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针对传统海表盐度遥感反演精度不高、影响因素较少等问题,本文基于SMAP(Soil Moisture Active Passive)卫星L2C(Level 2 C)数据、Argo(Array for Real-time Geostrophic Oceanography)数据和其他辅助数据,以太平洋部分海域(160°E~120°W,0°~30°N)为研究区域,综合考虑海面粗糙度以及白冠覆盖率等参量,利用径向基神经网络建立RBF亮温增量模型,并对平静海面亮温进行修正,然后基于Meissner-Wentz介电常数模型得到反演后的盐度值。验证结果表明:模型预测盐度和SMAP卫星盐度相对于Argo实测盐度的均方根误差分别为0.4和0.5,平均绝对误差分别为0.3和0.4。实验证明,利用RBF神经网络建立的亮温增量模型可以提高海表盐度反演的精度,对海表盐度反演具有实用意义。 相似文献
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自欧洲土壤湿度和盐度卫星SMOS和美国宝瓶座盐度卫星Aquarius相继发射之后,多个数据中心发布了两颗卫星的海表盐度网格化产品,其中包括法国海洋研究院SMOS卫星数据小组发布SMOS Locean L3盐度产品、西班牙巴塞罗那专家中心发布SMOS BEC L4盐度产品和美国宇航局喷气动力实验室发布AquariusV3.0 CAP L3盐度产品。本文利用精确盐度现场观测资料从产品精度和模拟海洋现象能力两个方面对以上3种产品质量进行了评估。研究表明:(1) 在精度方面,与盐度现场资料相比,Aquarius CAP 产品质量最高,产品盐度偏差和均方根误差全年稳定且偏差较小,部分海域达到了设计精度;SMOS两种卫星产品在全球海域偏差较不稳定,个别月份出现异常偏差值;SMOS产品在低纬和开阔海域的数据质量相对较高,但在高纬海域仍存在较大误差,需要进一步提升;(2) 在刻画海洋现象方面,Aquarius产品在热带太平洋较好刻画了淡池东缘盐度锋,SMOS BEC产品的刻画能力次之,SMOS Locean产品在热带太平洋充满了小尺度噪音,描述物理现象方面表现偏差。 相似文献
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针对SMOS和Aquarius海表盐度误差分析没有区分不同空间频谱信噪特征的问题,基于6种主要的遥感盐度分析产品,根据定性图像、纬向波数谱、均方根误差等指标,分析产品的有效分辨率并探讨其原因机制。研究表明:CATDS-0.25°分析产品所描述的盐度场中小尺度结构失真,其较高谱能量密度在热带海域以噪音为主,而在西边界流等海域以信号为主;BEC-L3-0.25°有着较小的均方根误差、清晰的盐度图像、显著的中尺度能量,最适于描绘中尺度(25~100 km)盐度特征;BEC-L4-0.25°被奇异谱分析方法过度平滑了盐度场;Aquarius-V2-1.00°通过局部平滑处理,在描述大尺度(>100 km)盐度现象方面表现较好;Aquarius-CAP-1.00°通过主动-被动联合算法(CAP)减小了均方根误差,但图像中卫星轨道形态明显;CATDS-1.00°的图像形态、能量分布和误差特征与Aquarius-V2-1.00°相当。这些结论可为用户正确使用产品进行地球物理学研究提供参考。 相似文献
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土壤湿度和海洋盐度卫星首次提供了覆盖全球的高频率、高精度、业务化的海表盐度产品,但其处理和延伸应用仍处于初级阶段,后续校准校正工作还将持续数年,如何及时把握其发展轨迹成为一个重要的科学问题.本研究从SMOS计划、数据概况、盐度反演算法、格点产品制作、多源数据融合和产品应用等方面,介绍和评述了SMOS计划及其海表盐度产品应用研究进展,着重分析了反演算法中的各种误差来源,对在轨2 a的运行情况进行了回顾、对未来的发展重点进行了展望,旨在为开发和应用SMOS产品提供参考. 相似文献
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孟加拉湾上层地转环流周年变化的遥感研究 总被引:1,自引:1,他引:1
应用1993~2003年TOPEX/Poseidon卫星测高数据结合历史水文资料,反演了孟加拉湾海面动力地形的平均周年变化,探讨了孟加拉湾上层环流季节特征和演变规律.结果显示,虽然孟加拉湾的大气环流受季风支配年周期波动显著,但表层环流形态的周年演变却呈3个不同的阶段.1~4月间(东北季风后期)湾内受一个海盆尺度的强大反气旋式环流的支配,湾口为西向流;5月西南季风骤起,印度季风漂流越过印度半岛南端出现在湾口,湾内反气旋环流弱化,在其南北两侧各出现一气旋式涡,构成5~9月间南北相间的三涡结构;10月东北季风再起,湾口漂流再次转向,10~12月间湾内则为海盆尺度的弱气旋式环流.受上述环流格局影响,位于西边界的印度沿岸流亦呈相应的3个阶段变化.分析表明,孟加拉湾风应力旋度的变化是造成湾内环流3个阶段演变的主要原因.本地风场和来自赤道海域的外强迫的共同驱动形成了孟加拉湾环流周年演变的独特规律. 相似文献
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海表盐度是研究海洋变化及其气候效应重要的物理量。本文将2018年SMAP卫星的月均、日均海表盐度产品分别与Argo月均网格化产品、实时散点盐度数据进行比较,评定其精度,并分析全球海表盐度分布特征。结果表明:SMAP卫星月均产品RMSE为0.17,BIAS为0.11,STD为0.17,R为0.98,t检验呈显著相关;SMAP卫星日均产品RMSE为0.28,BIAS为0.23,STD为0.26,R为0.81,相较月均产品,精度较低。SMAP卫星月均产品偏差在中纬度海域较小,在高纬度海域较大;SMAP卫星日均产品偏差在太平洋海域为-0.6~0.6,在地中海海域超过1.0。全球海表盐度在25.0~40.0之间,沿纬度方向呈带状分布,其中大西洋海表盐度普遍高于太平洋和印度洋。 相似文献
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针对传统海表盐度的物理机制反演模型拟合过程复杂且反演精度不高等问题,借助大范围、全天时、L波段探测的SMAP卫星微波海洋遥感产品,以北太平洋(135°~165°E,15°~45°N)范围为研究海域,利用深层神经网络(Deep Neural Network, DNN)和支持向量机(Support Vector Machine, SVM)建立海表盐度(Sea Surface Salinity, SSS)遥感反演模型。验证结果表明:DNN与SVM模型测试集反演SSS与Argo(Array for Real-time Geostrophic Oceanography))实测SSS的均方根误差(Root Mean Square Error, RMSE)分别为0.179 0和0.257 0,平均绝对误差(Mean Absolute Error, MAE)为0.129 3和0.182 1,最小绝对误差为0.642 6和2.038 0,最大绝对误差为1.324 1和2.373 2,反演模型数据与实测Argo数据拟合后的的相关系数分别为0.89和0.84。总体来看,DNN模型比SVM模型的反演精度更高,... 相似文献
