南海海表面温度的季节内变化特征

基于TRMM/TMI卫星遥感海表面温度(SST)数据,采用谐波分析方法和经验正交函数分解(EOF)方法对南海SST的季节内变化规律进行了分析,探讨了其对声速变化规律的影响。结果表明:南海SST季节内空间分布的第一模态呈现南北负正反对称分布;第二模态的空间分布为以越南外海的负值为中心。分析相应的时间系数功率谱可知其显著周期为5、6、8、11、12周。分析表明SST的季节内振荡与纬向风分量、经向风应力有密切关系。探讨潜热通量可发现其显著周期为54～69天,存在显著的季节内变化;冬夏季变化的最大区域分别集中在越南外海和南海北部,且第一模态的时间函数与潜热通量的最大相关系数可达到40%,相关系数的大值区域主要集中在越南上升流区域。南海海表声速较大但随季节变化不明显,与温度同相变化与盐度反相变化。     

MODIS 3A遥感图像的均值融合研究与应用

利用MODIS卫星资料分析研究海洋环境的变化时,需将多幅图像或数据进行融合处理.首先介绍了Terra和Aqua MODIS卫星数据均值融合算法,然后利用该算法分析了2006年热带风暴 "PRAPIROON"前后海表温度的变化,结果表明,南海北部研究海域海表温度在热带风暴"PRAPIROON"前平均为27. 12℃,热带风暴期间平均为25. 18℃,平均下降1. 94℃,区域海域个别点降幅接近10℃,且研究区域海表温度的变化具有非均匀性.该方法不仅可利用多源MOIDS卫星遥感资料反应一定时期研究海域海温的变化程度,还可分析不同区域变化的差异性,对于研究其它海洋或陆地环境参量变化具有一定的应用价值.     

FY-3D MWRI在轨交叉辐射定标和海表温度反演

海表温度(sea surface temperature,SST)在气候监测、海洋学研究、渔业经济研究和污染监测等多个方面起着重要作用。本文利用风云三号D星(FY-3D)微波成像仪(Microwave Radiation Imager, MWRI)数据对海表温度进行了反演。首先,以全球降水测量(Global Precipitation Measurement, GPM)卫星微波成像仪(GPM Microwave Imager, GMI)作为参考传感器,采用基于海洋微波辐射传输模型(radiative transfer model, RTM)的双差异方法对FY-3D MWRI进行交叉辐射定标,消除了其在轨辐射定标偏差,为精确反演海表温度奠定了基础;然后,在波段选择的基础上提出耦合微波海表发射率的海表温度多波段反演新算法,与传统的多波段反演算法相比,新反演算法的均方根误差从0.74 K减少至0.69 K;最后,用新反演算法从2020年的FY-3D MWRI数据反演得到全球的海表温度,并用时空匹配的iQuam浮标数据和GMI海表温度产品对反演结果进行精度验证,误差分别为0.04±1.13 K...     

南海海温年际变化的均方差分析

利用新的SODA海表温废资料,研究了2002～2007年南海表层水温（SST）的均方差特征,探讨其对声速变化的影响。分析结果表明：在所选取的南海海域中,南海SST均方差随季节和纬度都有所变化,整个南海SST均方差值变化范围为1—6。1～3月高于18°N海域,海温年际变化较大,基本接近4．低于18°N海域均方差值随月份减弱;4～6月南海海域海温年际变化小,随月份和纬度增大而略微增大;7~9月海温变化不明显,基本保持同样的变化趋势;10～12月在高于12°N附近海域,海温均方差值先变小,到12月份又开始增大,低于120N附近海域,均方差值保持在1左右变化。南海海表声速较大,但随季节变化不明显,夏、秋两季比春、冬两季较高。     

近40年中国区域对流层顶温度场时空变化特征

利用1981—2020年NCEP/NCAR再分析月平均资料,对中国区域近40年的对流层顶温度场进行了时空变化特征分析和四季变化状况研究。采用线性回归、Mann-Kendall突变检验分析、经验正交分解(EOF)等方法研究了对流层顶温度场的年际变化趋势和时空分布特征。结果表明：中国区域对流层顶温度在1981—2020年总体呈下降趋势,其中在1995—2020年减少趋势显著。对流层顶温度存在明显的季节性特征,春季和冬季气候倾向率较小,对全年对流层顶温度减小趋势贡献也较小;夏季和秋季气候倾向率较大,对全年对流层顶温度减小趋势贡献也较大。运用EOF法对对流层顶温度场空间变化特征分析发现,第一模态空间分布反映了中国区域对流层顶变化趋势在空间上基本一致,且分布由南到北呈现“+,-”的纬向结构;第二模态空间分布由南到北呈现“+,-,+,-”的纬向结构,并以34°N为界呈现出很明显的南北相反分布;第三模态空间分布由南到北呈现“+,-,+”的纬向结构。     

0.4~14 μm中国海域海表反照率时空分布特性

复杂海洋环境是空间光电探测的典型应用场景,可见至长波红外波段海表反照率参数是海洋大气传输与背景辐射特性研究的重要内容。鉴于目前中国海域海表反照率数据缺乏的现状,在多源卫星长时间观测海洋环境特性参数数据的统计分析基础上,通过考虑海水叶绿素含量、气溶胶光学厚度、海表面风速和太阳入射角度等参数的复合影响,建立了海表反照率的快速参数化应用模式,获得了中国南海、东海、黄海和渤海等典型海域0.4~14m海表反照率谱线,掌握了海表反照率的时空分布特征,为海空光电工程应用提供基础数据支撑。     

太阳辐射对直升机整机红外辐射特性影响的数值研究EI北大核心CSCD

太阳辐射对飞行中的直升机局部蒙皮有加热作用,从而改变整机红外辐射的分布特征。构建了包含直升机机身蒙皮、主旋翼、发动机机匣以及排气系统的物理模型,综合考虑发动机机匣、排气系统与发动机舱蒙皮的换热,耦合直升机前飞来流、旋翼下洗气流、尾桨气流,以时刻、季节、直升机朝向为变量,计算分析太阳辐射对直升机8~14μm波段红外辐射特性的作用规律。计算结果表明:夏季正午太阳直射可使机身向阳面整体升温20 K以上,局部最高可达25 K。直升机向阳面机身蒙皮8~14μm波段红外辐射强度在全天变化趋势呈山峰状,其峰值出现在12点前后。越靠近机身顶部向阳面,太阳辐射对8~14μm波段红外辐射强度增强作用越显著,最高可达25%。以冬季为基准,秋分、春分、夏至时的整机红外辐射分别增加7%、11%、21%左右。除夏季外,其他季节的机身两侧8~14μm波段红外辐射强度分布都呈现不对称性,春、秋两季两侧相差在5%左右,冬季在6.5%左右。整体上,夏季上午10点的太阳辐射对不同飞行方向的直升机8~14μm波段红外辐射强度分布影响较小。     

单通道物理法反演海表温度的参数敏感性分析及验证

定量分析了反演海表温度的单通道物理法对海水比辐射率、海面风速、海水盐度、大气透过率、大气上下行辐射等参数的敏感性,发现海水比辐射率、大气透过率对算法精度影响较大,是单通道物理法反演海表温度的主要误差来源.在不同的波段,单通道物理法对参数敏感性也有较大差别,中红外波段的敏感性要小于热红外波段.为了验证单通道物理法的可行性、精度及参数敏感性分析的结果,选择墨西哥湾海域2009年全年夜间MODIS实测数据进行实验.结果表明,中红外波段的单通道物理法反演海表温度的精度高于热红外波段,达到MODIS劈窗算法海表温度标准产品同等精度,这与参数敏感性分析的结果一致.由于中红外波段单通道物理法精度较高,一方面,可以满足常规的业务观测需求,为海表温度反演提供新的技术手段;另一方面,可用来标定劈窗算法系数,弥补海洋现场观测站位空间分布不足的问题.     

基于MERIS数据的渤海海表盐度反演北大核心CSCD

盐度是重要的物理海洋参数,会影响海洋许多过程。基于渤海实测的海表盐度和MERIS卫星获取的遥感反射率数据,建立并检验了一种多元线性模型和人工神经网络模型。经检验,两种模型的反演均方根误差分别为0.858psu和0.689psu(psu为实用盐度单位),对应的相关系数分别为R2=0.81和R2=0.82。将模型应用于MERIS遥感数据,获取了渤海海表盐度图,能够体现渤海海表盐度的空间分布情况。两种模型均可适用于多光谱遥感数据。     

中国低纬(海南)电离层漂移特性

为了研究中国低纬地区的电离层动力学特征,对2002年3月～2004年3月期间海南地区的电离层等离子体漂移观测资料进行了分析研究.结果表明:磁宁静时海南地区的电离层漂移日间垂直方向变化较为规则,季节变化不大,漂移速度通常向上,大小为0～20m/s,随季节变化;晚间垂直方向漂移变化较为复杂,漂移速度以向下为主,随月份和季节变化较大;水平方向漂移速度通常在50～100m/s左右,在日出日落时可达150～200m/s,甚至高达300m/s,且在南北方向和东西方向的漂移速度表现不同.这些特征与经度相差几乎180°的赤道区Jicamarca台站观测到的漂移特征对比,显示了较大的区域差别.     

Deriving Sea Surface Salinity and Density Variations From Satellite and Aircraft Microwave Radiometer Measurements: Application to Coastal Plumes Using STARRS

Using brightness temperature Tb measurements from L-band airborne microwave radiometers, with independent sea surface temperature (SST) observations, sea surface salinity (SSS) can be remotely determined with errors of about 1 psu in temperate regions. Nonlinearities in the relationship between Tb, SSS, and SST produce variations in the sensitivity of salinity S to variations in Tb and SST. Despite significant efforts devoted to SSS remote sensing retrieval algorithms, little consideration has been given to deriving density D from remotely sensed SSS and SST. Density is related to S and T through the equation of state. It affects the ocean's static stability and its dynamical response to forcings. By chaining together two empirical relationships (flat-sea emissivity and equation of state) to form an inversion algorithm for sea surface density (SSD) in terms of Tb and SST, we develop a simple L-band SSD retrieval algorithm. We use this to investigate the sensitivity of SSD retrievals to observed Tb and SST and infer errors in D for typical sampling configurations of the airborne Salinity, Temperature, And Roughness Remote Scanner (STARRS) and satellite-borne Soil Moisture and Ocean Salinity (SMOS) and Aquarius radiometers. We then derive D from observations of river plumes obtained using STARRS and demonstrate several oceanographic applications: the observations are used to study variations in T and S effects on D in the Mississippi plume, and the across-shelf density gradient is used to infer surface geostrophic shear and subsurface geostrophic current in the Plata plume. Future basin-scale applications of SSD retrievals from satellite-borne microwave radiometers such as SMOS and Aquarius are anticipated.     

Detection of Sea Surface Temperature (SST) Using Infrared Band Data of Advanced Very High Resolution Radiometer (AVHRR) in the Gulf of Finland

This paper presents the detection of sea surface temperature (SST) in the Gulf of Finland using infrared band data of Advanced Very High Resolution Radiometer (AVHRR). AVHRR imagery is evaluated as a main data source for monitoring SST as a measure of upwelling's dynamic. Sea surface effects (SSE), however, cause a temperature difference between the sea surface skin and water below the surface. Therefore, SSE is taken into account as one of the major error factors in the SST esimation. Further studies will be investigated using both AVHRR and MODIS in the future.     

