CO2Image retrieval studies and performance analysis
- 1German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Germany
- 2German Aerospace Center (DLR), Institute of Atmospheric Physics (IPA), Germany
- 3University of Heidelberg, Institute of Environmental Physics, Germany
Current and planned satellite missions such as the Japanese GOSAT (Greenhouse Gases Observing Satellite) and NASA’s OCO (Orbiting Carbon Observatory) series and the upcoming Copernicus Carbon Dioxide Monitoring (CO2M) mission aim to constrain national and regional-scale emissions down to scales of urban agglomerations and large point sources. The CO2Image demonstrator mission of the German Aerospace Center (DLR) is specifically designed to detect and quantify carbon dioxide (CO2) and methane (CH4) emissions from medium-size point sources. To this end its COSIS (Carbon dioxide Sensing Imaging Spectrometer) push-broom grating spectrometer measures reflected solar radiation with a high spatial resolution of 50x50 m2, covering tiles of ~50x50 km2 extent. The instrument has a moderate spectral resolution of approximately ~1 nm and observes in a single spectral window in the 2 µm region.
Here we present and discuss the impact of the expected COSIS performance on the retrieved level-2 data. The level-1 data (spectra) are generated using the Py4CAtS (Python for Computational ATmospheric Spectroscopy) line-by-line radiative transfer model and the COSIS SIMulator (COSIS-SIM). Based on the COSIS instrument parameters the analysis examines the retrieval errors related to noise which allows to estimate the detection and quantification limit of CO2 and CH4 emission rates at the instrument’s spatial and spectral resolution. We further discuss the effect of heterogeneous scenes, i.e. high contrast surfaces that cause an effective distortion of the spectral response function by non-uniform illumination of the entrance slit. Finally, we assess the influence of initial guess values for the plume's vertical extent and shape on the retrieval.
How to cite: Hochstaffl, P., Baumgartner, A., Slijkhuis, S., Lichtenberg, G., Koehler, C. H., Schreier, F., Roiger, A., Feist, D. G., Marshall, J., Butz, A., and Trautmann, T.: CO2Image retrieval studies and performance analysis, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15635, https://doi.org/10.5194/egusphere-egu23-15635, 2023.