Work

A comparison of data-driven and physics-informed statistical learning models for atmospheric remote sensing applications

Year: 2026

Type: article

Source: Journal of Quantitative Spectroscopy and Radiative Transfer

DOI: 10.1016/j.jqsrt.2026.110011

Authors: Frédéric Andre, Xijiade Aihemaiti, Tao Ren, Loïc Guilmard, François Thieuleux, Nada Mourtaday, Antoine Rimboud, Somesh P. Roy, Céline Cornet, Laurent C. Labonnotte, Jérôme Riedi

Institutions: Centre National de la Recherche Scientifique, Université de Lille, Laboratoire d'Optique Atmosphérique, Shanghai Jiao Tong University, Centre d'Énergétique et de Thermique de Lyon, Institut National des Sciences Appliquées de Lyon, Marquette University

Language: English

Topic: Radiative Heat Transfer Studies

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

SDG: Climate action

Open Access status: green

Funders: Agence Nationale de la Recherche, National Natural Science Foundation of China, Shanghai Jiao Tong University

Awards: Advanced Spectral models of GAs RaDiation, G575936601

OpenAlex ID: W7162567011

FWCI: 4.204

Cites: 26

Cited by: 2

Related to: 10