Improving Seasonal to Annual Predictions of Climate Variability and Water Availability at the Catchment Scale
| dc.contributor.author | Switanek, Matthew | |
| dc.creator | Switanek, Matthew | en_US |
| dc.date.accessioned | 2011-12-05T14:13:24Z | |
| dc.date.available | 2011-12-05T14:13:24Z | |
| dc.date.issued | 2008 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/193313 | |
| dc.description.abstract | In a water-stressed region, such as the southwestern United States, it is essential to improve current seasonal hydroclimatic predictions. Typically, seasonal hydroclimatic predictions have been conditioned by standard climate indices, e.g., NINO3 and PDO. In this work, a methodology called basin-specific climate prediction (BSCP) is proposed to improve hydroclimatic predictions. The method analyzes the statistically unique relationships between sea surface temperatures (SSTs) and a basin's hydroclimate. The oceanic region which maximizes the correlation is subsequently used as a predictor for hydroclimate. BSCP is used to perform hindcasts for the hydroclimate in the Little Colorado River basin and the results are compared to those using standard climate indices as predictors. | |
| dc.language.iso | EN | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Hydrology | en_US |
| dc.title | Improving Seasonal to Annual Predictions of Climate Variability and Water Availability at the Catchment Scale | en_US |
| dc.type | text | en_US |
| dc.type | Electronic Thesis | en_US |
| dc.contributor.chair | Troch, Peter A. | en_US |
| dc.identifier.oclc | 659749910 | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| dc.identifier.proquest | 2840 | en_US |
| thesis.degree.discipline | Hydrology | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | MS | en_US |
| refterms.dateFOA | 2018-06-19T09:05:12Z | |
| html.description.abstract | In a water-stressed region, such as the southwestern United States, it is essential to improve current seasonal hydroclimatic predictions. Typically, seasonal hydroclimatic predictions have been conditioned by standard climate indices, e.g., NINO3 and PDO. In this work, a methodology called basin-specific climate prediction (BSCP) is proposed to improve hydroclimatic predictions. The method analyzes the statistically unique relationships between sea surface temperatures (SSTs) and a basin's hydroclimate. The oceanic region which maximizes the correlation is subsequently used as a predictor for hydroclimate. BSCP is used to perform hindcasts for the hydroclimate in the Little Colorado River basin and the results are compared to those using standard climate indices as predictors. |
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