| Summary: | This study, focusing on the Antarctic polynyas, performed the imputation of chlorophyll-a concentration (Chl-a) dataset, which is one of the ocean color products mainly used for estimating primary productivity, using the Data Interpolating Empirical Orthogonal Function method and constructed accurate time-series data that excludes as much uncertainty as possible in long-term variability studies due to missing data. The polynya regions were classified into a total of 23 zones through quantitative criterions, and the statistical accuracy of imputation performance was 0.89 for R2 and 0.42, 0.24, and 0.15 for root mean square error, mean squared error, mean absolute error, respectively, on average, showing the ability to perform generally accurate reconstruction. Finally, the reconstructed Chl-a data showed a relatively stable fluctuation compared with standard satellite Chl-a data, and tended to be underestimated due to the expansion of the observable regions. We expect that securing these relatively stable and accurate estimates will be significantly different from the time-series data composed of standard Chl-a estimates, enabling more accurate variability and trend analysis.
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