Lidar and Microwave Radiometer Synergy for High Vertical Resolution Thermodynamic Profiling,

Continuous monitoring of thermodynamic atmospheric profiles is important for many applications, e.g. assessment of atmospheric stability and cloud formation. Nowadays there is a wide variety of ground-based sensors for atmospheric profiling. Unfortunately there is no single instrument able to provide a measurement with complete vertical coverage, high vertical and temporal resolution, and good performance under all weather conditions, simultaneously. For this reason, in the last decade instrument synergies have become a strong tool used by the scientific community to improve the quality and usage of the atmospheric observations. The current thesis presents the microwave radiometer (MWR) and lidar synergy, which aims to overcome the specific sensor limitations. On the one hand, lidar measurements can provide water vapor or temperature measurements with a high vertical resolution albeit with limited vertical coverage, due to overlapping function (OVF) problems, sunlight contamination and the presence of clouds. On the other hand, MWRs receive water vapor, temperature and cloud information throughout the troposphere though their vertical resolution is poor. The retrieval algorithm combining these two instruments is called Lidar and Microwave Synergetic Optimal Atmospheric Profiler (LIME SOAP) and is based on an Optimal Estimation Method (OEM). The main advantage of this technique with respect to other retrieval algorithms, e.g. neural networks, Kalman filters, etc., is that an OEM allows for an uncertainty assessment of the retrieved atmospheric products. LIME SOAP combines measurements, i.e. MWR brightness temperatures and lidar water vapor mixing ratio and/or temperature profiles, with a priori atmospheric information taking the uncertainty of both into account. The method is applied to two different scenarios, i.e. ground based measurements during a two months campaign in Germany, and airborne measurements over tropical and subtropical Atlantic Ocean, for retrieving high vertical resolution profiles of absolute humidity (AH), temperature (T), relative humidity (RH) and liquid water path (LWP). For all retrievals, the studies in terms of theoretical error and degrees of freedom per signal reveal that the information of the two sensors is optimally combined. In addition, the vertical resolution of the products is improved when the MWR+lidar combination is performed with respect to the instruments working alone. Different experiments are performed to analyze the improvements achieved via the synergy compared to the individual retrievals. Results show that, for example, when applying the LIME SOAP for ground-based AH profiling, on average the theoretically determined absolute humidity uncertainty is reduced by 60% (38%) with respect to the retrieval using only-MWR (only-Raman lidar) data, for two-months data analysis. For temperature, it is shown that the error is reduced by 47.1% (24.6%) with respect to the only-MWR (only-Raman lidar) profile, when using a collocated radiosonde as reference. When retrieving RH, correlation between T and AH is included, which leads to improvements in the retrieved RH with respect to the case when T and AH are calculated independently. In addition it is shown that the Raman lidar T profile is not essential for the T and RH retrievals and using only the MWR temperature information provides products satisfactory for the specific case study. From the airborne perspective of HALO, the lidar non-overlap region is situated in the upper troposphere, where the amount of water vapor is reduced. Thus, the MWR improvement in the blind lidar region has less impact than in the ground based scenario. The benefits of the sensor combination are demonstrated, being especially strong in regions where lidar data is not available, whereas if both instruments are available, the lidar measurements dominate the retrieval

Emerging Technologies and Synergies for Airborne and Space-Based Measurements of Water Vapor Profiles

A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity