This study utilized automated machine learning (AutoML) to calculate Arctic ice surfacetemperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and aroot mean squared error (RMSE) of 2.51K. Comparative analysis with...
This study utilized automated machine learning (AutoML) to calculate Arctic ice surfacetemperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and aroot mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN)models revealed that AutoML IST demonstrated good accuracy, particularly when compared toModerate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST.
These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy underchallenging polar conditions.