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1.
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 RM SST 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.  相似文献   

2.
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.  相似文献   

3.
Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher,which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity(SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation(SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2–year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e–4, and the RMSE is slightly larger than 1e–3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected,and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.  相似文献   

4.
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 3 m/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.  相似文献   

5.
全球有效波高和风速的时空变化及相关关系研究   总被引：2，自引：1，他引：1  
The climatology of significant wave height（SWH） and sea surface wind speed are matters of concern in the fields of both meteorology and oceanography because they are very important parameters for planning offshore structures and ship routings. The TOPEX/Poseidon altimeter, which collected data for about 13 years from September 1992 to October 2005, has measured SWHs and surface wind speeds over most of the world＇s oceans. In this paper, a study of the global spatiotemporal distributions and variations of SWH and sea surface wind speed was conducted using the TOPEX/Poseidon altimeter data set. The range and characteristics of the variations were analyzed quantitatively for the Pacific, Atlantic, and Indian oceans. Areas of rough waves and strong sea surface winds were localized precisely, and the correlation between SWH and sea surface wind speed analyzed.  相似文献   

6.
基于浮标实测数据的WindSat海洋反演产品精度分析   总被引：1，自引：1，他引：0  
To evaluate the ocean surface wind vector and the sea surface temperature obtained from Wind Sat, we compare these quantities over the time period from January 2004 to December 2013 with moored buoy measurements. The mean bias between the Wind Sat wind speed and the buoy wind speed is low for the low frequency wind speed product(WSPD_LF), ranging from –0.07 to 0.08 m/s in different selected areas. The overall RMS error is 0.98 m/s for WSPD_LF, ranging from 0.82 to 1.16 m/s in different selected regions. The wind speed retrieval result in the tropical Ocean is better than that of the coastal and offshore waters of the United States. In addition, the wind speed retrieval accuracy of WSPD_LF is better than that of the medium frequency wind speed product. The crosstalk analysis indicates that the Wind Sat wind speed retrieval contains some cross influences from the other geophysical parameters, such as sea surface temperature, water vapor and cloud liquid water. The mean bias between the Wind Sat wind direction and the buoy wind direction ranges from –0.46° to 1.19° in different selected regions. The overall RMS error is 19.59° when the wind speed is greater than 6 m/s. Measurements of the tropical ocean region have a better accuracy than those of the US west and east coasts. Very good agreement is obtained between sea surface temperatures of Wind Sat and buoy measurements in the tropical Pacific Ocean; the overall RMS error is only 0.36°C, and the retrieval accuracy of the low latitudes is better than that of the middle and high latitudes.  相似文献   

7.
This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.  相似文献   

8.
A new 0.1° gridded daily sea surface temperature(SST) data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave(Wind Sat, AMSR-E, ASMR2 and HY-2 A RM)and two infrared(MODIS and AVHRR) radiometers(RMs) based on the optimum interpolation(OI) method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error(RMSE) of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.  相似文献   

9.
基于一维综合孔径微波辐射计的海面温度反演研究   总被引：1，自引：0，他引：1  
Due to the low spatial resolution of sea surface temperature(T_S) retrieval by real aperture microwave radiometers,in this study, an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer, temporarily named 1 D-SAMR. Regarding the configuration of the radiometer, an angular resolution of 0.43° was reached by theoretical calculation. Experiments on sea surface temperature retrieval were carried out with ideal parameters; the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters. In the case of no auxiliary parameter errors, the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e., 0.710 6 K for the incidence angle of 35° under the radiometer calibration accuracy of0.5 K). While errors on auxiliary parameters are assumed to follow a Gaussian distribution, the greatest error on retrieved sea surface temperature was 1.330 5 K at an incidence angle of 65° in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s) over high W scene, for the radiometer calibration accuracy of 0.5 K.  相似文献   

