Abstract
ABSTRACT Sea ice concentration (SIC) can be retrieved from thermal infrared (TIR) imagery due to the distinctive thermal properties of ice and water. Nevertheless, existing TIR-based SIC algorithms rely on surface temperature data, which often introduces additional errors. To address this issue, we have developed a new TIR ice concentration algorithm (TIRIA) that directly utilizes TIR brightness temperatures. TIRIA considers factors such as seawater salinity, observation angle and their impacts on seawater brightness temperature. TIRIA and a traditional algorithm, the MODIS potential open water algorithm (MPA), are applied to MODIS TIR imagery. Results are evaluated with near-infrared (NIR) SICs and compared with passive microwave (PM) SICs. Overall, TIRIA outperforms MPA, exhibiting a smaller root mean square error (RMSE) (14.01% compared to 17.63%) and higher correlation coefficient (0.89 compared to 0.81). Both TIRIA and MPA tend to underestimate SIC in high SICs while overestimating it in low SICs. Due to its more accurate identification of water, TIRIA significantly mitigates the overestimation in low SICs. Compared to PM-based SICs, both TIR-based SICs exhibit overall overestimations, with better consistency between TIRIA and PM-based SICs. TIRIA, being independent of surface temperature products and theoretically applicable to any TIR data, showcases great potential for future application.
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