Carbonsat instrument pre- developments: towards monitoring carbon dioxide and methane concentrations from space

Abstract

, by combining a wide swath (250 km) with high spatial sampling of (6 km 2 ). This combination allows for separately addressing both, biogenic and anthropogenic fluxes of CO 2 and CH 4 at regional to local scales. The challenging mission objectives and the need to quantify small local differences in concentrations of greenhouse gases lead to demanding radiometric and spectral requirements for the instrument. Detailed instrument concepts were developed by two independent industrial consortia, resulting in consolidated designs for space-borne push-broom imaging grating spectrometers. Despite the similarity of the detection concepts, different choices were made in terms of key technologies, such as diffraction gratings and Sun diffusers. In order to address the specific need of high single-measurement accuracy at high spatial resolution over non-uniform scenes, both consortia devised hardware solutions based on so-called slit homogenisers. The above components have been subject to comprehensive breadboard studies, in order to mitigate development risk and raise the Technology Readiness Level (TRL). This paper provides an overview of these pre-development activities, with emphasis on the selected technologies for diffraction gratings. Laboratory test results for key performance parameters, such as efficiency, polarisation sensitivity and straylight, are shown. In addition, the baseline technologies for solar calibration (Sun diffuser) and non-uniform scene mitigation (slit homogenisers), as well as the corresponding breadboards of these components will be presented.

XCO<sub>2</sub> observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements

“…Currently, the European Commission (EC) and the European Space Agency (ESA) are considering a Copernicus CO 2 monitoring system for monitoring anthropogenic CO 2 emissions using a spectrometer with moderate spectral resolution similar to the assumptions made in this study (Sierk et al, 2018). Aided by a dedicated multi-angle polarimeter (MAP), the system aims at providing XCO 2 products with a spatial resolution of 4 km 2 (over a > 200 km swath) with a singlesounding accuracy better than 0.7 ppm and a systematic error less than 0.5 ppm.…”

“…This study focuses on the use of OCO-2 data with its specific radiometric performance, which thus do not fully cover the spectral range of the CO 2 M mission. SNR requirements for the Copernicus candidate mission have been derived to meet the targeted single-sounding precision, taking into account the selected spectral resolution (Sierk et al, 2018).…”

“…The selected moderate spectral resolution is expected to reduce the sensitivity to instrument errors, e.g., distortions of the instrument spectral response function (ISRF) and detector nonlinearity. It also enables the use of low-order diffraction grating technologies with high efficiencies and low stray light (Sierk et al, 2016). On the other hand, the design introduces the risk of XCO 2 errors due to spectral interference with other absorbers and enhanced aerosol-induced errors.…”

“…Here the spectral sizing point of MSR-d is adapted from the CarbonSat design. The listed signal-to-noise ratios per spectral sampling for each instrument concept are calculated under the same incoming radiance of 75.2, 10.4, and 2.4 W m −2 sr µm −1 for the 0.76, 1.61, and 2.06 µm bands, respectively (Sierk et al, 2018 To retrieve CO 2 columns from spaceborne earthshine radiance observations in the 0.76, 1.61, and 2.06 µm spectral ranges with different spectral resolutions, we use the Re-moTeC full-physics retrieval algorithm (Hasekamp and Butz, 2008), which was first applied for GOSAT measurements and later extensively used for greenhouse gas retrievals of different missions including GOSAT, OCO-2, and Sentinel-5P (Butz et al, 2009;Schepers et al, 2012;Guerlet et al, 2013;Hu et al, 2016Hu et al, , 2018Wu et al, 2018). The algorithm employs an iterative inverse scheme combined with an efficient forward radiative transfer model developed by Landgraf et al (2001), Hasekamp and Landgraf (2005), Hasekamp and Butz (2008), and Schepers et al (2014).…”