Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.

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.

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.

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

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.

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.

Coherent Doppler lidar wind retrieval for a typhoon based on the genetic simulated annealing algorithm

A method of spectrum estimation based on the genetic simulated annealing(GSA)algorithm is proposed,which is applied to retrieve the three-dimensional wind field of typhoon Nangka observed by our research group.Compared to the genetic algorithm(GA),the GSA algorithm not only extends the detection range and guarantees the accuracy of retrieval results but also demonstrates a faster retrieval speed.Experimental results indicate that both the GA and GSA algorithms can enhance the detection range by 35%more than the least squares method.However,the convergence speed of the GSA algorithm is 17 times faster than that of the GA,which is more beneficial for real-time data processing.

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.

A Method for Sea Surface Wind Field Retrieval from SAR Image Mode Data

To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions （GMFs） have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by com-bining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval re-suits by a combination method （CMOD5 and CMOD4） together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error （RMSE） of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.

Wind vector retrieval algorithm from spaceborne lidar data

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.

An Integrating VAP Method for Single-Doppler Radar Wind Retrieval

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 only two neighboring azimuthal data are used, the IVAP becomes the VAP. The frequency response function of IVAP indicates that the IVAP method can filter out shortwaves, and a larger azimuthal interval leads to stronger filtering ability, therefore a smoother retrieved wind field. The shortwave filter function of the IVAP method is tested by an ideal experiment wherein the radar observations are artificially created by a uniform flow superposed with random disturbances. The VAP and IVAP methods are used in wind retrieval, respectively, and give different results for different azimuthal intervals （i.e., 6°, 12°, 24°, and 48°）. Because the VAP method is sensitive to small disturbances, the retrieved winds have larger errors for all different azimuthal intervals. However, the retrieved wind by the IVAP method has smaller errors when the azimuthal interval is larger due to its shortwave filter function. An experiment for an idealized linear wind field is also carried out to demonstrate the effect of the retrieval azimuthal interval on the IVAP method. The results show that a short interval gives the retrieval close to the ＂true＂ wind field with a linear distribution. When increasing the interval, the retrieval is smoothed and can represent only the mean wind field.

An Improved Method for Doppler Wind and Thermo dynamic Retrievals

A variational method is developed to retrieve winds in the first step and then thermodynamic fields in the second step from Doppler radar observations. In the first step, wind fields are retrieved at two time levels: the beginning and ending times of the data assimilation period, simultaneously from two successive volume scans by using the weak form constraints provided by the mass continuity and vorticity equations. As the retrieved wind fields are expressed by Legendre polynomial expansions at the beginning and ending times, the time tendency term in the vorticity equation can be conveniently formulated, and the retrieved winds can be compared with the radar observed radial winds in the cost function at the precise time and position of each radar beam. In the second step, the perturbation pressure and temperature fields at the middle time are then derived from the retrieved wind fields and the velocity time tendency by using the weak form constraints provided by the three momentum equations. The merits of the new method are demonstrated by numerical experiments with simulated radar observations and compared with the traditional least squares methods which consider neither the precise observation times and positions nor the velocity time tendency. The new method is also applied to real radar data for a heavy rainfall event during the 2001 Meiyu season in China.

Sea surface wind speed retrieval under rain with the HY-2 microwave radiometer

As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer（RM） loaded on HY-2 satellite, the sensitivity of some brightness temperature（TB）channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with Wind Sat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.

A Physics-Based Dual-Frequency Approach for Altimeter Wind Speed Retrieval

The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future 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.

