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 is not yet available. Here we introduce such an algorithm for retrieving GHGs from LEO-LEO infraredlaser occultation (LIO) data, applied as a second step after retrieving thermodynamic profiles from LEO-LEO microwave occultation (LMO) data. We thoroughly describe the LIO retrieval algorithm and unveil the synergy with the LMOretrieved 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-toend simulations for a representative set of GHG profiles, including carbon dioxide (CO 2 ), water vapor (H 2 O), methane (CH 4 ), and ozone (O 3 ). The GHGs except for ozone are well Correspondence to: V. Proschek (veronika.proschek@uni-graz.at) retrieved throughout the UTLS, while ozone is well retrieved from about 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.

Abstract. LEO-LEO infrared-laser occultation (LIO) is a new occultation technique between Low Earth Orbit (LEO)satellites, which applies signals in the short wave infrared spectral range (SWIR) within 2 µm to 2.5 µm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO) method that enables to retrieve thermodynamic profiles (pressure, temperature, humidity) and altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss these influences, assessing effects from refraction, trace species absorption, aerosol extinction and Rayleigh scattering in detail, and addressing clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation as well. We show that the influence of refractive defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle with a close frequency spacing of LIO absorption and reference signals within 0.5 %. The influences of Rayleigh scattering and terrestrial thermal radiation are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions, but this influence can be made negligible by a close time spacing (within 5 ms) of interleaved laser-pulse and background signals. Cloud extinction loss generally blocks SWIR signals, except very thin or sub-visible cirrus clouds, which can be addressed by retrieving a cloud layering profile and exploiting it in the trace species retrieval. Wind can have a small influence on the trace species absorption, which can be made negligible by using a simultaneously retrieved or a moderately accurate

LEO-LEO infrared-laser occultation (LIO) is a new occultation technique between Low Earth Orbit (LEO) satellites, which applies signals in the short wave infrared spectral range (SWIR) within 2 μm to 2.5 μm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO) method, recently introduced by Kirchengast and Schweitzer (2011), that enables to retrieve thermodynamic profiles (pressure, temperature, humidity) and accurate altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. For enabling trace species retrieval based on differential transmission, the LIO signals are spectrally located as pairs, one in the centre of a suitable absorption line of a target species (absorption signal) and one close by but outside of any absorption lines (reference signal). Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss the atmospheric influences on the transmission and differential transmission of LIO signals. Refraction effects, trace species absorption (by target species, and cross-sensitivity to foreign species), aerosol extinction and Rayleigh scattering are studied in detail. The influences of clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation are discussed as well. We show that the influence of defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle and by a design with close frequency spacing of absorption and reference signals within 0.5 %. The influences of Rayleigh scattering and thermal radiation on the received signal intensities are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions but this influence can be as well made negligible by a design with a close time spacing (within 5 ms) of interleaved laser-pulse and background signals. Cloud extinction loss generally blocks SWIR signals, except very thin or sub-visible cirrus clouds, which can be addressed by a design allowing retrieval of a cloud layering profile from reference signals and its use in trace species retrieval when scanning through intermittent upper tropospheric cloudiness. Wind can have a small influence via Doppler shift resulting in a slightly modified trace species absorption in comparison to calm air, which can be made negligible by using a simultaneously retrieved wind speed profile or a moderately accurate (to about 10 m s⁻¹) background wind profile. Considering all these influences, we conclude that the set of SWIR channels proposed for implementing the LMIO method (Kirchengast et al., 2010; Kirchengast and Schweitzer, 2011) provides adequate sensitivity to accurately retrieve eight greenhouse gas/isotope trace species...

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 (CO₂), water vapor (H₂O), methane (CH₄), and ozone (O₃). 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

We analyzed the observations of scintillations in a laser beam (532 nm, ~200 mW power) traveling along a 144 km path at an altitude of 2.2-2.4 km above sea level, just above the atmospheric boundary layer, between the islands of La Palma and Tenerife. The observations were performed during nighttime on 18 July 2011, by means of a telescope with an aperture diameter of 1 m. Strong scintillations were observed. The estimates of spatial spectra and correlation functions indicated that the observed intensity fields possess, statistically, a locally isotropic structure, which agrees with the idea of a locally isotropic turbulence. The estimates of spatial autospectra and autocorrelation functions of the intensity field indicated that the characteristic scale of the internal structure of the observed clusters is 6.5-8 mm, while the characteristic size of the clusters is 4-5 cm. The major contribution to the observed scintillations comes from the inhomogeneities of the intensity field with scales from 1-2 cm up to 10-12 cm. The analysis of the cross-spectra indicated that the hypothesis of frozen turbulence introduced by Taylor can be used for the description of spatiotemporal structure of intensity fluctuations of laser beams traveling through long paths in the atmosphere.

Abstract.The new mission concept of microwave and infrared-laser occultation between low-Earth-orbit satellites (LMIO) is designed to provide accurate and long-term stable profiles of atmospheric thermodynamic variables, greenhouse gases (GHGs), and line-of-sight (l.o.s.) wind speed with focus on the upper troposphere and lower stratosphere (UTLS). While the unique quality of GHG retrievals enabled by LMIO over the UTLS has been recently demonstrated based on end-to-end simulations, the promise of l.o.s. wind retrieval, and of joint GHG and wind retrieval, has not yet been analyzed in any realistic simulation setting. Here we use a newly developed l.o.s. wind retrieval algorithm, which we embedded in an end-to-end simulation framework that also includes the retrieval of thermodynamic variables and GHGs, and analyze the performance of both stand-alone wind retrieval and joint wind and GHG retrieval. The wind algorithm utilizes LMIO laser signals placed on the inflection points at the wings of the highly symmetric C 18 OO absorption line near 4767 cm −1 and exploits transmission differences from a wind-induced Doppler shift. Based on realistic example cases for a diversity of atmospheric conditions, ranging from tropical to high-latitude winter, we find that the retrieved l.o.s. wind profiles are of high quality over the lower stratosphere under all conditions, i.e., unbiased and accurate to within about 2 m s −1 over about 15 to 35 km. The wind accuracy degrades into the upper troposphere due to the decreasing signal-to-noise ratio of the wind-induced differential transmission signals. The GHG retrieval in windy air is not vulnerable to wind speed uncertainties up to about 10 m s −1 but is found to benefit in the case of higher speeds from the integrated wind retrieval that enables correction of wind-induced Doppler shift of GHG signals. Overall both the l.o.s. wind and GHG retrieval results are strongly encouraging towards further development and implementation of a LMIO mission.

The new mission concept of microwave and infrared‐laser occultation between Low Earth Orbit satellites (LMIO) is capable to provide accurate, consistent, and long‐term stable measurements of many essential climate variables. These include temperature, humidity, key greenhouse gases (GHGs) such as carbon dioxide and methane, and line of sight wind speed, all with focus on profiling the upper troposphere and lower stratosphere. The GHG retrieval performance from LMIO data was so far analyzed under clear‐air conditions only, without clouds and scintillations from turbulence. Here we present and evaluate an algorithm, built into an already published clear‐air algorithm, which copes with cloud and scintillation influences on the infrared‐laser transmission profiles used for GHG retrieval. We find that very thin ice clouds fractionally extinct the infrared‐laser signals, thicker but broken ice clouds block them over limited altitude ranges, and liquid water clouds generally block them so that their cloud top altitudes typically constitute the limit to tropospheric penetration of profiles. The advanced algorithm penetrates through broken cloudiness. It achieves this by producing a cloud flagging profile from cloud‐perturbed infrared‐laser signals, which then enables bridging of transmission profile gaps via interpolation. Evaluating the retrieval performance with quasi‐realistic end‐to‐end simulations, including high‐resolution cloud data and scintillations from turbulence, we find a small increase only of GHG retrieval RMS errors due to broken‐cloud scenes and the profiles remain essentially unbiased as in clear air. These results are encouraging for future LMIO implementation, indicating that GHG profiles can be retrieved through broken cloudiness, maximizing upper troposphere coverage.

Abstract.A new technique for the satellite remote sensing of greenhouse gases in the atmosphere via the absorption of short-wave infrared laser signals transmitted between counter-rotating satellites in low Earth orbit has recently been proposed; this would enable the acquisition of a longterm, stable, global set of altitude-resolved concentration measurements. We present the first ground-based experimental demonstration of this new infrared-laser occultation method, in which the atmospheric absorption of CO 2 near 2.1 µm was measured over a ∼ 144 km path length between two peaks in the Canary Islands (at an altitude of ∼ 2.4 km), using relatively low power diode lasers (∼ 4 to 10 mW). The retrieved CO 2 volume mixing ratio of 400 ppm (± 15 ppm) is consistent within experimental uncertainty with simultaneously recorded in situ validation measurements. We conclude that the new method has a sound basis for monitoring CO 2 in the free atmosphere; other greenhouse gases such as methane, nitrous oxide and water vapour can be monitored in the same way.