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利用1998―2007年Seaflux资料结合太阳短波辐射及海面风场数据,分析了孟加拉湾海表日增温(Diurnal Warming of Sea Surface Temperature, dSST)的季节变化特征及其形成机制。结果显示,在赤道海域(5.0°N以南),dSST以年周期变化为主并呈现12月至次年5月高、6—11月低的单峰结构,在湾内(5.0°N以北),dSST则表现出显著的半年周期变化而呈现独特的春、秋季高,夏、冬季低的双峰结构。dSST空间分布形态春季呈湾中部高、四周低的态势;秋季湾口较低、湾内及赤道海域较高;夏、冬季形态基本一致均呈赤道高、湾内低的格局,但夏、冬季湾内高值中心略有不同,分别位于斯里兰卡岛东北部近海及湾西边界区。进一步分析表明,海面风速对整个研究海域的影响均较为重要,因此决定了dSST空间分布形态的季节变化。太阳短波辐射对湾内dSST季节变化的影响也较为重要,但在湾口以南至赤道大部分海域的影响较弱。 相似文献
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孟加拉湾上层环流研究综述 总被引:2,自引:0,他引:2
综述了孟加拉湾上层环流研究的主要成果并指出,研究海区环流与季风转换不完全同步。在西南季风期间,南、北海区各有一气旋式环流;在秋季季风过渡期间,出现海湾尺度的气旋式环流;在东北季风期间,气旋式环流减弱北移,南部则为一反气旋式环流控制;春季与秋季的情形相反,整个湾出现一海湾尺度的反气旋式环流。研究海区环流的变异主要受季风、赤道远地作用和浮力通量等复杂外源作用的影响。东印度沿岸流的季节变化与季风转换也不同步,局地风、内部Ekman抽吸、远地沿岸风及赤道远地作用的影响对沿岸流周年变化有重要作用。孟加拉湾上层环流年际变化显著,此年际变化主要受赤道风场的影响。 相似文献
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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
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为解决海洋中大量观测数据只含有温度剖面而缺乏盐度观测的问题, 基于历史观测的温盐剖面资料, 考虑到盐度卫星数据的发展, 采用回归分析方法, 在孟加拉湾建立了盐度与温度、经纬度、表层盐度的关系, 并对不同反演方法的反演结果进行检验评估。结果发现, 在不引入海表盐度(sea surface salinity, SSS)时, 最佳反演模型是温度、温度的二次项与经纬度确定的回归模型, 而SSS的引入则可以进一步优化反演结果。将反演结果与观测结果进行对比, 显示用反演的盐度剖面计算的比容海面高度误差超过2cm, 而引入SSS后的误差低于1.5cm。SSS的引入能够较为真实地反映海洋盐度场的垂直结构和内部变化特征, 既能够捕捉到对上混合层有重要影响的SSS信号, 又能够反映盐度在跃层上的季节内变化以及盐度障碍层的季节变化。水团分析显示, 与气候态相比, 盐度反演结果可以更好地表征海洋上层水团的变化特征。 相似文献
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The issue of sea level rise is receiving considerable attention all over the world. Although the Indian stations have shown mixed trends, a positive sea level trend has been noticed in the Hooghly Estuary, situated on the east coast of India. The Hooghly River serves as a navigable waterway to Calcutta and Haldia ports. The river is tidal for nearly 250 km. To study the water levels and tidal currents in the lower part of the Hooghly Estuary, from sea face at Sagar to Hooghly Point, a vertically integrated numerical model has been used. The model is fully nonlinear and uses a semiexplicit finite‐difference scheme to solve the basic hydrodynamic equations on a staggered grid. This model is coupled with a one‐dimensional model, which has been used for the upper estuary from Hooghly Point to Swarupganj, where the flow is unidirectional. The computed water levels and currents are found to be in good agreement with the available observations. This model is applied to study the alterations in tidal circulation for a rise and fall in the sea level. The results have shown a substantial increase in the amplitude and velocities of the tidal wave due to the sea level rise. 相似文献
