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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 10, 4165-4190, 2017
https://doi.org/10.5194/amt-10-4165-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
07 Nov 2017
Line-averaging measurement methods to estimate the gap in the CO2 balance closure – possibilities, challenges, and uncertainties
Astrid Ziemann1, Manuela Starke1, and Claudia Schütze2 1Chair of Meteorology, TU Dresden, 01062 Dresden, Germany
2Department for Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany
Abstract. An imbalance of surface energy fluxes using the eddy covariance (EC) method is observed in global measurement networks although all necessary corrections and conversions are applied to the raw data. Mainly during nighttime, advection can occur, resulting in a closing gap that consequently should also affect the CO2 balances. There is the crucial need for representative concentration and wind data to measure advective fluxes. Ground-based remote sensing techniques are an ideal tool as they provide the spatially representative CO2 concentration together with wind components within the same voxel structure. For this purpose, the presented SQuAd (Spatially resolved Quantification of the Advection influence on the balance closure of greenhouse gases) approach applies an integrated method combination of acoustic and optical remote sensing. The innovative combination of acoustic travel-time tomography (A-TOM) and open-path Fourier-transform infrared spectroscopy (OP-FTIR) will enable an upscaling and enhancement of EC measurements. OP-FTIR instrumentation offers the significant advantage of real-time simultaneous measurements of line-averaged concentrations for CO2 and other greenhouse gases (GHGs). A-TOM is a scalable method to remotely resolve 3-D wind and temperature fields. The paper will give an overview about the proposed SQuAd approach and first results of experimental tests at the FLUXNET site Grillenburg in Germany.

Preliminary results of the comprehensive experiments reveal a mean nighttime horizontal advection of CO2 of about 10 µmol m−2 s−1 estimated by the spatially integrating and representative SQuAd method. Additionally, uncertainties in determining CO2 concentrations using passive OP-FTIR and wind speed applying A-TOM are systematically quantified. The maximum uncertainty for CO2 concentration was estimated due to environmental parameters, instrumental characteristics, and retrieval procedure with a total amount of approximately 30 % for a single measurement. Instantaneous wind components can be derived with a maximum uncertainty of 0.3 m s−1 depending on sampling, signal analysis, and environmental influences on sound propagation. Averaging over a period of 30 min, the standard error of the mean values can be decreased by a factor of at least 0.5 for OP-FTIR and 0.1 for A-TOM depending on the required spatial resolution. The presented validation of the joint application of the two independent, nonintrusive methods is in the focus of attention concerning their ability to quantify advective fluxes.


Citation: Ziemann, A., Starke, M., and Schütze, C.: Line-averaging measurement methods to estimate the gap in the CO2 balance closure – possibilities, challenges, and uncertainties, Atmos. Meas. Tech., 10, 4165-4190, https://doi.org/10.5194/amt-10-4165-2017, 2017.
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Short summary
There is a crucial need for adequate data of concentration and wind to close the potential gap in mass balance of CO2. Ground-based line-integrating remote sensing techniques are an ideal tool as they provide the spatially representative CO2 concentration together with wind components within the same voxel structure. An integrated method combination of acoustic and optical systems was applied to measure spatially representative CO2 advection at the grassland Grillenburg site.
There is a crucial need for adequate data of concentration and wind to close the potential gap...
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