An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval

Wade T. Crow; Matthias Drusch; Eric F. Wood

doi:10.1109/36.942540

An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval

Wade T. Crow, Matthias Drusch, Eric F. Wood

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

69 Scopus citations

Abstract

Using a high-resolution hydrologic model, a land surface microwave emission model (LSMEM), and an explicit simulation of the orbital and scanning characteristics for the advanced microwave sensing radiometer (AMSR-E), an observing system simulation experiment (OSSE) is carded out to assess the impact of land surface heterogeneity on large-scale retrieval and validation of soil moisture products over the U.S. Southern Great Plains using the 6.925 GHz channel on the AMSR-E sensor. Land surface heterogeneity impacts soil moisture products through the presence of nonlinearities in processes represented by the LSMEM, as well as the fundamental inconsistency in spatial scale between gridded soil moisture imagery derived from in situ point-scale sampling, numerical modelling, and microwave remote sensing sources. Results within the 575000 km² Red-Arkansas River basin show that, for surfaces with vegetation water contents below 0.75 kg/m², these two scale effects induce root mean squared errors (RMSEs) of 1.7% volumetric (0.017 cm_water³/cm_soil³) into daily 60 km AMSR-E soil moisture products and RMS differences of 3.0% (0.030 cm_water³/cm_soil³) into 60 km comparisons of AMSR-E soil moisture products and in situ field-scale measurements of soil moisture sampled on a fixed 25-km grid.

Original language	English (US)
Pages (from-to)	1622-1631
Number of pages	10
Journal	IEEE Transactions on Geoscience and Remote Sensing
Volume	39
Issue number	8
DOIs	https://doi.org/10.1109/36.942540
State	Published - Sep 2001

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Earth and Planetary Sciences(all)

Keywords

Antenna gain function
Hydrological modelling
Passive microwave remote sensing
Soil moisture

Access to Document

10.1109/36.942540

Fingerprint Dive into the research topics of 'An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval'. Together they form a unique fingerprint.

Cite this

@article{a256718a28e24e96b4a442e2cfd8ca84,

title = "An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval",

abstract = "Using a high-resolution hydrologic model, a land surface microwave emission model (LSMEM), and an explicit simulation of the orbital and scanning characteristics for the advanced microwave sensing radiometer (AMSR-E), an observing system simulation experiment (OSSE) is carded out to assess the impact of land surface heterogeneity on large-scale retrieval and validation of soil moisture products over the U.S. Southern Great Plains using the 6.925 GHz channel on the AMSR-E sensor. Land surface heterogeneity impacts soil moisture products through the presence of nonlinearities in processes represented by the LSMEM, as well as the fundamental inconsistency in spatial scale between gridded soil moisture imagery derived from in situ point-scale sampling, numerical modelling, and microwave remote sensing sources. Results within the 575000 km2 Red-Arkansas River basin show that, for surfaces with vegetation water contents below 0.75 kg/m2, these two scale effects induce root mean squared errors (RMSEs) of 1.7% volumetric (0.017 cmwater3/cmsoil3) into daily 60 km AMSR-E soil moisture products and RMS differences of 3.0% (0.030 cmwater3/cmsoil3) into 60 km comparisons of AMSR-E soil moisture products and in situ field-scale measurements of soil moisture sampled on a fixed 25-km grid.",

keywords = "Antenna gain function, Hydrological modelling, Passive microwave remote sensing, Soil moisture",

author = "Crow, {Wade T.} and Matthias Drusch and Wood, {Eric F.}",

note = "Funding Information: Manuscript received October 1, 2000; revised April 20, 2001. This work was supported by NASA Grants NAG8–1517 and NAG5–6494 and NOAA Grant NA96GP0413. W. T. Crow and E.F. Wood are with the Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 USA (e-mail: wadecrow@princeton.edu). M. Drusch is with the Meteorological Institute, Bonn University, Bonn, Germany. Publisher Item Identifier S 0196-2892(01)06678-5.",

year = "2001",

month = sep,

doi = "10.1109/36.942540",

language = "English (US)",

volume = "39",

pages = "1622--1631",

journal = "IEEE Transactions on Geoscience and Remote Sensing",

issn = "0196-2892",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "8",

}

TY - JOUR

T1 - An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval

AU - Crow, Wade T.

