the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm
Thomas E. Taylor
Christopher W. O'Dell
David Crisp
Akhiko Kuze
Hannakaisa Lindqvist
Paul O. Wennberg
Abhishek Chatterjee
Michael Gunson
Annmarie Eldering
Brendan Fisher
Matthäus Kiel
Robert R. Nelson
Aronne Merrelli
Greg Osterman
Frédéric Chevallier
Paul I. Palmer
Liang Feng
Nicholas M. Deutscher
Manvendra K. Dubey
Dietrich G. Feist
Omaira E. García
David W. T. Griffith
Frank Hase
Laura T. Iraci
Rigel Kivi
Cheng Liu
Martine De Mazière
Isamu Morino
Justus Notholt
Young-Suk Oh
Hirofumi Ohyama
David F. Pollard
Markus Rettinger
Matthias Schneider
Coleen M. Roehl
Mahesh Kumar Sha
Kei Shiomi
Kimberly Strong
Ralf Sussmann
Voltaire A. Velazco
Mihalis Vrekoussis
Thorsten Warneke
Debra Wunch
Related authors
We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Evaluation of measurement data – Guide to the expression of uncertainty in measurementissued by the JCGM, the error concept and the uncertainty concept are the same. Arguments in favor of the contrary were found not to be compelling. Neither was any evidence presented that
errorsand
uncertaintiesdefine a different relation between the measured and true values, nor is a Bayesian concept beyond the mere subjective probability referred to.