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North American land data assimilation system: A framework for merging model and satellite data for improved drought monitoring

North American land data assimilation system: A framework for merging model and satellite data for improved drought monitoring
North American land data assimilation system: A framework for merging model and satellite data for improved drought monitoring

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological-ecological-human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources.

227-259
CRC Press
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Xia, Youlong
dd51d092-f162-4643-adf3-f1b48f1a53af
Luo, Lifeng
e9b25aa8-e877-45a6-bdca-53aba9bbde84
Wood, Eric F.
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Ek, Michael
ce2724ad-0b64-4802-85c5-ad556f31b1e8
Mitchell, Kenneth E.
91d961dc-4337-4c48-aace-74ebe14f1e2b
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Xia, Youlong
dd51d092-f162-4643-adf3-f1b48f1a53af
Luo, Lifeng
e9b25aa8-e877-45a6-bdca-53aba9bbde84
Wood, Eric F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Ek, Michael
ce2724ad-0b64-4802-85c5-ad556f31b1e8
Mitchell, Kenneth E.
91d961dc-4337-4c48-aace-74ebe14f1e2b

Sheffield, Justin, Xia, Youlong, Luo, Lifeng, Wood, Eric F., Ek, Michael and Mitchell, Kenneth E. (2012) North American land data assimilation system: A framework for merging model and satellite data for improved drought monitoring. In, Remote Sensing of Drought: Innovative Monitoring Approaches. CRC Press, pp. 227-259. (doi:10.1201/b11863).

Record type: Book Section

Abstract

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological-ecological-human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources.

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More information

Published date: 1 January 2012
Additional Information: Publisher Copyright: © 2012 by Taylor & Francis Group, LLC.

Identifiers

Local EPrints ID: 480472
URI: http://eprints.soton.ac.uk/id/eprint/480472
PURE UUID: 62f12440-27e5-430e-b814-a2183fffe78f
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

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Date deposited: 02 Aug 2023 17:13
Last modified: 06 Jun 2024 01:54

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Contributors

Author: Youlong Xia
Author: Lifeng Luo
Author: Eric F. Wood
Author: Michael Ek
Author: Kenneth E. Mitchell

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