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Open AccessArticle

Comparison of Continuous In-Situ CO2 Measurements with Co-Located Column-Averaged XCO2 TCCON/Satellite Observations and CarbonTracker Model Over the Zugspitze Region

1
Department of Ecology and Ecosystem Management, Technical University of Munich, 85354 Freising, Germany
2
Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
3
German Environment Agency (UBA), GAW Global Observatory Zugspitze-Hohenpeissenberg, 82475 Platform Zugspitze, Germany
4
Department of Mathematics, Technical University of Munich, 85748 Garching, Germany
5
Institute for Advanced Study, Technical University of Munich, 85748 Garching, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(24), 2981; https://doi.org/10.3390/rs11242981
Received: 13 November 2019 / Revised: 9 December 2019 / Accepted: 11 December 2019 / Published: 12 December 2019
(This article belongs to the Special Issue Remote Sensing of Greenhouse Gases and Air Pollution)
Atmospheric CO2 measurements are important in understanding the global carbon cycle and in studying local sources and sinks. Ground and satellite-based measurements provide information on different temporal and spatial scales. However, the compatibility of such measurements at single sites is still underexplored, and the applicability of consistent data processing routines remains a challenge. In this study, we present an inter-comparison among representative surface and column-averaged CO2 records derived from continuous in-situ measurements, ground-based Fourier transform infrared measurements, satellite measurements, and modeled results over the Mount Zugspitze region of Germany. The mean annual growth rates agree well with around 2.2 ppm yr−1 over a 17-year period (2002–2018), while the mean seasonal amplitudes show distinct differences (surface: 11.7 ppm/column-averaged: 6.6 ppm) due to differing air masses. We were able to demonstrate that, by using consistent data processing routines with proper data retrieval and gap interpolation algorithms, the trend and seasonality can be well extracted from all measurement data sets. View Full-Text
Keywords: carbon dioxide; XCO2; in situ; remote sensing; satellite; time-series analysis; seasonality carbon dioxide; XCO2; in situ; remote sensing; satellite; time-series analysis; seasonality
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MDPI and ACS Style

Yuan, Y.; Sussmann, R.; Rettinger, M.; Ries, L.; Petermeier, H.; Menzel, A. Comparison of Continuous In-Situ CO2 Measurements with Co-Located Column-Averaged XCO2 TCCON/Satellite Observations and CarbonTracker Model Over the Zugspitze Region. Remote Sens. 2019, 11, 2981.

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