Dedicated neural networks algorithms for direct estimation of tropospheric ozone from satellite measurements

This work presents a new approach for one of the main problems in the analysis of atmospheric phenomena, the prediction of atmospheric concentrations of different elements. The proposed methodology is more efficient than other classical approaches and is used in this work to predict tropospheric ozone concentration. The relevance of this problem stems from the fact that excessive ozone concentrations may cause several problems related to public health. Previous research by the authors of this work has shown that the classical approach to this problem (linear models) does not achieve satisfactory results in tropospheric ozone concentration prediction. The authors’ approach is based on Machine Learning (ML) techniques, which include algorithms related to neural networks, fuzzy systems and advanced statistical techniques for data processing. In this work, the authors focus on one of the main ML techniques, namely, neural networks. These models demonstrate their suitability for this problem both in terms of prediction accuracy and information extraction.

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Tropospheric ozone column retrieval from OMI data by means of neural networks: a validation exercise with ozone soundings over Europe

EURASIP Journal on Advances in Signal Processing ◽

10.1186/1687-6180-2013-21 ◽

2013 ◽

Vol 2013 (1) ◽

Cited By ~ 2

Author(s):

Antonio Di Noia ◽

Pasquale Sellitto ◽

Fabio Del Frate ◽

Marco Cervino ◽

Marco Iarlori ◽

...

Keyword(s):

Neural Networks ◽

Tropospheric Ozone ◽

Ozone Column

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Forecasting tropospheric ozone concentrations with adaptive neural networks

The 2011 International Joint Conference on Neural Networks ◽

10.1109/ijcnn.2011.6033450 ◽

2011 ◽

Author(s):

R. Taormina ◽

L. Mesin ◽

F. Orione ◽

E. Pasero

Keyword(s):

Neural Networks ◽

Tropospheric Ozone ◽

Ozone Concentrations ◽

Adaptive Neural Networks

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“Cloud slicing”: A new technique to derive upper tropospheric ozone from satellite measurements

Journal of Geophysical Research Atmospheres ◽

10.1029/2000jd900768 ◽

2001 ◽

Vol 106 (D9) ◽

pp. 9853-9867 ◽

Cited By ~ 77

Author(s):

J. R. Ziemke ◽

S. Chandra ◽

P. K. Bhartia

Keyword(s):

Tropospheric Ozone ◽

New Technique ◽

Satellite Measurements ◽

A New Technique

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Quantifying and attributing changes in tropospheric ozone from a combination of satellite measurements and models

10.5194/egusphere-egu2020-21123 ◽

2020 ◽

Author(s):

Jessica Neu ◽

Kazuyuki Miyazaki ◽

Kevin Bowman ◽

Gregory Osterman

Keyword(s):

Time Series ◽

Tropospheric Ozone ◽

Earth Science ◽

Satellite Measurements ◽

Science Data ◽

The Past ◽

Long Term Changes ◽

Earth Science Data

<p>Given the importance of tropospheric ozone as a greenhouse gas and a hazardous pollutant that impacts human health and ecosystems, it is critical to quantify and understand long-term changes in its abundance.&#160; Satellite records are beginning to approach the length needed to assess variability and trends in tropospheric ozone, yet an intercomparison of time series from different instruments shows substantial differences in the net change in ozone over the past decade.&#160; We discuss our efforts to produce Earth Science Data Records of tropospheric ozone and quantify uncertainties and biases in these records.&#160; We also discuss the role of changes in the magnitude and distribution of precursor emissions and in downward transport of ozone from the stratosphere in determining tropospheric ozone abundances over the past 15 years.</p>

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