Mobile remote sensing of atmosphericCO2, CH4, and CO above the Pacific

using a field-qualifiedFourier-transform spectrometer

Marvin Knapp1, Ralph Kleinschek1, Frank Hase2, Anna Agustí-Panareda3, Antje Inness3, Jerome Barre3, Stefan Kinne4, and André Butz1

1Institute of Environmental Physics, Heidelberg University, Germany

2Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Germany3European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK4Max Planck Institute for Meteorology, Hamburg, Germany

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Overview

• We develop a ship-going variant of a mobile Fourier-transform spectrometer1 that allows direct-sunlight observations on the ocean

• The design withstands rain and sea spray and requires low operator attendance

• We retrieve column-average dry-air mole fractions of CO2, CH4, and CO from shortwave-infrared (SWIR) spectra

• The instrument was tested during the Measuring Oceanic REferences 2 (MORE-2) campaign in June 2019

• Observations are validation data for the ECMWF CAMS2 model data and oceanic TROPOMI3 CO measurements

• The instrument may serve as an ocean extension to ground-based satellite validation networks like TCCON4,5 and COCCON6

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Enclosure Design

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Weatherproof enclosure (left) contains an EM27/SUN1 FTS with a custom-built solar tracker (right) to compensate the ships movements during direct-sunlight observations.

The deployed instrument on the research vessel Sonne. Theelectronics are protected by a ventilated and waterproofbox.

This rotatable housing is mounted on the lid andcontains the solar tracker. The direct sunlight beamenters through the round window.

Campaign Route

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This map shows the route of the RV Sonne during the MORE-2 campaign. Blue dots mark measurements of ourinstrument. We observed 33544 spectra from which we calculate atmospheric gas abundances.

Data Processing

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Our measurements of the dry-air column-average mole fractions XCO2, XCH4, and XCO are filtered for corrupteddata and corrected for a well-known spurious airmass dependency (left). To ensure traceability to WorldMeteorological Organization (WMO) standards, we calibrated against the Total Carbon Column Network (TCCON) viaside-by-side measurements on July 23rd 2019 (right).

The airmass-dependency for each species as a plot of eachcampaign observation referenced against a measurement at 45°solar zenith angle (SZA) of the respective fore- (neg. SZA) andafternoon (pos. SZA) against the SZA. We correct theunderestimation at high SZA with a third-order polynomial.

We deployed our instrument in Karlsruhe beside the TCCONstation and performed side-by-side measurements. From the ratioof the EM27/SUN measurements (blue) and the TCCONobservations (orange) we derive a scaling factor to WMOstandards.

preliminary preliminary

Results – Mixing Ratios

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Atmospheric gas abundances measured during the MORE-2 campaign with the EM27/SUN (blue) comparedto CAMS model data (green) and 1783 coincident TROPOMI CO measurements (orange) above the Pacific.

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Results – Mixing Ratios Deviations

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CAMS and TROPOMI data minus ground-based EM27/SUN measurements during the campaign. While CAMSCH4 shows regions of small but consistent under- (180°) or overestimation (160°E), CAMS CO2 and CO agreewell with our measurements. Furthermore, we can validate the TROPOMI CO observations.

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Results

Hourly averages of our observations reacha precision of 0.24 ppm, 1.1 ppb, and 0.75ppb for CO2, CH4, and CO, resp.

We find an excellent agreement betweento CAMS model data and TROPOMIobservations over the Pacific bycalculating the campaign mean deviationfor each species to

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CO2 / ppm CH4 / ppb CO / ppb

CAMS 0.274 ± 0.331 -0.8 ± 4.3 3.1 ± 3.5

TROPOMI - - 2.8 ± 6.2

Furthermore, we compare the observed difference of TROPOMI observations to the ground-based measurements against several quantities which could affect the trace gas retrieval7. There is no dependency of the difference to either the tested parameters, indicating that the TROPOMI retrieval works well for ocean observations.

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References

1. Gisi, M., Hase, F., Dohe, S., Blumenstock, T., Simon, A., Keens, A., 2012. XCO 2 -measurements with a tabletop FTS using solar absorption spectroscopy. Atmos. Meas. Tech. 5, 2969–2980. https://doi.org/10.5194/amt-5-2969-2012

2. Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J.J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., Suttie, M., 2019. The CAMS reanalysis of atmospheric composition. Atmos. Chem. Phys. 19, 3515–3556. https://doi.org/10.5194/acp-19-3515-2019

3. Borsdorff, T., Aan de Brugh, J., Hu, H., Aben, I., Hasekamp, O., Landgraf, J., 2018. Measuring Carbon Monoxide With TROPOMI: First Results and a Comparison With ECMWF-IFS Analysis Data. Geophys. Res. Lett. 45, 2826–2832. https://doi.org/10.1002/2018GL077045

4. Hase, F., Blumenstock, T., Dohe, S., Groß, J., Kiel, M.ä., 2015. TCCON data from Karlsruhe (DE), Release GGG2014.R1. https://doi.org/10.14291/TCCON.GGG2014.KARLSRUHE01.R1/1182416

5. Wunch, D., Toon, G.C., Blavier, J.-F.L., Washenfelder, R.A., Notholt, J., Connor, B.J., Griffith, D.W.T., Sherlock, V., Wennberg, P.O., 2011. The Total Carbon Column Observing Network. Proc. R. Soc. A 369, 2087–2112. https://doi.org/10.1098/rsta.2010.0240

6. Frey, M., Sha, M.K., Hase, F., Kiel, M., Blumenstock, T., Harig, R., Surawicz, G., Deutscher, N.M., Shiomi, K., Franklin, J.E., Bösch, H., Chen, J., Grutter, M., Ohyama, H., Sun, Y., Butz, A., Mengistu Tsidu, G., Ene, D., Wunch, D., Cao, Z., Garcia, O., Ramonet, M., Vogel, F., Orphal, J., 2019. Building the COllaborative Carbon Column Observing Network (COCCON): long-term stability and ensemble performance of the EM27/SUN Fourier transform spectrometer. Atmos. Meas. Tech. 12, 1513–1530. https://doi.org/10.5194/amt-12-1513-2019

7. Landgraf, J., aan de Brugh, J., Scheepmaker, R., Borsdorff, T., Hu, H., Houweling, S., Butz, A., Aben, I., Hasekamp, O., 2016. Carbon monoxide total column retrievals from TROPOMI shortwaveinfrared measurements. Atmos. Meas. Tech. 9, 4955–4975. https://doi.org/10.5194/amt-9-4955-2016

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