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1.
Compared with traditional real aperture microwave radiometers, one-dimensional synthetic aperture microwave radiometers have higher spatial resolution. In this paper, we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz, 10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence angles. We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature. The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature.Then, a backpropagation(BP) neural network algorithm, a random forest(RF) algorithm and two multiple linear regression algorithms(RE1 and RE2) were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°–65°. The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise. The BP achieves the lowest retrieval errors at all incidence angles. The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.  相似文献   

2.
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   

3.
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   

4.
A retrieval algorithm of arctic sea ice concentration (SIC) based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness tempe...  相似文献   

5.
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   

6.
1IntroductionRemote sensingis an effective approach for esti-mation of the sea surface temperature(SST),andadvanced very high resolution radiometer(AVHRR)and moderate resolution imaging spectroradiometer(MODIS)thermal infared(TIR)data are widelyused in th…  相似文献   

7.
Several remotely sensed sea surface salinity(SSS) retrievals with various resolutions from the soil moisture and ocean salinity(SMOS) and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles(S) using multilinear regressions. The performance is evaluated using a total root mean square(RMS) error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°,which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.  相似文献   

8.
For the application of soil moisture and ocean salinity(SMOS) remotely sensed sea surface salinity(SSS) products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere(negative bias) and along the southern,northern and some other oceanic margins(positive or negative bias).The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature(TB) reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.  相似文献   

9.
Based on 5 831 continuous in situ measurements of the partial pressure of carbon dioxide on the sea surface p(CO2),related parameters of the sea surface temperature(SST) and chlorophyll-a(Chl a) concentration in 2010 winter,spring and summer of the Huanghai Sea and the Bohai Sea,the inherent relations among them are investigated preliminarily.This study reveals that the seasonal variability of SST and Chl a concentration has a significant influence on p(CO2).The authors have proposed a new algorithm to estimate p(CO2) from SST and Chl a concentration measurements.Compared with the vessel data,the root mean square error(RMSE) of p(CO2) retrieved by using the new model is 13.45 μatm(1atm=101.325 kPa) and the relative error is less than 4%.Then,SST and Chl a concentration data observed by satellite are used to retrieve p(CO2) in the Huanghai Sea and the Bohai Sea;and a better accuracy can be obtained if the quality control for sea surface chlorophyll-a concentration observed by satellite is used.The RMSE of retrieved p(CO2) data with quality control and that without quality control are 15.82 μatm and 31.74 μatm,respectively.  相似文献   

10.
The European Space Agency will launch the first salinity satellite for remotely sensing the global soil moisture and ocean salinity (SMOS) at a sun-synchronous orbit in 2009. One of the payloads on the satellite is a synthetic aperture microwave radiometer (MIRAS), which is an innovative instrument designed as a two-dimensional (2D) interferometer for acquiring brightness temperature (TB) at L-band (1.4 GHz). MIRAS allows measuring TB at a series of incidences for full polarizations. As the satellite travels, a given location within the 2D field of view is observed from different incidence angles. The authors develop a new scheme to retrieve the sea-surface salinity (SSS) from SMOS’s TB at multi-incidence angles in a pixel, utilizing the properties of emissivity changing with incidence angles. All measurements of a given Stokes parameter in a pixel are first fitted to incidence angles in three order polynomial, and then the smoothed data are used for retrieving the SSS. The procedure will remove the random noise in TB greatly. Furthermore, the new method shows that the error in retrieved SSS is very sensitive to the system biases in the calibrated TB of the sensor, but the error in the retrieval is also a system bias, which can be corrected by post-launch validation. Therefore, this method may also serve as a means to evaluate the calibration precision in TB.  相似文献   

11.
一维综合孔径微波辐射计能够有效提高观测的空间分辨率,其观测入射角通常在0°~55°范围内变化。为了开发适用于一维综合孔径微波辐射计的海面温度反演算法,需要评估其观测亮温对海洋大气环境要素的敏感性。利用海面发射率模型和大气辐射传输模型,构建了适用于一维综合孔径微波辐射计的微波海洋大气辐射传输模式,研究了C波段垂直和水平极化微波辐射亮温在不同入射角下对海洋大气环境要素的敏感性变化情况,并定量计算了相应的敏感系数。结果表明:垂直和水平极化亮温对海洋大气环境要素的敏感性表现出不同的特性。随着入射角的增大,垂直极化亮温对海面温度的敏感性增强,对海面风场的敏感性相对减弱;水平极化亮温则相反。由大气水汽含量和云液态水含量误差引入的垂直和水平极化亮温误差随入射角增大而增大,但是,即使在55°的大入射角下垂直和水平极化亮温误差仍小于0.12 K。对于海面温度反演精度优于1 K的要求,一维综合孔径微波辐射计的测温精度需优于0.6 K。研究结果对于一维综合孔径微波辐射计海面温度反演算法的研究和载荷设计具有一定的理论指导意义。  相似文献   