10.
The in situ sea surface salinity(SSS) measurements from a scientific cruise to the western zone of the southeast Indian Ocean covering 30°–60°S, 80°–120°E are used to assess the SSS retrieved from Aquarius(Aquarius SSS).Wind speed and sea surface temperature(SST) affect the SSS estimates based on passive microwave radiation within the mid- to low-latitude southeast Indian Ocean. The relationships among the in situ, Aquarius SSS and wind-SST corrections are used to adjust the Aquarius SSS. The adjusted Aquarius SSS are compared with the SSS data from My Ocean model. Results show that:(1) Before adjustment: compared with My Ocean SSS, the Aquarius SSS in most of the sea areas is higher; but lower in the low-temperature sea areas located at the south of 55°S and west of 98°E. The Aquarius SSS is generally higher by 0.42 on average for the southeast Indian Ocean.(2) After adjustment: the adjustment greatly counteracts the impact of high wind speeds and improves the overall accuracy of the retrieved salinity(the mean absolute error of the Zonal mean is improved by 0.06, and the mean error is-0.05 compared with My Ocean SSS). Near the latitude 42°S, the adjusted SSS is well consistent with the My Ocean and the difference is approximately 0.004.  相似文献   

11.
HY-2微波辐射计降雨条件下海面风速反演算法研究   总被引：1，自引：0，他引：1  
由于降雨改变了海洋-大气的辐射/散射特性,长期以来星载遥感器在降雨条件下进行海面风速信息提取存在困难。本文针对自主海洋动力环境卫星海洋2号（HY-2）搭载的扫描微波辐射计,分析了不同频段亮温对降雨和海面风速敏感性,自此基础上获得了一种对降雨不敏感的亮温通道组合,该亮温通道组合对海面风速的敏感性甚至高于原有亮温通道。本文利用该亮温通道组合建立了降雨条件下的风速反演算法,并将反演结果与WindSat全天候风速产品、HY-2微波辐射计原有风速产品以及浮标实测数据进行了比较。结果表明本文算法在降雨条件下的反演误差小于2m/s,明显优于原有HY-2微波辐射计风速产品,验证了本文发展的算法在降雨条件下的风速反演能力。  相似文献   

12.
本文利用2016年的AMSR2、GMI、WindSat和HY-2A RM等星载微波辐射计海表温度（SST）数据，分析了北极卫星遥感SST数据的时空覆盖和产品精度情况。结果表明:北极星载微波辐射计SST冬季覆盖率和有效覆盖天数要低于夏季，GMI的SST有效覆盖率较低，AMSR2较高，联合使用AMSR2、GMI、WindSat和HY-2A RM星载微波辐射计SST数据，2月份覆盖率在12%~15%之间，有效观测天数优于26 d，8月份覆盖率全月高于26%，有效观测天数优于29 d。北极地区星载微波辐射计SST数据的误差均要大于全球平均水平，AMSR2数据精度较好，WindSat与AMSR2的精度相当，GMI的均方根误差约是AMSR2的2倍，HY-2A RM数据精度低于其他星载微波辐射计水平。  相似文献   

13.
为提高降雨条件下星载全极化微波辐射计海面风场精度，通过匹配WindSat海面风场和降雨率数据以及美国国家浮标中心浮标观测数据，得到18 996组匹配样本，深入分析了降雨对海面风场反演精度的严重影响，构建了风场校正模型。试验结果表明，降雨导致海面风速被严重高估，风向误差随着降雨率的增大而增大。校正后的风速精度在低风速段提升明显。无论降雨率多大，校正后风速精度均比校正前高。风速均方根误差由原来的2.9 m/s降低到了2.1 m/s，风向均方根误差由原来的26.9°降低到了26.3°。  相似文献   

14.
海面有效波高(H1/3)是表征海浪的重要参数,随着卫星遥感技术的发展,雷达高度计已成为获取海面有效波高的重要手段,但也只能对卫星星下点轨迹处进行有效观测,远无法满足大范围应用的需求.本研究结合2013年10月HY-2雷达高度计观测的海面有效波高和微波散射计观测的海面风场资料,分别对高、低风速下风浪数据进行拟合,建立了适用于0~40 m/s风速范围内的南海海域风浪关系模型,经模型比对和结果验证,结果表明,基于HY-2卫星数据分析建立的南海海域风浪关系模型是可信的,特别是低风速的风浪模型与实测数据建立的风浪模型具有很好的一致性;根据建立的风浪关系模型,从卫星散射计大面观测的海面风场出发,能推算出风浪条件下海面有效波高的大面信息,数据覆盖远高于卫星高度计的星下点观测,能为分析和预报海浪、风暴潮灾害提供大范围的海面有效波高信息.  相似文献   

15.
国内外对海上阵风的研究并不多,且大多集中在阵风预报和应用研究方面,对于海洋阵风数据的获取技术未见文献系统论述。本文利用HY-2B卫星雷达高度计观测的后向散射系数,结合校正微波辐射计观测的亮度温度信息,提出联合反演阵风风速的方法。两个遥感载荷联合反演得到的阵风风速与2019–2021年美国国家浮标数据中心（NDBC）浮标数据进行真实性检验,结果显示:阵风风速均方根误差（RMSE）为0.98 m/s,相关系数为0.82;基于本方法利用国外同类卫星Jason-3得到的阵风风速与2016–2018年NDBC浮标数据的RMSE为0.96 m/s,相关系数为0.88。本文在HY-2B卫星雷达高度计海面风速观测的基础上,纳入同一卫星平台校正微波辐射计的同步观测信息联合实现了海面阵风的观测,数据的比对结果证明文中方法具有较高的观测精度。同时,该方法对于具有相同观测体制的国内外卫星也适用。  相似文献   

16.
张婷  张杰  王进  孟俊敏 《海洋科学》2014,38(6):43-46
基于南海北部PY30-1平台上2012年2月至9月测风仪观测的风速数据,开展了HY-2扫描辐射计风速数据比较研究。选取时空匹配窗口为5 min和25 km,利用HY-2扫描辐射计RM 100,70和35 km分辨率3种风速数据,分别与平台观测数据进行了比较。比较结果表明:在南海北部海域,HY-2扫描辐射计100 km分辨率风速和平台观测风速的均方根偏差为3.86 m/s;70 km分辨率风速和平台观测风速的均方根偏差为10.52 m/s;35 km分辨率风速和平台观测风速的均方根偏差为5.54 m/s。还进一步比较了有雨和无雨两种情况下HY-2扫描辐射计和平台数据的偏差,结果表明:有雨和无雨条件下都是100 km分辨率的数据偏差最小。这为在我国南海北部海域应用HY-2扫描辐射计的风速数据产品的选择提供了依据。  相似文献   

17.
The scanning multichannel microwave radiometer (SMMR) is an imaging 5-frequency radiometer flown on the Seasat and Nimbus-7 earth satellites launched in 1978. It measures dual-polarized microwave radiances from the earth's atmosphere and surface, primarily for the purpose of deriving global and nearly all-weather measurements of sea surface temperature, wind speed, and atmospheric liquid water and water vapor. This paper describes the SMMR instrument and its calibration, antenna pattern measurements, and data processing procedures. Analysis of early data from the Seasat SMMR shows that the expected engineering performance in flight was achieved, and the measurement of sea surface temperature and wind speed with accuracies of 1.5 K and 2 m/s, respectively, may be achievable once the geophysical data processing algorithms and analysis have been completed.  相似文献   

18.
星载SAR对雨团催生海面风场的观测研究   总被引：2，自引：1，他引：1  
雨团或对流雨是热带与亚热带地区的主要降雨形式,较易被高分辨率星载合成孔径雷达（SAR）探测到。SAR图像上的雨团足印是由大气中雨滴的散射与吸收、下沉气流等共同导致形成的。本文以RADARSAT-2卫星100 m分辨率的SAR图像上雨团引起的海面风场及其结构反演与解译作为实例进行分析。使用CMOD4地球物理模式函数,分别以NCEP再分析数据、欧洲MetOp-A卫星先进散射计（ASCAT）和中国HY-2卫星微波散射计的风向为外部风向,进行了SAR图像的海面风场反演。反演的海面风速相对于NCEP、ASCAT和HY-2的均方根误差（RMSE）分别为1.48 m/s,1.64 m/s和2.14 m/s。SAR图像上一侧明亮另一侧昏暗的圆形信号图斑被解译为雨团携带的下沉气流对海面风场（海面粗糙度）的改变所致。平行于海面背景风场其通过雨团圆形足印中心的剖面上的风速变化可拟合为正弦或余弦曲线,其拟合线性相关系数均不低于0.80。背景风场的风速大小、雨团引起的风速大小以及雨团足印的直径可利用拟合曲线获得,雨团足印的直径大小一般为数千米或数十千米,本文的8例个例解译与分析均验证了该结论。  相似文献   

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