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Prediction of daily sea surface temperature using artificial neural networks

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Title
Prediction of daily sea surface temperature using artificial neural networks
Author(s)
Aparna, S. G.; D'Souza, Selrina; N. B. Arjun
Publication Date
2018-03
Journal
INTERNATIONAL JOURNAL OF REMOTE SENSING, v.39, no.12, pp.4214 - 4231
Publisher
TAYLOR & FRANCIS LTD
Abstract
We present an artificial neural network model to predict the sea surface temperature (SST) and delineate SST fronts in the northe-astern 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.
URI
https://pr.ibs.re.kr/handle/8788114/12415
DOI
10.1080/01431161.2018.1454623
ISSN
0143-1161
Appears in Collections:
Center for Climate Physics(기후물리 연구단) > 1. Journal Papers (저널논문)
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