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Data quality assessment and rainfall estimation using dense radar networks
While their coverage is adequate for many applications, due to the Earth's curvature and terrain induced blockage, today's operational long-range weather surveillance radar networks lack the capability to provide low altitude observations below 2 km. The use of short-range distributed radar networks can overcome that limitation by providing the expected coverage close to the ground where most of the events that affect citizens' lives occur. To pursue this vision, the Engineering Research Center (ERC) for Collaborative and Adaptive Sensing of the Atmosphere (CASA) has deployed two X-band radar network technology test beds in Oklahoma (IP1) and western Puerto Rico (IP3). The Oklahoma test bed investigates the ability of a distributive, adaptive and collaborative sensing (DCAS) network to observe, understand, predict and respond to the weather hazards (e.g. tornadoes, convective cells and super cell detection), while the Puerto Rico test bed investigates the deployment of a low cost (< $30K) and minimal infrastructure short range radar network which operates independently of wired power and communication infrastructure and is referred to as Off-the-Grid (OTG) for qualitative rainfall estimation and mapping. As a result of errors from different sources, radar measurement and its resulting products (e.g. QPE) have an uncertainty associated with them. Before performing any QPE within the CASA radar networks, the sources of errors that affect the radar measurements need to be identified and evaluated in order to obtain the most accurate rainfall estimation from radar measurements. This document investigates rainfall estimation using dense networks of short-range X-band radars. We consider QPE and the dual-polarized radar situation, such as the IP1 network, and also consider "qualitative Precipitation Estimation (qPE)", using the simpler, single-parameter (single-polarized) radars such as the CASA OTG network. Error sources that affect the radar measurements (e.g. signal attenuation in rain, wet radome attenuation, clutter filtering effects, and antenna pointing errors), methods to calibrate or correct for bias in the radars' power measurements and their respective verification, and radar-based rainfall estimation and network configuration improvements are investigated using both CASA test beds. Moreover, several important questions need to be addressed related to the design of OTG radar networks, including how to approach the problem of rainfall attenuation at the X-band operating frequency of the system and ground clutter correction without the polarimetric and Doppler velocity measurements capability.
Trabal-Del Valle, Jorge M, "Data quality assessment and rainfall estimation using dense radar networks" (2013). Doctoral Dissertations Available from Proquest. AAI3589198.