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Parallel-Dynamic Interpolation Algorithm of Sea Surface Height for Future 2D Altimetry Mapping of Sea Surface Height

The sea surface height data volume of the future wide-swath two-dimensional(2 D) altimetric satellite is thousands of times greater than that of nadir altimetric satellites. The time complexity of the 2 D altimetry mapping reaches O(n~3). It is challenging to map the global grid products of future 2 D altimetric satellites. In this study, to improve the efficiency of global data mapping, a new algorithm called parallel-dynamic interpolation(PA-DI) was designed. Through the use of 2 D data segmentation and fine-grained data mosaic methods, the parallel along-track DI processes were accelerated, and a fast and efficient spatial-temporal high-resolution and low-error enhanced mapping method was obtained. As determined from a comparison of the single-threaded DI with the PA-DI,the new algorithm optimized the time complexity from O(n~3) to O(n~3/KL), which improved the mapping efficiency and achieved the expected results. According to the test results of the observing system simulation experiments, the PA-DI algorithm may provide an efficient and reliable method for future wide-swath 2 D altimetric satellite mapping.     

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MEAN SEA LEVEL AND SEA SURFACE VARIABILITY OF NQRTHWEST PACIFIC OCEAN AND EASTERN CHINA SEAS FROM GEOSAT ALTIMETRY

Collinear analysis technique is widely used for determining sea surface variability with Geosat altimeterdata from its Exact Repeat Mission(ERM).But most of the researches have been only on global scaleor in oceans deeper than 2000 m.In shallow shelf waters this method is hampered by the inaccuracy ofocean tide data supplied with Geosat Geophysical Data Records(GDRs).This work uses a modified collinearanalysis technique characterized by simultaneous separation of mean sea level and ocean tide with theleast squares method,to compute sea surface variability in the Northwest Pacific Ocean and eastern ChinaSeas.The mean sea level map obtained contains not ouly bathymetric but also dynamic features such asamphidromes,indicating considerable improvement over previous works.Our sea surface variability mapsshow clearly the main current system,the well-known Zhejiang coastal upwelling,and a northern East Chi-na Sea meso-scale eddy in good agreement with satellite sea surface temperature(SST)observation and his-to     

Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center (NDBC), root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.     

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Objective analysis and classification of the ten-day mean sea surface temperature variation in the East China Sea using singular value decomposition technique

The seasonal changes of the ten-day mean sea surface temperature in the East China Sea for the years 1953–1972 were studied using the singular value decomposition technique. Main results obtained are as follows: In the singular vector analysis of the ten-day mean sea surface temperature in the East China Sea, the first three singular vectors (or seasonal march functions) account for 97.76% of the variance of the data. The geographical distribution in the weightings (or spatial pattern functions) on these vectors shows a remarkable regional organization. An objective classification of the surface water mass in the East China Sea was based on the mode of its seasonal temperature changes. Contribution No. 801 from the Institute of Oceanology, Academia Sinica. An abstract of this paper was presented at an IAPSO Session of XVII IUGG held at Canberra, Australia, December 1979.     

Preliminary validation of SMOS sea surface salinity measurements in the South China Sea

The SMOS(soil moisture and ocean salinity) mission undertaken by the European Space Agency(ESA) has provided sea surface salinity(SSS) measurements at global scale since 2009.Validation of SSS values retrieved from SMOS data has been done globally and regionally.However,the accuracy of SSS measurements by SMOS in the China seas has not been examined in detail.In this study,we compared retrieved SSS values from SMOS data with in situ measurements from a South China Sea(SCS) expedition during autumn 2011.The comparison shows that the retrieved SSS values using ascending pass data have much better agreement with in situ measurements than the result derived from descending pass data.Accuracy in terms of bias and root mean square error(RMS) of the SSS retrieved using three different sea surface roughness models is very consistent,regardless of ascending or descending orbits.When ascending and descending measurements are combined for comparison,the retrieved SSS using a semi-empirical model shows the best agreement with in situ measurements,with bias-0.33 practical salinity units and RMS 0.74.We also investigated the impact of environmental conditions of sea surface wind and sea surface temperature on accuracy of the retrieved SSS.The SCS is a semi-closed basin where radio frequencies transmitted from the mainland strongly interfere with SMOS measurements.Therefore,accuracy of retrieved SSS shows a relationship with distance between the validation sites and land.     

Measurements of ocean wave and current field using dual polarized X-band radar

A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed. Two experiments into the use of the radar system were carried out at two sites, respectively, for calibration process in Zhangzi Island of the Yellow Sea, and for validation in the Yellow Sea and South China Sea. Ocean wave parameters and sea surface current velocities were retrieved from the dual polarized radar image sequences based on an inverse method. The results obtained from dual-polarized radar data sets acquired in Zhangzi Island are compared with those from an ocean directional buoy. The results show that ocean wave parameters and sea surface current velocities retrieved from radar image sets are in a good agreement with those observed by the buoy. In particular, it has been found that the vertically-polarized radar is better than the horizontally-polarized radar in retrieving ocean wave parameters, especially in detecting the significant wave height below 1.0 m.     

中国区域BP-Adaboost强预测器对流层天顶延迟建模研究

选取中国大陆构造环境监测网（陆态网）提供的155个测站2014~2018年对流层延迟产品,基于BP-Adaboost算法将多个弱神经网络预测器集成为强预测器,建立新的无气象参数对流层延迟计算模型。利用陆态网2019年参与建模的141个建模测站、未参与建模的62个测站的对流层延迟产品和中国区域86个无线电探空站解算出的对流层延迟精确值对BP-Adaboost模型进行精度评定,结果表明,新模型的平均偏差分别为0.62 mm、-1.16 mm和12.32 mm,均方根误差分别为25.30 mm、26.72 mm和46.29 mm,优于常见的无气象参数模型;BP-Adaboost模型在内陆地区或海拔2 km以上地区具有更高的精度,能够满足中国大陆区域卫星导航用户实时对流层延迟改正的需求。