A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases

A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases

<p>Satellite observations of dry-column methane mixing ratios (XCH<span class="inline-formula"><sub>4</sub></span>) from shortwave infrared (SWIR) solar backscatter radiation provide a powerful resource to quantify methane emissions in service of climate actio...

Full description

Bibliographic Details
Main Authors: N. Balasus, D. J. Jacob, A. Lorente, J. D. Maasakkers, R. J. Parker, H. Boesch, Z. Chen, M. M. Kelp, H. Nesser, D. J. Varon
Format: Article
Language:English
Published: Copernicus Publications 2023-08-01
Series:Atmospheric Measurement Techniques
Online Access:https://amt.copernicus.org/articles/16/3787/2023/amt-16-3787-2023.pdf

Internet

https://amt.copernicus.org/articles/16/3787/2023/amt-16-3787-2023.pdf

Similar Items