Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies
Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies
A multi-sensor/multi-platform approach to water and energy cycle prediction is demonstrated in an effort to understand the variability and feedback of land surface and atmospheric processes over large space and time scales. Remote sensing-based variables including soil moisture (from AMSR-E), surface heat fluxes (from MODIS) and precipitation rates (from TRMM) are combined with North American Regional Reanalysis derived atmospheric components to examine the degree of hydrological consistency throughout these diverse and independent hydrologic data sets. The study focuses on the influence of the North American Monsoon System (NAMS) over the southwestern United States, and is timed to coincide with the SMEX04 North American Monsoon Experiment (NAME). The study is focused over the Arizona portion of the NAME domain to assist in better characterizing the hydrometeorological processes occurring across Arizona during the summer monsoon period. Results demonstrate that this multi-sensor approach, in combination with available atmospheric observations, can be used to obtain a comprehensive and hydrometeorologically consistent characterization of the land surface water cycle, leading to an improved understanding of water and energy cycles within the NAME region and providing a novel framework for future remote observation and analysis of the coupled land surface-atmosphere system.
AMSR-E, Atmospheric processes, Climate dynamics, Data assimilation, Evapotranspiration, Feedback, Hydrological consistency, Hydrological cycle, Hydrology, Hydrometeorology, Land surface temperature, MODIS, Multi-sensor, NAME, NAMS, North American Monsoon System, Remote sensing, Satellite, SMEX, Soil moisture, TRMM
430-444
McCabe, M. F.
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Wood, E. F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Wójcik, R.
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Pan, M.
be4f9b26-fdfb-4d95-9527-269d9e95faea
Sheffield, J.
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Gao, H.
0ab679b9-f396-48c1-b668-3f96e0f6a1c0
Su, H.
3a18a541-730a-45ed-9e3a-a81351353773
15 February 2008
McCabe, M. F.
728c3adf-8316-4a9f-9409-a5b0a2125482
Wood, E. F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Wójcik, R.
9bc2e2f7-b365-4672-82da-fed11399e6ce
Pan, M.
be4f9b26-fdfb-4d95-9527-269d9e95faea
Sheffield, J.
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Gao, H.
0ab679b9-f396-48c1-b668-3f96e0f6a1c0
Su, H.
3a18a541-730a-45ed-9e3a-a81351353773
McCabe, M. F., Wood, E. F., Wójcik, R., Pan, M., Sheffield, J., Gao, H. and Su, H.
(2008)
Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies.
Remote Sensing of Environment, 112 (2), .
(doi:10.1016/j.rse.2007.03.027).
Abstract
A multi-sensor/multi-platform approach to water and energy cycle prediction is demonstrated in an effort to understand the variability and feedback of land surface and atmospheric processes over large space and time scales. Remote sensing-based variables including soil moisture (from AMSR-E), surface heat fluxes (from MODIS) and precipitation rates (from TRMM) are combined with North American Regional Reanalysis derived atmospheric components to examine the degree of hydrological consistency throughout these diverse and independent hydrologic data sets. The study focuses on the influence of the North American Monsoon System (NAMS) over the southwestern United States, and is timed to coincide with the SMEX04 North American Monsoon Experiment (NAME). The study is focused over the Arizona portion of the NAME domain to assist in better characterizing the hydrometeorological processes occurring across Arizona during the summer monsoon period. Results demonstrate that this multi-sensor approach, in combination with available atmospheric observations, can be used to obtain a comprehensive and hydrometeorologically consistent characterization of the land surface water cycle, leading to an improved understanding of water and energy cycles within the NAME region and providing a novel framework for future remote observation and analysis of the coupled land surface-atmosphere system.
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More information
Accepted/In Press date: 21 March 2007
e-pub ahead of print date: 28 August 2007
Published date: 15 February 2008
Additional Information:
Funding Information:
Research was funded by NASA project grants 1) NNG04GQ32G: A Terrestrial Evaporation Product Using MODIS Data; 2) NAG5-11111 Land Surface Modeling Studies in Support of AQUA AMSR-E Validation; and 3) NAG5-11610: Evaluation of Hydrologic Remote Sensing Observations for Improved Weather Prediction. The NARR derived atmospheric variables HI low and CTP, were kindly produced by Francina Dominguez of the Department of Civil and Environmental Engineering, University of Illinois-Urbana: her effort is greatly appreciated.
Keywords:
AMSR-E, Atmospheric processes, Climate dynamics, Data assimilation, Evapotranspiration, Feedback, Hydrological consistency, Hydrological cycle, Hydrology, Hydrometeorology, Land surface temperature, MODIS, Multi-sensor, NAME, NAMS, North American Monsoon System, Remote sensing, Satellite, SMEX, Soil moisture, TRMM
Identifiers
Local EPrints ID: 480926
URI: http://eprints.soton.ac.uk/id/eprint/480926
ISSN: 0034-4257
PURE UUID: 54b82eb7-45b7-4af9-ad5e-6b4f72a28a31
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Date deposited: 10 Aug 2023 16:59
Last modified: 18 Mar 2024 03:33
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Contributors
Author:
M. F. McCabe
Author:
E. F. Wood
Author:
R. Wójcik
Author:
M. Pan
Author:
H. Gao
Author:
H. Su
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