Automatic Detection and Classification of Atmospherical Fronts

Andreea Ploscar, Anca Muscalagiu, Eduard Pauliuc, Adriana Coroiu

2024

Abstract

This paper presents an application that uses Convolutional Neural Networks (CNN) for the automatic detection and classification of atmospherical fronts in synoptic maps, which are a graphical representation of weather conditions over a specific geographic area at a given point in time. These fronts are significant indicators of meteorological characteristics and are essential for weather forecasting. The proposed method takes in a region extracted from a synoptic map to detect and classify fronts as cold, warm, or mixed, setting our study apart from existing literature. Furthermore, unlike previous research that typically utilizes atmospheric data grids, our study employs synoptic maps as input data. Additionally, our model produces a single output, accurately representing the front type with a 78% accuracy rate. The CNN model was trained on data collected from various meteorological stations worldwide between 2013 and 2022. The proposed tool can provide valuable information to weather forecasters and improve their accuracy.

Paper Citation

in Harvard Style

Ploscar A., Muscalagiu A., Pauliuc E. and Coroiu A. (2024). Automatic Detection and Classification of Atmospherical Fronts. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 94-100. DOI: 10.5220/0012306700003636

in Bibtex Style

@conference{icaart24,
author={Andreea Ploscar and Anca Muscalagiu and Eduard Pauliuc and Adriana Coroiu},
title={Automatic Detection and Classification of Atmospherical Fronts},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={94-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012306700003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Automatic Detection and Classification of Atmospherical Fronts
SN - 978-989-758-680-4
AU - Ploscar A.
AU - Muscalagiu A.
AU - Pauliuc E.
AU - Coroiu A.
PY - 2024
SP - 94
EP - 100
DO - 10.5220/0012306700003636
PB - SciTePress