Algorithm for estimating sea surface temperatures based on Aqua/MODIS global ocean data. 1. Development and validation of the algorithm

An algorithm for estimating global sea surface temperatures (SST) from data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite has been developed empirically. Four atmospheric correction models for MODIS observations are examined, and the effects of ancillary data for corrections are discussed. A nonlinear (NLSST) model using high-temporal-resolution climatological SSTs as the first guess shows high accuracy and availability. The addition of a temperature-proportional term to the NLSST model effectively improves the estimate.     

Spatio-temporal variability in sea surface temperatures for the Yellow Sea based on MODIS dataset

The spatio-temporal variabilities in sea surface temperature (SST) were analyzed using a time series of MODIS datasets for four separate regions in the Yellow Sea (YS) that were located along a north-south axis. The space variant temporal anomaly was further decomposed using an empirical orthogonal function (EOF) for estimating spatially distributed SST. The monthly SSTs showed similar temporal patterns in each region, which ranged from 2.4°C to 28.4°C in the study years 2011 to 2013, with seasonal cycles being stronger at the higher latitudes and weaker at the lower latitudes. Spatially, although there were no significant differences among the four regions (p < 0.05) in any year, the geographical distribution of SST was characterized by an obvious gradient whereby SST decreased along the north-south axis. The monthly thermal difference among regions was largest in winter since the SST in the southeast was mainly affected by the Yellow Sea Warm Currents. The EOF1 mode accounted for 56% of the total spatial variance and exhibited a warming signal during the study period. The EOF2 mode accounted for 8% of the total variance and indicated the warm current features in the YS. The EOF3 mode accounted for 6% of the total variance and indicated the topographical features. The methodology used in this study demonstrated the spatio-temporal variabilities in the YS.     

基于海面高度数据的全球海洋多核涡旋探测和统计

This study produced a statistical analysis of multicore eddy structures based on 23 years' altimetry data in global oceans. Multicore structures were identified using a threshold-free closed-contour algorithm of sea surface height, which was improved for this study in respect of certain technical details. Meanwhile a more accurate definition of eddy boundary was used to estimate eddy scale. Generally, multicore structures, which have two or more closed eddies of the same polarity within their boundaries, represent an important transitional stage in their lives during which the component eddies might experience splitting or merging. In comparison with global eddies, the lifetimes and propagation distances of multicore eddies were found to be much smaller because of their inherent structural instability. However, at the same latitude, the spatial scale of multicore eddies was found larger than that of single-core eddies, i.e., the eddy area could be at least twice as large. Multicore eddies were found to exhibit some features similar to global eddies. For example, multicore eddies tend to occur in the Antarctic Circumpolar Current, some western boundary currents, and mid-latitude regions around 25°N/S, the majority(70%) of eddies propagate westward while only 30% propagate eastward, and large-amplitude eddies are restricted mainly to reasonably confined regions of highly unstable currents.     

基于改进DBSCAN算法的ICESat-2海面点数据去噪处理及精度评估

ICESat-2卫星搭载先进的光子计数式激光雷达ATLAS,使用全新的测量方式获取海量的光子点云数据.光子计数激光点云由于受海洋表面噪声以及水中穿透性较强等因素影响,现有的去噪算法在浅海区域海面去噪上存在一定的局限性.针对上述问题,本文提出了一种基于改进DBSCAN参数的去噪算法,通过利用点云数据集自身分布特性生成候选...     

