Greenhouse gas profiling by infrared-laser and microwave occultation: retrieval algorithm and demonstration results from end-to-end simulations

Abstract

Measuring greenhouse gas (GHG) profiles with global coverage and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS) is key for improved monitoring of GHG concentrations in the free atmosphere. In this respect a new satellite mission concept adding an infrared-laser part to the already well studied microwave occultation technique exploits the joint propagation of infrared-laser and microwave signals between Low Earth Orbit (LEO) satellites. This synergetic combination, referred to as LEO-LEO microwave and infrared-laser occultation (LMIO) method, enables to retrieve thermodynamic profiles (pressure, temperature, humidity) and accurate altitude levels from the microwave signals and GHG profiles from the simultaneously measured infrared-laser signals. However, due to the novelty of the LMIO method, a retrieval algorithm for GHG profiling did not yet exist. Here we introduce such an algorithm for retrieving GHGs from LEO-LEO infrared-laser occultation (LIO) data, applied as a second step after retrieving thermodynamic profiles from LEO-LEO microwave occultation (LMO) data as recently introduced in detail by Schweitzer et al. (2011b). We thoroughly describe the LIO retrieval algorithm and unveil the synergy with the LMO-retrieved pressure, temperature, and altitude information. We furthermore demonstrate the effective independence of the GHG retrieval results from background (a priori) information in discussing demonstration results from LMIO end-to-end simulations for a representative set of GHG profiles, including carbon dioxide (CO<sub>2</sub>), water vapor (H<sub>2</sub>O), methane (CH<sub>4</sub>), and ozone (O<sub>3</sub>). The GHGs except for ozone are well retrieved throughout the UTLS, while ozone is well retrieved from 10 km to 15 km upwards, since the ozone layer resides in the lower stratosphere. The GHG retrieval errors are generally smaller than 1% to 3% r.m.s., at a vertical resolution of about 1 km. The retrieved profiles also appear unbiased, which points to the climate benchmarking capability of the LMIO method. This performance, found here for clear-air atmospheric conditions, is unprecedented for vertical profiling of GHGs in the free atmosphere and encouraging for future LMIO implementation. Subsequent work will examine GHG retrievals in cloudy air, addressing retrieval performance when scanning through intermittent upper tropospheric cloudiness

Greenhouse gas profiling by infrared‐laser and microwave occultation in cloudy air: Results from end‐to‐end simulations

“…Building on the LMIO forward modeling and retrieval capabilities in clear air, presented in detail by Proschek et al [], we developed appropriate capabilities for cloudy air. In this section we describe how we parameterized cloud influences in the forward modeling, how these influences affect the LIO signals, and how we set up and carried out the LIO forward simulations.…”

“…The basic settings for the simulations were taken to be the same as described in section 2.2 of Proschek et al [], which is why we focus here on the differences to those settings needed for the present end‐to‐end simulations. In the FOM simulations, we used the so‐called “Ideal Geometry” mode for the LEO orbits, providing for vertical occultation event planes at user‐specified tangent point locations with user‐specified azimuthal orientation that enable to well match high‐resolution cloud cross sections from CALIPSO nadir scans.…”

“…These errors are superposed on the forward modeled signals by the OSM subsystem of xEGOPS/EGOPS. They were modeled in the same way in this study as by Proschek et al [], where they are described in detail.…”

“…Building on other pioneering work on the LMIO method and the ACCURATE mission concept as cited above, Proschek et al [] introduced a novel algorithm for GHG retrieval from infrared (IR)‐laser signal data, as part of LMIO data, and proved it to work well under clear‐air conditions. IR‐laser signals are very sensitive to clouds, however, from semitransparent thin cirrus clouds that already perturb the signals to liquid water clouds that fully block them.…”

“…The LIO signals feeding the GHG retrieval can be considered intermittently disturbed or blocked by clouds, while the LMO signals are essentially unaffected by clouds [ Emde et al , ] and therefore enable retrieval of thermodynamic profiles (pressure, temperature, humidity) and altitude leveling information also into and through clouds [ Schweitzer et al , ]. Otherwise the measurement geometry and setup are identical as for clear‐air conditions and have been discussed in detail by Kirchengast and Schweitzer [] and Proschek et al [].…”