On estimation of atmospheric scattering characteristics from spectral measurements of solar radiation using machine learning algorithms

Stanislav V. Nikitin; Alexey I. Chulichkov; Alexander N. Borovski; Oleg V. Postylyakov

doi:10.1117/12.2574237

21 September 2020 On estimation of atmospheric scattering characteristics from spectral measurements of solar radiation using machine learning algorithms

Stanislav V. Nikitin, Alexey I. Chulichkov, Alexander N. Borovski, Oleg V. Postylyakov

Author Affiliations +

Proceedings Volume 11531, Remote Sensing of Clouds and the Atmosphere XXV; 115310V (2020) https://doi.org/10.1117/12.2574237
Event: SPIE Remote Sensing, 2020, Online Only

Conference Poster

Abstract

Determination of the content of trace gases (such as, for example, NO2, formaldehyde) by DOAS (differential optical absorption spectroscopy) method in the lower troposphere can be difficult with significant scattering of light on clouds and aerosol. Often, the parameters of cloudiness and aerosol are unknown for specific DOAS measurements, and, therefore, the estimation of these parameters directly from the DOAS analysis data is an approach that could increase the final measurement accuracy of trace gases. In this work, we consider the problems of retrieving such characteristics as: cloud bottom height, cloud optical depth, aerosol optical depth, F-factor (a factor reciprocal to air mass factor) from the input data obtained during DOAS analysis. To do this, we trained and compared two machine learning (ML) models - neural network and random forest. Both ML algorithms solve the regression problem; data obtained by numerical computation by linearized radiative transfer model were used as a learning dataset. The dependence of the error on the test dataset depending on the regularizing parameters was investigated for the neural network. Retrieval errors of aerosol and cloud characteristics were preliminary estimated.

Citation Download Citation

Stanislav V. Nikitin, Alexey I. Chulichkov, Alexander N. Borovski, and Oleg V. Postylyakov "On estimation of atmospheric scattering characteristics from spectral measurements of solar radiation using machine learning algorithms", Proc. SPIE 11531, Remote Sensing of Clouds and the Atmosphere XXV, 115310V (21 September 2020); https://doi.org/10.1117/12.2574237

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available