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Remote Sens. 2017, 9(12), 1305; https://doi.org/10.3390/rs9121305

Prediction of Arctic Sea Ice Concentration Using a Fully Data Driven Deep Neural Network

Unit of Arctic Sea-Ice Prediction, Korea Polar Research Institute, Incheon 21990, Korea
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Received: 29 November 2017 / Revised: 9 December 2017 / Accepted: 11 December 2017 / Published: 12 December 2017
(This article belongs to the Section Ocean Remote Sensing)
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Abstract

The Arctic sea ice is an important indicator of the progress of global warming and climate change. Prediction of Arctic sea ice concentration has been investigated by many disciplines and predictions have been made using a variety of methods. Deep learning (DL) using large training datasets, also known as deep neural network, is a fast-growing area in machine learning that promises improved results when compared to traditional neural network methods. Arctic sea ice data, gathered since 1978 by passive microwave sensors, may be an appropriate input for training DL models. In this study, a large Arctic sea ice dataset was employed to train a deep neural network and this was then used to predict Arctic sea ice concentration, without incorporating any physical data. We compared the results of our methods quantitatively and qualitatively to results obtained using a traditional autoregressive (AR) model, and to a compilation of results from the Sea Ice Prediction Network, collected using a diverse set of approaches. Our DL-based prediction methods outperformed the AR model and yielded results comparable to those obtained with other models. View Full-Text
Keywords: arctic sea ice; autoregressive model; deep learning; global warming; long and short-term memory; machine learning; multilayer perceptron; neural network; sea ice concentration; sea ice extent arctic sea ice; autoregressive model; deep learning; global warming; long and short-term memory; machine learning; multilayer perceptron; neural network; sea ice concentration; sea ice extent
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Chi, J.; Kim, H.-C. Prediction of Arctic Sea Ice Concentration Using a Fully Data Driven Deep Neural Network. Remote Sens. 2017, 9, 1305.

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