12.
相比于实孔径微波辐射计,一维综合孔径微波辐射计具有高空间分辨率和多入射角观测特点。本文提出采用观测频率为6.9,10.65,18.7,23.8和36.5 GHz,且入射角范围为0°~65°的一维综合孔径微波辐射计遥感大气海洋环境要素。基于构建的微波大气海洋辐射传输正演模型,分析了辐射计亮温对大气海洋环境要素的敏感性,为辐射计关键指标确定和大气海洋环境要素反演算法设计提供技术支撑。结果表明:一维综合孔径微波辐射计的垂直和水平极化亮温对大气海洋环境要素的敏感性表现出不同特性,且敏感性随入射角的改变而变化显著;6.9和10.65 GHz对海面温度的敏感性较大,且随着入射角的增大,垂直极化亮温的敏感性增大,水平极化亮温的敏感性减小;10.65和18.7 GHz对海面风速的敏感性相对较大,且敏感性最大的风速区间位于10~20 m/s;23.8 GHz对大气水汽含量最敏感,且水汽含量较低、入射角较大时,敏感性越大;36.5 GHz对云液态水含量最敏感,随着入射角的增大,垂直极化亮温的敏感性减小,水平极化的敏感性增大,但两者均在液态水含量较小时表现出较大的敏感性。  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.
基于星载微波辐射计的海洋大气参数反演算法研究   总被引:4,自引:0,他引:4  
利用3个辐射传输模式对无冰无降水情况下的星载微波辐射计亮温测量进行仿真研究,通过模拟计算结果与同步卫星数据之间的比较分析,确定了用于反演算法研究的前向模式;利用该模式,提出了基于物理的星载微波辐射计海洋大气参数(包括海面风速、海表温度、大气垂直积分水汽量以及积分液态水量)多重线性回归算法。  相似文献   

15.
SARAL carried onboard a radar altimeter that provides very precise measurements of the sea surface height (SSH). Like other altimetric missions, SARAL carries a passive microwave radiometer (PMR) for wet tropospheric correction to SSH. In the present study, new algorithms are developed for the retrieval of cloud liquid water (CLW) and total precipitable water vapor (TPW) over the global oceans from PMR measurements of the brightness temperatures. A radiative transfer and genetic algorithm based retrieval scheme is proposed for the estimation of CLW and TPW from SARAL PMR. The comparisons of CLW from PMR with independent measurements from GPM-GMI and SSMIS within and outside ±40° latitudes show correlation (R) of 0.86 and 0.83, bias of 0.7 and ?3.61?mg/cm2, and root mean square error (RMSE) of 8.42 and 8.07?mg/cm2, respectively. Similarly, TPW from PMR with GPM-GMI and SSMIS show R of 0.99 and 0.98, bias of ?0.04 and ?0.03?g/cm2 and RMSE of 0.17 and 0.17?g/cm2, respectively. The retrieval accuracy of CLW and TPW from the new algorithms is compared with these parameters provided in the SARAL geophysical data records as finished products, which showed substantial improvement in the quality of the parameters from the new algorithm.  相似文献   

16.
HY-2卫星扫描微波辐射计数据反演北极海冰漂移速度   总被引:1,自引:1,他引:0  
本文基于最大互相关法,利用海洋二号(HY-2)卫星扫描微波辐射计37 GHz通道多时相垂直极化亮温数据,获取了北极海冰漂移速度。采用2012年和2013年国际北极浮标计划海冰现场观测数据,对利用微波辐射计亮温资料反演的冬季北极海冰漂移速度进行了定量验证,结果表明:流速和流向均方根误差分别为1.12 cm/s和16.37°,从一定程度上说明了HY-2卫星扫描微波辐射计亮温数据反演海冰漂移速度的可行性。此外,使用美国国防气象卫星F-17搭载的专用微波成像仪91 GHz通道垂直极化亮温,采用高斯拉普拉斯滤波方法进行处理,结合最大互相关法反演的海冰漂移速度,优于法国海洋开发研究院海冰漂移速度产品。  相似文献   

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