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Carbon Monitoring Satellite (CarbonSat): assessment of scattering related atmospheric CO2 and CH4 retrieval errors and first results on implications for inferring city CO2 emissions

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons62381

Gerbig,  Christoph
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Buchwitz, M., Reuter, M., Bovensmann, H., Pillai, D., Heymann, J., Schneising, O., et al. (2013). Carbon Monitoring Satellite (CarbonSat): assessment of scattering related atmospheric CO2 and CH4 retrieval errors and first results on implications for inferring city CO2 emissions. Atmospheric Measurement Techniques, 6(12), 3477-3500. doi:10.5194/amt-6-3477-2013.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-7906-7
Abstract
Carbon Monitoring Satellite (CarbonSat) is one of two candidate missions for ESA’s Earth Explorer 8 (EE8) satellite – the selected one to be launched around the end of this decade. The objective of the CarbonSat mission is to improve our understanding of 5 natural and anthropogenic sources and sinks of the two most important anthropogenic greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4). The unique feature of CarbonSat is its “GHG imaging capability”, which is achieved via a combination of high spatial resolution (2 km×2 km) and good spatial coverage (wide swath and gap-free across- and along-track ground sampling). This capability enables global 10 imaging of localized strong emission source such as cities, power plants, methane seeps, landfills and volcanos and better disentangling of natural and anthropogenic GHG sources and sinks. Source/sink information can be derived from the retrieved atmospheric column-averaged mole fractions of CO2 and CH4, i.e. XCO2 and XCH4, via inverse modeling. Using the most recent instrument and mission specification, an 15 error analysis has been performed using the BESD/C retrieval algorithm. We focus on systematic errors due to aerosols and thin cirrus clouds, as this is the dominating error source especially with respect to XCO2 systematic errors. To compute the errors for each single CarbonSat observation in a one year time period, we have developed an error parameterization scheme based on six relevant input parameters: we con20 sider solar zenith angle, surface albedo in two bands, aerosol and cirrus optical depth, and cirrus altitude variations but neglect, for example, aerosol type variations. Using this method we have generated and analyzed one year of simulated CarbonSat observations. Using this data set we estimate that scattering related systematic errors are mostly (approx. 85 %) below 0.3 ppm for XCO2 (<0.5 ppm: 99.5 %) and below 2 ppb for 25 XCH4 (<4 ppb: 99.3%). We also show that the single measurement precision is typically around 1.2 ppm for XCO2 and 7 ppb for XCH4 (1-sigma). The number of quality filtered observations over cloud and ice free land surfaces is in the range 33–47 million per month depending on month. Recently it has been shown that terrestrial Vegetation Chlorophyll Fluorescence (VCF) emission needs to be considered for accurate XCO2 retrieval. We therefore retrieve VCF from clear Fraunhofer lines located at 755nm and show that CarbonSat will provide valuable information on VCF. The VCF single measurement precision is approximately 0.3mWm−2 nm−1 sr−1 (1-sigma). As a first appli- 5 cation of the one year data set we assess the capability of CarbonSat to quantify the CO2 emissions of large cities using Berlin, the capital of Germany, as an example. We show that the precision of the inferred Berlin CO2 emissions as obtained from single CarbonSat overpasses is in the range 5–10 MtCO2 yr−1 (10–20 %). We found that systematic errors could be on the same order depending on which assumptions are used 10 with respect to observational and biogenic XCO2 modeling errors.