基于HY-2A微波散射计海面风场资料的台风风剖面信息提取研究

台风风剖面信息是直观反映与台风中心不同距离的各点与平均风速关系的曲线,它是确定各级台风风圈范围的重要基础。本文利用HY-2A微波散射计海面风场资料,结合Holland风场模型提出了一种新的台风风剖面信息提取方法,并选取2012–2017年期间16期典型台风进行应用。结果表明:34 kt与50 kt风圈半径的平均均方根误差为37.6 km与18.3 km,该方法具有较好的适用性和精度。本研究对于描述台风结构特征及潜在的破坏力和台风可能的影响范围具有一定的现实意义。     

基于D-S理论的卫星遥感海表面温度和同化数据融合方法

利用卫星遥感获取海表面温度实时性强,但其数据质量随大气环境而波动;利用同化技术求解的海表面温度局部精度高,但覆盖面与实时性差.鉴于两种技术适应不同情况,拟使用信息融合技术实现两者优势互补,即根据各自的优势和局限性对数据点进行一致性评价和加权融合计算,在提高精度的同时对结果的不确定性进行量化和评价.以我国东部海域海表温度为例的采样试验结果表明,融合法更适应复杂的环境.     

基于POMgcs模式中国海及邻近海域三维温盐流数值预报海面温度的检验分析

对基于POMgcs海洋模式建立中国海及邻近海域三维温盐流数值预报系统的海面温度产品,进行检验分析。利用2011年预报的月平均海面温度数据同卫星观测的月平均海面温度资料相比较,发现三维温盐流数值预报系统预报偏高。此外,分别利用2011年GTS海洋观测海面温度数据和2012年2、3、4月份卫星融合海面温度数据,与该系统海面温度预报逐日产品进行检验分析。检验结果表明:预报精度随着预报时效逐渐降低;预报海面温度高于观测值1℃~2℃。     

A global wave parameter database for geophysical applications. Part 1: Wave-current–turbulence interaction parameters for the open ocean based on traditional parameterizations

Ocean surface mixing and drift are influenced by the mixed layer depth, buoyancy fluxes and currents below the mixed layer. Drift and mixing are also functions of the surface Stokes drift U_ss, volume Stokes transport T_S, a wave breaking height scale H_swg, and the flux of energy from waves to ocean turbulence Φ_oc. Here we describe a global database of these parameters, estimated from a well-validated numerical wave model, that uses traditional forms of the wave generation and dissipation parameterizations, and covers the years 2003–2007. Compared to previous studies, the present work has the advantage of being consistent with the known physical processes that regulate the wave field and the air–sea fluxes, and also consistent with a very large number of in situ and satellite observations of wave parameters. Consequently, some of our estimates differ significantly from previous estimates. In particular, we find that the mean global integral of Φ_oc is 68 TW, and the yearly mean value of T_S is typically 10–30% of the Ekman transport, except in well-defined regions where it can reach 60%. We also have refined our previous estimates of U_ss by using a better treatment of the high frequency part of the wave spectrum. In the open ocean, U_ss ≃ 0.013U₁₀, where U₁₀ is the wind speed at 10 m height.     

基于现场观测与MyOcean模式数据的印度洋东南部Aquarius反演海表盐度的评价与纠正

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.     

A global wave parameter database for geophysical applications. Part 1: Wave-current–turbulence interaction parameters for the open ocean based on traditional parameterizations

Ocean surface mixing and drift are influenced by the mixed layer depth, buoyancy fluxes and currents below the mixed layer. Drift and mixing are also functions of the surface Stokes drift U_ss, volume Stokes transport T_S, a wave breaking height scale H_swg, and the flux of energy from waves to ocean turbulence Φ_oc. Here we describe a global database of these parameters, estimated from a well-validated numerical wave model, that uses traditional forms of the wave generation and dissipation parameterizations, and covers the years 2003–2007. Compared to previous studies, the present work has the advantage of being consistent with the known physical processes that regulate the wave field and the air–sea fluxes, and also consistent with a very large number of in situ and satellite observations of wave parameters. Consequently, some of our estimates differ significantly from previous estimates. In particular, we find that the mean global integral of Φ_oc is 68 TW, and the yearly mean value of T_S is typically 10–30% of the Ekman transport, except in well-defined regions where it can reach 60%. We also have refined our previous estimates of U_ss by using a better treatment of the high frequency part of the wave spectrum. In the open ocean, U_ss  0.013U₁₀, where U₁₀ is the wind speed at 10 m height.