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Advanced solutions for rainfall estimation over complex terrain in the San Francisco Bay area

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dc.contributor.authorBiswas, Sounak Kumar, author
dc.contributor.authorChandrasekar, V., advisor
dc.contributor.authorCheney, Margaret, committee member
dc.contributor.authorGooch, Steven, committee member
dc.contributor.authorJames, Susan, committee member
dc.date.accessioned2024-01-01T11:25:25Z
dc.date.available2025-12-29
dc.date.issued2023
dc.description.abstractFresh water is an increasingly scarce resource in the western United States and effective management and prediction of flooding and drought have a direct economic impact on almost all aspects of society. Therefore it is critical to monitor and predict water inputs into the hydrological cycle of the Western United States (US). The complex topography of the western US poses a significant challenge in developing physically realistic and spatially accurate estimates of precipitation using remote sensing techniques. The intricate landscape presents a challenging observing environment for weather radar systems. This is further compounded by the complex microphysical processes during the cool season which are influenced by coastal air-sea interactions, as well as orographic effects along the coastal regions of the West. The placement and density of operational National Weather Service (NWS) radars (popularly known as NEXRAD or WSR-88D) pose a challenge in meeting the needs for water resource management in the western US due to the complex terrain of the region. Consequently, areas like the San Francisco Bay Area could use enhanced precipitation monitoring, in terms of amount and type, along watersheds and surrounding rivers and streams. Shorter wavelength radars such as X-Band radar systems are able to augment the WSR-88D network, to observe better the lower atmosphere with higher temporal and spatial resolution. This research investigates and documents the challenges of precipitation monitoring by radars over complex terrain and aims to provide effective and advanced solutions for accurate Quantitative Precipitation Estimation (QPE) using both WSR-88D and the gap-filling X-Band radar systems over the Bay Area on the US West Coast, with a focus on the cool season. Specifically, this study focuses on a precipitation microphysics perspective, aiming to create an algorithm capable of distinguishing orographically enhanced rainfall from cool-season stratiform rainfall using X-Band radar observations. A radar-based rainfall estimator is developed to increase the accuracy of rainfall quantification. Additionally, various other scientific and engineering challenges have been addressed including radar calibration, attenuation correction of the radar beam, radar beam blockage due to terrain, and correction of measurements of the vertical profiles of radar observables. The final QPE product is constructed by merging the X-Band based QPE product with the operational NEXRAD based QPE product, significantly enhancing the overall quality of rainfall mapping within the Bay Area. Case studies reveal that the new product is able to improve QPE accuracy by ~70% in terms of mean absolute error and root mean squared error compared to the operational products. This establishes the overall need for precipitation monitoring by gap-filling X-Band radar systems in the complex terrain of the San Francisco Bay Area.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierBiswas_colostate_0053A_18152.pdf
dc.identifier.urihttps://hdl.handle.net/10217/237472
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.accessEmbargo expires: 12/29/2025.
dc.titleAdvanced solutions for rainfall estimation over complex terrain in the San Francisco Bay area
dc.typeText
dcterms.embargo.expires2025-12-29
dcterms.embargo.terms2025-12-29
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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