Arjun Babu Nellikkattil

Arjun Babu Nellikkattil

he/him

I am a climate scientist passionate about developing advanced mathematical and machine learning tools to improve our understanding of the climate system and predict future changes. My current research focuses on refining climate risk assessments and informing policy decisions by providing precise, data-driven insights into future precipitation trends.

Prediction of daily sea surface temperature using artificial neural networks

Published in International Journal of Remote Sensing, 2018

An artificial neural network model to predict the sea surface temperature (SST) and delineate SST fronts in the northeastern Arabian Sea. The predictions are made one day in advance, using current day’s SST for predicting the SST of the next day. The model is used to predict the SST map for every single day during 2013–2015. The results show that more than 75% of the time the model error is ≤ ±0.5ºC. For the years 2014 and 2015, 80% of the predictions had an error ≤±0.5ºC. The model performance is dependent on the availability of data during the previous days. Thus, during the summer monsoon months, when the data availability is comparatively less, the errors in the prediction are slightly higher. The model is also able to capture SST fronts.

Recommended citation: Aparna, S. G., Selrina D’souza, and N. B. Arjun. "Prediction of daily sea surface temperature using artificial neural networks." International Journal of Remote Sensing 39, no. 12 (2018): 4214-4231.
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