Graduate Exam Abstract
August 8, 2013, 10 am
A Study of Accuracy, Vertical Resolution and Temporal Resolution of Remotely-Sensed Water Vapor Profiles Retrieved from Microwave and Millimeter-Wave Radiometry
Abstract: The goal of this study is to improve the accuracy, vertical resolution and revisit time for passive microwave and millimeter-wave remote sensing of total column water vapor as well as its profile in the troposphere. In one sensing modality, ground-based microwave radiometers operating at frequencies near the 22.235 GHz (K-band) water vapor absorption line have been used extensively for remote sensing of water vapor in the troposphere. These ground-based remote sensors are relatively low cost and have the advantage of frequent updates that can be used to track rapid changes as well as gradients in water vapor profiles. Water vapor profiles are necessary to initialize numerical weather prediction (NWP) models, so improvements in their measurement tend to improve the accuracy of NWP models. This is particularly important in the case of ensemble forecasting of convective initiation, which examines the distribution of forecasts under a variety of initial conditions to determine where and when severe weather is likely to begin. Bayesian optimal estimation is commonly used to retrieve water vapor profiles from ground-based microwave radiometer measurements. To explore the capability and performance of this retrieval technique to track rapidly changing water vapor profiles, the HUMidity EXperiment 2011 (HUMEX11) was conducted at the U.S. Department of Energys (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site.
Bayesian optimal estimation requires both radiometric measurements and background statistics as input. The measurements provide the a-posteriori remote sensing information, while the statistics provide a-priori data on the general behavior of the troposphere at a particular place. Each frequency channel measurement provides information needed to retrieve water vapor profiles, but these measurements have a high degree of redundancy. To improve the accuracy and maximize the retrieved profiles vertical resolution, any retrieval algorithm requires as much independent information as possible about the atmospheric parameter. Maximizing the amount of independent information is more complex than just adding as many frequency channels as possible. Instead, it requires selecting the channels that provide the greatest amount of unique information. To address this need, this study will determine the amount of independent information available in the microwave and millimeter-wave frequency range from 10 200 GHz based on weighting function analysis. The results of the study will provide guidance in frequency and bandwidth selection for passive microwave and millimeter-wave radiometry.
Adviser: Prof. Steven C. Reising
Non-ECE Member: Prof. Steven A. Rutledge, Atmospheric Science
Member 3: Prof. Branislav M. Notaros, Electrical and Computer Engineering
Addional Members: Dr. J. Vivekanandan, Electrical and Computer Engineering
S. Sahoo, X. Bosch-Lluis, S. C. Reising and J. Vivekanandan, "On the Vertical Resolution and Accuracy of Water-Vapor Profile Retrieval from Ground-Based K-Band Microwave Radiometer Measurements," IEEE Trans. Geosci. Remote Sens.,(under review)
S. Sahoo, X. Bosch-Lluis, S. C. Reising and J. Vivekanandan, "Tropospheric Humidity Retrieval Using a Ground-Based Network of Scanning Compact Microwave Radiometers" Proceedings of the 9th International Symposium on Tropospheric Profiling, L'Aquila, Italy, 2012
Program of Study: