This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.
利用TOPEX/Poseidon卫星连续12年(1993年1月～2004年12月)对中国大陆及周边地区观测的GDR-M(Merged Geophysical Data Record)数据集,提取Ku波段和C波段的后向散射系数,经平滑、内插处理之后,得到5′×5′的网格数据及其时间序列.对后向散射系数在中国典型地表类型(如湿地、沙漠、山地和农业基地等)的空间分布特征进行了分析与讨论.利用快速Fourier变换(FFT)探测后向散射系数时间序列的周期变化,发现周期以周年为主,部分地区还有半年周期变化.利用最小二乘方法得到周年周期和半年周期的振幅等周期项信息,结果显示周年振幅明显大于半年振幅.分析了后向散射系数时间序列异常与我国环境和气候变化以及严重灾害(如洪水、干旱)的关系.利用SRTM导出的坡度对我国部分地区的后向散射系数的相关性进行了分析,以确定地势对后向散射系数的影响程度,结果显示Ku波段和C波段后向散射系数皆与坡度呈负相关,辽宁和吉林地区的相关性最强为0.56,塔克拉玛干沙漠地区的相关性最弱为0.11,其他地区多为(0.3～0.5)之间,表明地势起伏而引起的坡度对后向散射系数有显著的负相关性.
