Retrieval techniques and information content analysis to improve remote sensing of atmospheric water vapor, liquid water and temperature from ground-based microwave radiometer measurements

Observation of profiles of temperature, humidity and winds with sufficient accuracy and fine vertical and temporal resolution are needed to improve mesoscale weather prediction, track conditions in the lower to mid-troposphere, predict winds for renewable energy, inform the public of severe weather and improve transportation safety. In comparing these thermodynamic variables, the absolute atmospheric temperature varies only by 15%; in contrast, total water vapor may change by up to 50% over several hours. In addition, numerical weather prediction (NWP) models are initialized using water vapor profile information, so improvements in their accuracy and resolution tend to improve the accuracy of NWP. Current water vapor profile observation systems are expensive and have insufficient spatial coverage to observe humidity in the lower to mid-troposphere. To address this important scientific need, the principal objective of this dissertation is to improve the accuracy, vertical resolution and revisit time of tropospheric water vapor profiles retrieved from microwave and millimeter-wave brightness temperature measurements.;This dissertation advances the state of knowledge of retrieval of atmospheric water vapor from microwave brightness temperature measurements. It focuses on optimizing two information sources of interest for water vapor profile retrieval, i.e. independent measurements and background data set size. From a theoretical perspective, it determines sets of frequencies in the ranges of 20-23, 85-90 and 165-200 GHz that are optimal for water vapor retrieval from each of ground-based and airborne radiometers. The maximum number of degrees of freedom for the selected frequencies for ground-based radiometers is 5-6, while the optimum vertical resolution is 0.5 to 1.5 km. On the other hand, the maximum number of degrees of freedom for airborne radiometers is 8-9, while the optimum vertical resolution is 0.2 to 0.5 km. From an experimental perspective, brightness temperature data sets from the HUMEX11 and DYNAMO field experiments have been used to improve knowledge of the impact of the background information on retrieval of water vapor profiles and estimation of water vapor and liquid water using low elevation angle data sets. HUMEX11 measurements have been used to improve retrieval performance by choosing optimal atmospheric a-priori statistics of 35-55 profiles and layer thickness of 100-m to detect dynamic changes and gradients. DYNAMO measurements have been used to retrieve slant water path and slant liquid water with estimated error of less than 10% and 25%, respectively, for all elevation angles of interest.;These theoretical and experimental advances improve understanding of retrievals using microwave brightness temperature and extend them to more challenging applications, including sudden atmospheric gradients and slant path delay retrieval for elevation angles as low as 5º. (Abstract shortened by UMI.).