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

Abstract

AbstractThe 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.