Articles | Volume 14, issue 12
Atmos. Meas. Tech., 14, 7511–7524, 2021
https://doi.org/10.5194/amt-14-7511-2021
Atmos. Meas. Tech., 14, 7511–7524, 2021
https://doi.org/10.5194/amt-14-7511-2021

Research article 03 Dec 2021

Research article | 03 Dec 2021

Assessing the feasibility of using a neural network to filter Orbiting Carbon Observatory 2 (OCO-2) retrievals at northern high latitudes

Joseph Mendonca et al.

Data sets

GES DISC data NASA https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Lite_FP.10r/

TCCON data from Bremen (DE) J. Notholt, C. Petri, T. Warneke, N. M. Deutscher, M. Palm, M. Buschmann, C. Weinzierl, R. C. Macatangay, and P. Grupe https://doi.org/10.14291/TCCON.GGG2014.BREMEN01.R1

TCCON data from Bialystok (PL) N. M. Deutscher, J. Notholt, J. Messerschmidt, C. Weinzierl, T. Warneke, C. Petri, and P. Grupe https://doi.org/10.14291/TCCON.GGG2014.BIALYSTOK01.R2

TCCON data from Sodankylä (FI) R. Kivi, P. Heikkinen, and E. Kyrö https://doi.org/10.14291/TCCON.GGG2014.SODANKYLA01.R0/1149280

TCCON data from Ny Ålesund, Spitsbergen (NO) J. Notholt, T. Warneke, C. Petri, N. M. Deutscher, C. Weinzierl, M. Palm, and M. Buschmann https://doi.org/10.14291/TCCON.GGG2014.NYALESUND01.R1

TCCON data from East Trout Lake, SK (CA) D. Wunch, J. Mendonca, O. Colebatch, N. T. Allen, J.-F. Blavier, S. Roche, J. Hedelius, G. Neufeld, S. Springett, D. Worthy, R. Kessler, and K. Strong https://doi.org/10.14291/TCCON.GGG2014.EASTTROUTLAKE01.R1

TCCON data from Eureka (CA) K. Strong, S. Roche, J. E. Franklin, J. Mendonca, E. Lutsch, D. Weaver, P. F. Fogal, J. R. Drummond, R., Batchelor, and R. Lindenmaier https://doi.org/10.14291/TCCON.GGG2014.EUREKA01.R3

TCCON data from Park Falls (US) P. O. Wennberg, C. M. Roehl, D. Wunch, G. C. Toon, J.-F. Blavier, R. Washenfelder, G. Keppel-Aleks, N. T. Allen, and J. Ayers https://doi.org/10.14291/TCCON.GGG2014.PARKFALLS01.R1

TCCON data from Rikubetsu (JP) I. Morino, N. Yokozeki, T. Matsuzaki, and M. Horikawa https://doi.org/10.14291/TCCON.GGG2014.RIKUBETSU01.R2

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Short summary
Machine learning has become an important tool for pattern recognition in many applications. In this study, we used a neural network to improve the data quality of OCO-2 measurements made at northern high latitudes. The neural network was trained and used as a binary classifier to filter out bad OCO-2 measurements in order to increase the accuracy and precision of OCO-2 XCO2 measurements in the Boreal and Arctic regions.