THE APPLICATION OF A STATISTICAL DOWNSCALING PROCESS TO DERIVE 21{sup ST} CENTURY RIVER FLOW PREDICTIONS USING A GLOBAL CLIMATE SIMULATION

PDF Version Also Available for Download.

Description

The ability of water managers to maintain adequate supplies in coming decades depends, in part, on future weather conditions, as climate change has the potential to alter river flows from their current values, possibly rendering them unable to meet demand. Reliable climate projections are therefore critical to predicting the future water supply for the United States. These projections cannot be provided solely by global climate models (GCMs), however, as their resolution is too coarse to resolve the small-scale climate changes that can affect hydrology, and hence water supply, at regional to local scales. A process is needed to ‘downscale’ the ... continued below

Creation Information

Werth, D. & Chen, K. F. August 22, 2013.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

The ability of water managers to maintain adequate supplies in coming decades depends, in part, on future weather conditions, as climate change has the potential to alter river flows from their current values, possibly rendering them unable to meet demand. Reliable climate projections are therefore critical to predicting the future water supply for the United States. These projections cannot be provided solely by global climate models (GCMs), however, as their resolution is too coarse to resolve the small-scale climate changes that can affect hydrology, and hence water supply, at regional to local scales. A process is needed to ‘downscale’ the GCM results to the smaller scales and feed this into a surface hydrology model to help determine the ability of rivers to provide adequate flow to meet future needs. We apply a statistical downscaling to GCM projections of precipitation and temperature through the use of a scaling method. This technique involves the correction of the cumulative distribution functions (CDFs) of the GCM-derived temperature and precipitation results for the 20{sup th} century, and the application of the same correction to 21{sup st} century GCM projections. This is done for three meteorological stations located within the Coosa River basin in northern Georgia, and is used to calculate future river flow statistics for the upper Coosa River. Results are compared to the historical Coosa River flow upstream from Georgia Power Company’s Hammond coal-fired power plant and to flows calculated with the original, unscaled GCM results to determine the impact of potential changes in meteorology on future flows.

Notes

available

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: SRNL-STI-2013-00265
  • Grant Number: DE-AC09-08SR22470
  • DOI: 10.2172/1091096 | External Link
  • Office of Scientific & Technical Information Report Number: 1091096
  • Archival Resource Key: ark:/67531/metadc839581

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • August 22, 2013

Added to The UNT Digital Library

  • May 19, 2016, 9:45 a.m.

Description Last Updated

  • Dec. 12, 2016, 2:53 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 4

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Werth, D. & Chen, K. F. THE APPLICATION OF A STATISTICAL DOWNSCALING PROCESS TO DERIVE 21{sup ST} CENTURY RIVER FLOW PREDICTIONS USING A GLOBAL CLIMATE SIMULATION, report, August 22, 2013; United States. (digital.library.unt.edu/ark:/67531/metadc839581/: accessed November 16, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.