AU - Drusch, Matthias

AU - Wood, Eric F.

N1 - Funding Information: Manuscript received October 1, 2000; revised April 20, 2001. This work was supported by NASA Grants NAG8–1517 and NAG5–6494 and NOAA Grant NA96GP0413. W. T. Crow and E.F. Wood are with the Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 USA (e-mail: wadecrow@princeton.edu). M. Drusch is with the Meteorological Institute, Bonn University, Bonn, Germany. Publisher Item Identifier S 0196-2892(01)06678-5.

PY - 2001/9

Y1 - 2001/9

N2 - Using a high-resolution hydrologic model, a land surface microwave emission model (LSMEM), and an explicit simulation of the orbital and scanning characteristics for the advanced microwave sensing radiometer (AMSR-E), an observing system simulation experiment (OSSE) is carded out to assess the impact of land surface heterogeneity on large-scale retrieval and validation of soil moisture products over the U.S. Southern Great Plains using the 6.925 GHz channel on the AMSR-E sensor. Land surface heterogeneity impacts soil moisture products through the presence of nonlinearities in processes represented by the LSMEM, as well as the fundamental inconsistency in spatial scale between gridded soil moisture imagery derived from in situ point-scale sampling, numerical modelling, and microwave remote sensing sources. Results within the 575000 km2 Red-Arkansas River basin show that, for surfaces with vegetation water contents below 0.75 kg/m2, these two scale effects induce root mean squared errors (RMSEs) of 1.7% volumetric (0.017 cmwater3/cmsoil3) into daily 60 km AMSR-E soil moisture products and RMS differences of 3.0% (0.030 cmwater3/cmsoil3) into 60 km comparisons of AMSR-E soil moisture products and in situ field-scale measurements of soil moisture sampled on a fixed 25-km grid.

AB - Using a high-resolution hydrologic model, a land surface microwave emission model (LSMEM), and an explicit simulation of the orbital and scanning characteristics for the advanced microwave sensing radiometer (AMSR-E), an observing system simulation experiment (OSSE) is carded out to assess the impact of land surface heterogeneity on large-scale retrieval and validation of soil moisture products over the U.S. Southern Great Plains using the 6.925 GHz channel on the AMSR-E sensor. Land surface heterogeneity impacts soil moisture products through the presence of nonlinearities in processes represented by the LSMEM, as well as the fundamental inconsistency in spatial scale between gridded soil moisture imagery derived from in situ point-scale sampling, numerical modelling, and microwave remote sensing sources. Results within the 575000 km2 Red-Arkansas River basin show that, for surfaces with vegetation water contents below 0.75 kg/m2, these two scale effects induce root mean squared errors (RMSEs) of 1.7% volumetric (0.017 cmwater3/cmsoil3) into daily 60 km AMSR-E soil moisture products and RMS differences of 3.0% (0.030 cmwater3/cmsoil3) into 60 km comparisons of AMSR-E soil moisture products and in situ field-scale measurements of soil moisture sampled on a fixed 25-km grid.

KW - Antenna gain function

KW - Hydrological modelling

KW - Passive microwave remote sensing

KW - Soil moisture

UR - http://www.scopus.com/inward/record.url?scp=0035444720&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035444720&partnerID=8YFLogxK

U2 - 10.1109/36.942540

DO - 10.1109/36.942540

M3 - Article

AN - SCOPUS:0035444720

VL - 39

SP - 1622

EP - 1631

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

SN - 0196-2892

IS - 8

ER -