How Wind Affects Passive Microwave Measurements of Sea Surface Temperature

Uncertainty in the wind speed is a major source of error in passive microwave measurements from satellites of sea surface temperature (SST) because of the non-linear relationship between sea surface emissivity and wind speed. The accuracy of the SST measurement that can be achieved with only passive microwave measurements was assessed by computer modeling. Our investigation showed that the second-order terms must be included in the equation of radiative transfer in an analysis of the errors in the retrieved SST. In addition, we found that the effects of wind roughening and foam production should be treated separately. We have concluded that the accuracy of SST measurements would be improved by including data from an active remote-sensing instrument such as a scatterometer.     

A MODIS Sea Surface Temperature Composite for Regional Applications

Sea surface temperature (SST) is an important input for regional and global weather modeling, but timely high- resolution SST data from either in situ or satellite sources are limited. A regional near-real-time aqua moderate resolution imaging spectroradiometer (MODIS) 1-km-resolution SST composite has been developed by the NASA Short-term Prediction and Research Transition (SPoRT) program to provide continuous high-resolution SST fields twice daily for regional weather applications. The SPoRT Aqua MODIS SST composite is inter- compared to both half-degree-resolution real-time global (RTG) SST analysis and a 6-km-resolution geostationary operational environmental satellite 12 (GOES) Imager SST analysis and validated against buoy data for the month of May 2004. The SPoRT MODIS composite provides more accurate and detailed spatial information than the RTG-SST or GOES products during this period. Compared to limited buoy data, the daytime MODIS composites for May 2004 were found to have an average cool bias of -0.09degC, and the nighttime composites an average cool bias of -0.29degC, with both day and night composites having correlation values of approximately 0.90. A comparison of the MODIS SST composite to the more recent and higher resolution 12th-degree RTG-SST analysis and the 20th-degree resolution operational sea surface temperature and sea ice analysis indicated that the SPoRT MODIS composite provides additional spatial and diurnal cycle information on a regional scale.     

Empirical orthogonal function analysis of sea surface temperaturepatterns in Delaware Bay

Empirical orthogonal functions (EOFs) are used to study a time-series of IR images from the Delaware Bay region, to determine the dominant patterns of sea surface temperature (SST) variance. Thirty-two months of AVHRR imagery, from February 1992 to September 1994, were used in the study. The SST images were averaged into monthly means for the analysis. EOF analysis decomposed the time series into its component parts. For Delaware Bay, the seasonal solar heating cycle dominated the results, accounting for 95.3% of the total variance. Higher modes in this area are interpreted as the result of spring heating and fall cooling of shallow river and bay waters ahead of offshore waters. The EOF results provide independent satellite derived evidence for lateral variability in the circulation of the estuary, which had previously been found in in-situ studies. The lateral variability in the bay circulation is a result of Delaware Bay's drowned river valley bathymetry     

A relaxation labeling technique for computing sea surfacevelocities from sea surface temperature

The paper applies a relaxation labeling technique to computing sea surface advective velocities from sequential satellite sea surface temperature (SST) images. The technique first identifies prominent feature points in a pair of time-lapsed SST images, and then estimates sea surface current velocities by establishing feature point correspondences between the two images. In the context of relaxation labelling operation the authors have constructed a compatibility coefficient expressing flow field spatial smoothness, or coherency, suitable for fluid motion. New results are reported and are compared to those obtained using two other methods: the geostrophic currents from in situ measurements and the maximum cross-correlation (MCC) method. The three kinds of velocities are shown to be consistent to one another     

Detection of Sea Surface Temperature (SST) and Salinity Using Thermal Infrared Data of AVHRR and MODIS in the Gulf of Bohai Sea of China

This paper presents the detection of sea surface temperature (SST) and salinity in the Gulf of Bohai Sea of China using thermal infrared (TIR) data of Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). Both AVHRR and MODIS imageries are evaluated as main data sources for monitoring SST as a measure of upwelling's dynamic. The relationship between SST and salinity in the area is also discussed during 1997-2000 derived from AVHRR data and then examined using MODIS data of 2000. The obtained results indicated that both AVHRR and MODIS are useful to detect SST and salinity in the study area.