wind along the azimuth, to which the VAP method is very sensitive. Nevertheless, the spatial resolution of the VAD method is very poor compared to the VAP method. We show, in this study, that these two retrieval methods are actually related with each other and they are two special applications of a retrieval function based on the azimuthal uniform-wind assumption for a given azimuthal interval [01,02]. When using this retrieval function to retrieve wind fields, the azimuthal interval used in retrieval can be adjusted according to the requirement of smoothness or resolution. The larger （smaller） the azimuthal interval is, the coarser （finer） the horizontal resolution of retrieved wind field is, and the more insensitive （sensitive） the retrieval method is to small-scale perturbations. Because the full information within the azimuthal interval [01,02], instead of the information at two terminal points only, i.e., azimuths 01 and 02, is used to retrieve the wind fields, this method is referred to as the integrating VAP （IVAP） method, wherein the horizontal wind field is retrieved by using the Doppler velocity over the part of circumference, delimited by the given azimuthal interval times the scan radius. By contrast, the VAP method uses only the velocities at two terminal points of the given azimuthal interval. Therefore, the IVAP method has a filtering function, and the filtering rate can be controlled by adjusting the azimuthal interval. The filter such as that used in the pre-processing of the VAP method is no longer necessary for the IVAP method. When the retrieval azimuthal interval is as large as a whole circumference, the IVAP becomes the VAD. On the other hand, if

关键词： Doppler radar wind retrieval integrating velocity-azimuth processing （IVAP） velocity-azimuth display （VAD）

A high wind geophysical model fuction for Quik SCAT wind retrievals and application to Typhoon IOKE

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Acta Oceanologica Sinica 2015年第7期34卷 65-73页

作者： ZOU Juhong ZENG Tao CUI Songxue National Satellite Ocean Application Service State Oceanic Administration

The geophysical model function （GMF） describes the relationship between a backscattering and a sea surface wind, and enables a wind vector retrieval from backscattering measurements. It is clear that the GMF plays an important role in an ocean wind vector retrieval. The performance of the existing Ku-band model function QSCAT-1 is considered to be effective at low and moderate wind speed ranges. However, in the conditions of higher wind speeds, the existing algorithms diverge alarmingly, owing to the lack of in situ data required for developing the GMF for the high wind conditions, the QSCAT-1 appears to overestimate the a0, which results in underestimating the wind speeds. Several match-up QuikSCAT and special sensor microwave/imager （SSM/I） wind speed measurements of the typhoons occurring in the west Pacific Ocean are analyzed. The results show that the SSM/I wind exhibits better agreement with the ＂best track＂ analysis wind speed than the QuikSCAT wind retrieved using QSCAT-1. On the basis of this evaluation, a correction of the QSCAT-1 model function for wind speed above 16 m/s is proposed, which uses the collocated SSM/I and QuikSCAT measurements as a training set, and a neural network approach as a multiple nonlinear regression technologytechnology.In order to validate the revised GMF for high winds, the modified GMF was applied to the QuikSCAT observations of Hurricane IOKE. The wind estimated by the QuikSCAT for Typhoon IOKE in 2006 was improved with the maximum wind speed reaching 55 m/s. An error analysis was performed using the wind fields from the Holland model as the surface truth. The results show an improved agreement with the Holland model wind when compared with the wind estimated using the QSCAT-1. However, large bias still existed, indicating that the effects of rain must be considered for further improvement.

关键词： geophysical model function high wind QuikSCAT neural network wind retrieval

Kinematic Features of a Bow Echo in Southern China Observed with Doppler Radar

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Advances in Atmospheric Sciences 2013年第6期30卷 1535-1548页

作者：彭新东张人禾王红艳 State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences

A bow echo is a type of mesoscale convective phenomenon that often induces extreme weather and appears with strong reflectivity on radar images. A strong bow echo that developed from a supercell was observed over Foshan City in southern China on 17 April 2011. The intense gusty winds and showers caused huge losses of property and severely affected human lives. This paper presents an analysis of this strong meso- n-scale convective system based on Doppler radar observations. The isolated bow echo exhibited a horizontal scale of about 80 km in terms of reflectivity above 40 dBZ, and a life span of 8 hours. The system originated from the merging of a couple of weakly organized cells in a shear line, and developed into an arch shape as it moved through the shear zone. Sufficient surface moisture supply ensured the convective instability and development of the bow echo. The low-altitude winds retrieved from single Doppler radar observations showed an obvious rear-inflow jet along the notch area. Different from the conventional definition, no book- end anticyclone was observed throughout the life cycle. Very strong slantwise updrafts and downdrafts were recognizable from the retrieved winds, even though the spatial scale of the bow echo was small. Strong winds and induced damage on the surface are considered to have been caused by the mid-level rear-inflow jet and intense convective downdrafts.

关键词： bow echo kinematic features Doppler radar wind retrieval

Astudyofanewretrievalalgorithmformeasurementofoceanicwindvectorsfieldusingsatellitemicrowavescatterometer

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Acta Oceanologica Sinica 1998年第3期17卷 305-309页

作者： Lin Mingsen Sun Ying Zheng Shuqing(Received February 10, 1997 accepted June 9, 1997) Third Institute of Oceanography State Oceanic Administration Xiamen 361005 China

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.

关键词： SASS wind retrieval wind direction alias removal scatterometer