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The effect of river runoff over the northern Indian Ocean(NIO) especially over the Bay of Bengal(Bo B) has been studied using global Nucleus for European Modelling of the Ocean(NEMO). Two sensitivity experiments, with and without river runoff are conducted and the influence of river runoff on the Indian Ocean hydrography,stratification and circulation features are studied. It is found that due to river runoff surface salinity over the northern Bo B decreases by more than 5 and the East India Coastal Current strengthens by 2 cm/s during post monsoon season. The fresh river water reaches up to 15°N in the Bo B and is the main cause for low salinity there.Sea surface temperature in the northwestern Bo B increases by more than 0.2℃ due to the river runoff in summer monsoon while surface cooling upto 0.2℃ is seen in north-west part of Bo B in winter season. The seasonal mixed layer depth in the region is found to be dependent on river runoff. The effect of vertical shear and Brunt Vaisala frequency on stratification is also examined. The ocean water becomes highly stratified up to 3 035 m due to the river runoff. It is found that the energy required for mixing is high in the northern and coastal Bo B. 相似文献
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Effect of River Discharge on Bay of Bengal Circulation 总被引:1,自引:1,他引:1
The seasonal circulation and mixed layer depths in Bay of Bengal is modeled using the three-dimensional Princeton Ocean Model (POM). Along the coastal boundaries a higher resolution is accomplished using the curvilinear orthogonal grid. Model uses a free-surface and terrain following sigma coordinates. The initial climatological salinity and temperature fields for the model are derived from the World Ocean Atlas-2001(WOA01). The Model is forced with wind stress derived from COADS wind climatology. Bilinear interpolation is used to obtain the initial fields and wind stress to the required model specification. Using the seasonal fields and wind stress the model is integrated for simulating Bay of Bengal circulation. The numerical simulations on climatological scale for monsoon months were conducted to study the evolution of dynamics. The simulations bring out not only the typical characteristic features of fresh water plume along the coast but also intensification of the flow over the monsoon period. The increase in the fresh water flow found to affect only the western parts of the BoB. The opposing currents due to monsoon winds and southward flowing fresh water discharge (FWD) were also delineated. The model results show that the wind stress induced turbulence process is subdued in the presence of strong vertical salinity stratification due to the influence of FWD. The simulated mixed layer depths are in agreement with the reported analytical energy required for mixing values. 相似文献
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An analysis on the error structure and mechanism of soil moisture and ocean salinity remotely sensed sea surface salinity products 总被引:1,自引:0,他引:1
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