Abstract
Satellite retrievals of the atmospheric dry-air column-average mole fraction of CO 2 (XCO 2 ) based on hyperspectral measurements in appropriate near (NIR) and short wave infrared (SWIR) O 2 and CO 2 absorption bands can help to answer important questions about the carbon cycle but the precision and accuracy requirements for XCO 2 data products are demanding. Multiple scattering of light at aerosols and clouds can be a significant error source for XCO 2 retrievals. Therefore, so called full physics retrieval algorithms were developed aiming to minimize scattering related errors by explicitly fitting scattering related properties such as cloud water/ice content, aerosol optical thickness, cloud height, etc. However, the computational costs for multiple scattering radiative transfer (RT) calculations can be immense. Processing all data of the Orbiting Carbon Observatory-2 (OCO-2) can require up to thousands of CPU cores and the next generation of CO 2 monitoring satellites will produce at least an order of magnitude more data. Here we introduce the Fast atmOspheric traCe gAs retrievaL FOCAL including a scalar RT model which approximates multiple scattering effects with an analytic solution of the RT problem of an isotropic scattering layer and a Lambertian surface. The computational performance is similar to an absorption only model and currently determined by the convolution of the simulated spectra with the instrumental line shape function (ILS). We assess FOCAL’s quality by confronting it with accurate multiple scattering vector RT simulations using SCIATRAN. The simulated scenarios do not cover all possible geophysical conditions but represent, among others, some typical cloud and aerosol scattering scenarios with optical thicknesses of up to 0.7 which have the potential to survive the pre-processing of a XCO 2 algorithm for real OCO-2 measurements. Systematic errors of XCO 2 range from −2.5 ppm (−6.3‰) to 3.0 ppm (7.6‰) and are usually smaller than ±0.3 ppm (0.8‰). The stochastic uncertainty of XCO 2 is typically about 1.0 ppm (2.5‰). FOCAL simultaneously retrieves the dry-air column-average mole fraction of H 2 O (XH 2 O) and the solar induced chlorophyll fluorescence at 760 nm (SIF). Systematic and stochastic errors of XH 2 O are most times smaller than ±6 ppm and 9 ppm, respectively. The systematic SIF errors are always below 0.02 mW/m 2 /sr/nm, i.e., it can be expected that instrumental or forward model effects causing an in-filling of the used Fraunhofer lines will dominate the systematic errors when analyzing actually measured data. The stochastic uncertainty of SIF is usually below 0.3 mW/m 2 /sr/nm. Without understating the importance of analyzing synthetic measurements as presented here, the actual retrieval performance can only be assessed by analyzing measured data which is subject to part 2 of this publication.
Highlights
Satellite retrievals of the atmospheric dry-air column-average mole fraction of CO2 (XCO2) based on hyperspectral measurements in appropriate near (NIR) and short wave infrared (SWIR) O2 and CO2 absorption bands can help to answer pressing questions about the carbon cycle [1]
We are interested in XCO2 retrieval results of high quality; the correct retrieval of other state vector elements is less important as long as the XCO2 quality is not affected
The systematic errors of the baseline scenario are always very small (0.03 ppm at maximum), which confirms the radiative transfer (RT) consistency in the absorption only case and ensures that, e.g., the number of particles is basically identical in the SCIATRAN and the FOCAL “world”
Summary
Satellite retrievals of the atmospheric dry-air column-average mole fraction of CO2 (XCO2) based on hyperspectral measurements in appropriate near (NIR) and short wave infrared (SWIR) O2 and CO2 absorption bands can help to answer pressing questions about the carbon cycle [1]. The needed RT calculations with multiple scattering (especially with polarization) can produce computational costs which are several orders of magnitude larger than for absorption only models This is true even when making use of short cuts and approximations such as the low streams interpolation method [12], correlated-k method [16], or neglecting RT effects like polarization [17]. We propose a scalar RT model which approximates multiple scattering effects at an optically thin isotropic scattering layer with only little extra computational costs compared to an absorption only RT model Whilst part 1 of this publication is on theoretical aspects of the RT and the retrieval, part 2 [25] deals with the application to measured OCO-2 data including noise model, zero level offset, pre- and post-filtering, bias correction, and validation
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