ABSTRACT

The use of remote sensing data, whether for change detection, spatial and temporal analysis, or numerical simulation of water bodies, requires a complete data set. Here, high temporal and spatial resolution sea surface temperature (SST) data for the Arctic are produced based on optimal interpolation and data reconstruction algorithms with a temporal resolution of 12 h and a spatial resolution of 9 km. The accuracy of the reconstructed data sets is verified using Argo measurements to demonstrate the validity and reliability of the data interpolation empirical orthogonal functions method. The root mean square error of the fusion data (a temporal resolution of 12 h) is relatively stable, ranging from 0.49°C to 0.62°C. In comparison with remote sensing systems (RSS) MW-IR SST and Advanced Very High Resolution Radiometer (AVHRR) OISST, the accuracy of the fusion data (a temporal resolution of 24 h) is in the range of 0.48–0.65°C, while that of the MW-IR SST is in the range of 0.48–0.60°C and AVHRR OISST is in the range of 0.66–0.79°C. The fusion data is more accurate than those of AVHRR OISST, and there is no obvious difference with RSS MW-IR SST.

摘要

遥感数据的使用，无论是变化检测、时空分析，还是水体数值模拟，都需要一个完整的数据集。在这里，基于最优插值和数据重建算法生成了北极的高时空分辨率海面温度 (SST) 数据，时间分辨率为 12 小时，空间分辨率为 9 公里。使用 Argo 测量验证重建数据集的准确性，以证明数据插值经验正交函数方法的有效性和可靠性。融合数据的均方根误差（时间分辨率为 12 h）相对稳定，范围从 0.49°C 到 0.62°C。与遥感系统 (RSS) MW-IR SST 和高级甚高分辨率辐射计 (AVHRR) OISST 相比，融合数据的精度（时间分辨率为 24 小时）在 0.48-0.65°C 范围内，而 MW-IR SST 的精度在 0.48-0.60°C 范围内，AVHRR OISST 的精度在范围内0.66–0.79°C。融合数据比AVHRR OISST更准确，与RSS MW-IR SST没有明显区别。