Three-dimensional water vapor retrieval using a network of scanning compact microwave radiometers
dc.contributor.author | Padmanabhan, Sharmila, author | |
dc.contributor.author | Reising, S. C., advisor | |
dc.date.accessioned | 2024-03-13T20:12:28Z | |
dc.date.available | 2024-03-13T20:12:28Z | |
dc.date.issued | 2009 | |
dc.description.abstract | Quantitative precipitation forecasting is currently limited by the paucity of observations on sufficiently fine temporal and spatial scales. In particular, convective storms have been observed to develop in regions of strong and rapidly evolving moisture gradients that vary spatially on sub-meso γ scales (2-5 km). Therefore, measurements of water vapor aloft with high time resolution and sufficient spatial resolution have the potential to improve forecast skill for the initiation of convective storms. Such measurements may be used for assimilation into and validation of numerical weather prediction (NWP) models. Currently, water vapor density profiles are obtained using in-situ sensors on radiosondes and remotely using lidars, GPS ground-based networks, CPS radio occultation from satellites and a relatively small number of space-borne microwave and infrared radiometers. In-situ radiosonde measurements have excellent vertical resolution but are severely limited in temporal and spatial coverage. In addition, each radiosonde takes 45-60 minutes to rise from ground level to the tropopause, and is typically advected by upper-level winds up to tens of km horizontal displacement from its launch site. Tomographic inversion applied to ground-based measurements of GPS wet delay is expected to yield data with 0.5-1 km vertical resolution at 30-minute intervals. COSMIC and CHAMP satellites in low earth orbit (LEO) provide measurements with 0.1-0.5 km vertical resolution at 30-minute intervals but only 200-600 km horizontal resolution, depending on the magnitude of the path-integrated refractivity. Microwave radiometers in low-earth orbit provide reasonable vertical resolution (2 km) and mesoscale horizontal resolution (20 km) with long repeat times. Both the prediction of convective initiation and quantitative precipitation require knowledge of water vapor variations on sub-meso γ scales (2-5 km) with update times on the order of a few tens of minutes. Due to the relatively high cost of both commercially-available microwave radiometers for network deployment and rapid radiosonde launches with close horizontal spacing, such measurements have not been available. Measurements using a network of multi-frequency microwave radiometers can provide information to retrieve the 3-D distribution of water vapor in the troposphere. An Observation System Simulation Experiment (OSSE) was performed in which synthetic examples of retrievals using a network of radiometers were compared with results from the Weather Research Forecasting (WRF) model at a grid scale of 500 m. These comparisons show that the 3-D water vapor field can be retrieved with an accuracy varying from 15-40% depending on the number of sensors in the network and the location and time of the a priori. To deploy a network of low cost radiometers, the Compact Microwave Radiometer for Humidity profiling (CMR-H) was developed by the Microwave Systems Laboratory at Colorado State University. Using monolithic microwave integrated circuit technology and unique packaging yields a radiometer that is small (24 x 18 x 16 cm), light weight (6 kg), relatively inexpensive and low-power consumption (25-50 W, depending on weather conditions). Recently, field measurements at the DOE Atmospheric Radiation Measurement (ARM) Southern Great Plains site in Oklahoma have demonstrated the potential for coordinated, scanning microwave radiometers to provide 0.5-1 km resolution both vertically and horizontally with sampling times of 15 minutes or less. This work describes and demonstrates the use of algebraic reconstruction tomography to retrieve the 3-D water vapor field from simultaneous brightness temperatures using radiative transfer theory, optimal estimation and Kalman filtering. | |
dc.format.medium | born digital | |
dc.format.medium | doctoral dissertations | |
dc.identifier | ETDF_Padmanabhan_2009_3374610.pdf | |
dc.identifier.uri | https://hdl.handle.net/10217/237898 | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Colorado State University. Libraries | |
dc.relation.ispartof | 2000-2019 | |
dc.rights | Copyright 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.license | Per the terms of a contractual agreement, all use of this item is limited to the non-commercial use of Colorado State University and its authorized users. | |
dc.subject | atmospheric measurement | |
dc.subject | electromagnetic tomography | |
dc.subject | humidity measurement | |
dc.subject | microwave radiometry | |
dc.subject | precipitation forecasting | |
dc.subject | remote sensing | |
dc.subject | electrical engineering | |
dc.subject | remote sensing | |
dc.title | Three-dimensional water vapor retrieval using a network of scanning compact microwave radiometers | |
dc.type | Text | |
dcterms.rights.dpla | This 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.discipline | Electrical and Computer Engineering | |
thesis.degree.grantor | Colorado State University | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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