The Application of Sea-Surface Wind Detection with Doppler Lidar in Olympic Sailing

The mobile incoherent Doppler lidar （MIDL）, which was jointly developed by State Key Laboratory of Severe Weather （LaSW） of the Chinese Academy of Meteorological Sciences （CAMS） and Ocean University of China, provided meteorological services during the Olympic sailing events in Qingdao in 2008. In this study, two experiments were performed based on these measurements. First, the capabilities of MIDL detection of sea-surface winds were investigated by comparing its radial velocities with those from a sea buoy. MIDL radial velocity was almost consistent with sea-buoy data; both reflected the changes in wind with time. However, the MIDL data was 0.5 m s-1 lower on average than the sea-buoy data due to differences in detection principle, sample volume, sample interval, spatial and temporal resolution. Second, the wind fields during the Olympic sailing events were calculated using a four-dimensional variation data assimilation （4DVAR） algorithm and were evaluated by comparing them with data from a sea buoy. The results show that the calculations made with the 4DVAR wind retrieval method are able to simulate the fine retrieval of sea-surface wind data--the retrieved wind fields were consistent with those of sea-buoy data. Overall, the correlation coefficient of wind direction was 0.93, and the correlation coefficient of wind speed was 0.70. The distribution of retrieval wind fields was consistent with that of MIDL radial velocity; the root-mean-square error between them had an average of only 1.52 m s-1^.

Comparison of two wind algorithms of ENVISAT ASAR at high wind

Two wind algorithms of ENVISAT advanced synthetic aperture radar （ASAR）, i. e. CMOD4 model from the European Space Agency （ESA） and CMOD_IFR2 model from Quilfen et al., are compared in this paper. The wind direction is estimated from orientation of low and linear signatures in the ASAR imagery. The wind direction has inherently a 180° ambiguity since only a single ASAR image is used. The 180° ambiguity is eliminated by using the buoy data from the NOAA （National Oceanic and Atmospheric Administration） buoys moored in the Pacific. Wind speed is obtained with the two wind algorithms using both estimated wind direction and normalized radar cross section （NRCS）. The retrieved wind results agree well with the data from Quikscat. The root mean square error （RMSE） of wind direction is 2.80°. The RMSEs of wind speed from CMOD4 model and CMOD_IFR2 model are 1.09 m/s and 0.60 m/s, respectively. The results indicate that the CMOD_IFR2 model is slight better than CMOD4 model at high wind.

Remote Sensing of Sea Surface Wind of Hurricane Michael by GPS Reflected Signals

In this paper, the propagating geometry and the w av eform of the GPS reflected signals are expatiated in detail. Furthermore, the pr inciple and the method of retrieving sea surface wind are presented. In order to test the feasibility of retrieval, the experiment data obtained by NASA in Hurr icane Michael are used. The result shows that the retrieval accuracy of wind spe ed is about 2 m/s.

WIND SHEAR IDENTIFICATION WITH THE RETRIEVED WIND OF DOPPLER WEATHER RADAR

Wind shear reflects that the wind field is not uniform, which is one of the primary factors which make the retrieval of the wind field difficult. Based on volume velocity process(VVP) wind field retrieval technique, the intensity of wind shear is identified in this paper. After analyzing the traditional techniques that rely on the difference of radial velocity to identify wind shear, a fixed difference among radial velocities that may cause false identification in a uniform wind field was found. Because of the non-uniformity in wind shear areas, the difference of retrieved results between surrounding analysis volumes can be used as a measurement to show how strong the wind shear is. According to the analysis of a severe convective weather process that occurred in Guangzhou, it can be found that the areas of wind shear appeared with the strength significantly larger than in other regions and the magnitude generally larger than4.5 m/(s·km). Besides, by comparing the variation of wind shear strength during the convection, it can be found that new cells will be more likely to generate when the strength is above 3.0 m/(s·km). Therefore, the analysis of strong wind shear's movement and development is helpful to forecasting severe convections.

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

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.

STRUCTURE OF MESO-β AND –γ-SCALE ON SOUTH CHINA HEAVY RAINFALL ON 12～13 JUNE 2005 USING DUAL-DOPPLER RADAR

The three-dimensional wind fields of the heavy rain on 12-13 June 2005 in Guangdong province are retrieved and studied with the volume scan data of the dual-Doppler radar located in the cities of Meizhou and Shantou. It is shown that the meso-β-scale and meso-γ-scale convergence lines located in the convective system at the low and middle layer play an important role in the heavy rainfall. The convergence line is the initiating and maintaining mechanism of the rain. A three dimensional kinematic structure model is also given.