Simulation and Analysis of Sea Surface Skin Temperature Diurnal Variation Using a One-Dimensional Mixed Layer Model and Himawari-8 Data
Sea Surface Skin Temperature (SSTskin) derived from satellites and its diurnal variation are crucial for climate research, yet conventional ocean models, which primarily solve for the foundation or bulk SST, are not designed to simulate the very thin skin layer temperature (SSTskin). Consequently, specialized parameterizations or coupled model components are often required to obtain SSTskin. This study aimed to capture SSTskin diurnal warming events and evaluate the performance of the improved one-dimensional mixed-layer model (PWP: Price-Weller-Pinkel) in simulating SSTskin. Using high-frequency Himawari-8 satellite observations, a typical diurnal warming event was detected in the coastal waters off northwestern Australia, with the maximum SSTskin diurnal variation reaching 3 °C. The reliability of Himawari-8 data was validated using iQuam in situ observations, showing a mean bias of −0.28 °C. The improved PWP model (incorporating an SSTskin parameterization scheme), forced by ERA5 datasets, was used to simulate SSTskin and its diurnal variation at 90 (0.25° × 0.25°) grid points. Results indicated that the PWP model reproduced the diurnal variation cycle consistently with observations, accurately matched regions with significant warming, and achieved a mean bias of −0.37 °C. However, in low-wind-speed areas (<1 m/s), abnormal SSTskin overestimation (>3 °C) occurred due to rapid thinning of the mixed layer and the absence of horizontal diffusion in this one-dimensional model. The improved PWP model, with its relatively stable SSTskin parameterization scheme, provides a computationally efficient tool for studying vertical processes in the upper ocean. Future work should evaluate vertical mixing schemes under low wind speed conditions to enhance the capability of numerical models to simulate SSTskin.
Authors
- Zexi Mao (ORCID: https://orcid.org/0000-0002-4542-6780)
- Xuan Sang
- Pinyan Xu
- Z. P. Mao
- Xianliang Zhang
- Longwei Zhang
Institutions
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Sciences (CN)
- Ministry of Natural Resources (CN)
- Second Institute of Oceanography (CN)
- Shanghai Institute of Technical Physics (CN)
- University of Chinese Academy of Sciences (CN)
- University of Maine (US)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-12-23
- DOI
- https://doi.org/10.3390/rs18010043
- Primary Topic
- Oceanographic and Atmospheric Processes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Shanghai Jiao Tong University
- National Key Research and Development Program of China