Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies

M. F. McCabe; E. F. Wood; R. Wójcik; M. Pan; J. Sheffield; H. Gao; H. Su

doi:10.1016/j.rse.2007.03.027

Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies

M. F. McCabe^*, E. F. Wood, R. Wójcik, M. Pan, J. Sheffield, H. Gao, H. Su

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

106 Scopus citations

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.

Original language	English (US)
Pages (from-to)	430-444
Number of pages	15
Journal	Remote Sensing of Environment
Volume	112
Issue number	2
DOIs	https://doi.org/10.1016/j.rse.2007.03.027
State	Published - Feb 15 2008
Externally published	Yes

Bibliographical note

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
SMEX
Satellite
Soil moisture
TRMM

ASJC Scopus subject areas

Soil Science
Geology
Computers in Earth Sciences

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.rse.2007.03.027

Cite this

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title = "Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies",

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.",

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, SMEX, Satellite, Soil moisture, TRMM",

author = "McCabe, {M. F.} and Wood, {E. F.} and R. W{\'o}jcik and M. Pan and J. Sheffield and H. Gao and H. Su",

note = "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. ",

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doi = "10.1016/j.rse.2007.03.027",

language = "English (US)",

volume = "112",

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AU - McCabe, M. F.

AU - Wood, E. F.

AU - Wójcik, R.

AU - Pan, M.

AU - Sheffield, J.

AU - Gao, H.

AU - Su, H.

N1 - 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.

PY - 2008/2/15

Y1 - 2008/2/15

N2 - 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.

AB - 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.

KW - AMSR-E

KW - Atmospheric processes

KW - Climate dynamics

KW - Data assimilation

KW - Evapotranspiration

KW - Feedback

KW - Hydrological consistency

KW - Hydrological cycle

KW - Hydrology

KW - Hydrometeorology

KW - Land surface temperature

KW - MODIS

KW - Multi-sensor

KW - NAME

KW - NAMS

KW - North American Monsoon System

KW - Remote sensing

KW - SMEX

KW - Satellite

KW - Soil moisture

KW - TRMM

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DO - 10.1016/j.rse.2007.03.027

M3 - Article

AN - SCOPUS:38049161845

SN - 0034-4257

VL - 112

SP - 430

EP - 444

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

IS - 2

ER -

Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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