Assessment of the SMAP Soil Emission Model and Soil Moisture Retrieval Algorithms for a Tibetan Desert Ecosystem

Donghai Zheng, R. van der Velde, Jun Wen, Xin Wang, Paolo Ferrazzoli, Mike Schwank, Andreas Colliander, Rajat Bindlish, Zhongbo Su

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

The Soil Moisture Active Passive (SMAP) satellite mission launched in January 2015 provides worldwide soil moisture (SM) monitoring based on L-band brightness temperature (TBp) measurements at horizontal (TBH) and vertical (TBV) polarizations. This paper presents a performance assessment of SMAP soil emission model and SM retrieval algorithms for a Tibetan desert ecosystem. It is found that the SMAP emission model largely underestimates the SMAP measured TBH (≈ 15 K), and the TBV is underestimated during dry-down episodes. A cold bias is noted for the SMAP effective temperature due to underestimation of soil temperature, leading to the TBp underestimation (>5 K). The remaining TBH underestimation is found to be related to the surface roughness parameterization that underestimates its effect on modulating the TBp measurements. Further, the topography and uncertainty of soil information are found to have minor impacts on the TBp simulations. The SMAP baseline SM products produced by single-channel algorithm (SCA) using the TBV measurements capture the measured SM dynamics well, while an underestimation is noted for the dry-down periods because of TBV underestimation. The products based on the SCA with TBH measurements underestimate the SM due to underestimation of TBH, and the dual-channel algorithm overestimates the SM. After implementing a new surface roughness parameterization and improving the soil temperature and texture information, the deficiencies noted above in TBp simulation and SM retrieval are greatly resolved. This indicates that the SMAP SM retrievals can be enhanced by improving both surface roughness and adopted soil temperature and texture information for Tibetan desert ecosystem.

Original languageEnglish
Pages (from-to)3786-3799
Number of pages14
JournalIEEE transactions on geoscience and remote sensing
Volume56
Issue number7
DOIs
Publication statusPublished - Jul 2018

Fingerprint

soil emission
Soil moisture
Ecosystems
desert
soil moisture
Soils
ecosystem
surface roughness
soil temperature
Surface roughness
Parameterization
soil texture
parameterization
Textures
Temperature
satellite mission
performance assessment
brightness temperature
Temperature measurement
Topography

Keywords

  • Effective temperature
  • L-band
  • Rough surfaces
  • Soil
  • soil emission
  • Soil measurements
  • soil moisture (SM)
  • Soil Moisture Active Passive (SMAP)
  • Surface roughness
  • surface roughness
  • Surface topography
  • Temperature measurement
  • Tibetan Plateau
  • topography.
  • ITC-ISI-JOURNAL-ARTICLE

Cite this

Zheng, Donghai ; van der Velde, R. ; Wen, Jun ; Wang, Xin ; Ferrazzoli, Paolo ; Schwank, Mike ; Colliander, Andreas ; Bindlish, Rajat ; Su, Zhongbo. / Assessment of the SMAP Soil Emission Model and Soil Moisture Retrieval Algorithms for a Tibetan Desert Ecosystem. In: IEEE transactions on geoscience and remote sensing. 2018 ; Vol. 56, No. 7. pp. 3786-3799.
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title = "Assessment of the SMAP Soil Emission Model and Soil Moisture Retrieval Algorithms for a Tibetan Desert Ecosystem",
abstract = "The Soil Moisture Active Passive (SMAP) satellite mission launched in January 2015 provides worldwide soil moisture (SM) monitoring based on L-band brightness temperature (TBp) measurements at horizontal (TBH) and vertical (TBV) polarizations. This paper presents a performance assessment of SMAP soil emission model and SM retrieval algorithms for a Tibetan desert ecosystem. It is found that the SMAP emission model largely underestimates the SMAP measured TBH (≈ 15 K), and the TBV is underestimated during dry-down episodes. A cold bias is noted for the SMAP effective temperature due to underestimation of soil temperature, leading to the TBp underestimation (>5 K). The remaining TBH underestimation is found to be related to the surface roughness parameterization that underestimates its effect on modulating the TBp measurements. Further, the topography and uncertainty of soil information are found to have minor impacts on the TBp simulations. The SMAP baseline SM products produced by single-channel algorithm (SCA) using the TBV measurements capture the measured SM dynamics well, while an underestimation is noted for the dry-down periods because of TBV underestimation. The products based on the SCA with TBH measurements underestimate the SM due to underestimation of TBH, and the dual-channel algorithm overestimates the SM. After implementing a new surface roughness parameterization and improving the soil temperature and texture information, the deficiencies noted above in TBp simulation and SM retrieval are greatly resolved. This indicates that the SMAP SM retrievals can be enhanced by improving both surface roughness and adopted soil temperature and texture information for Tibetan desert ecosystem.",
keywords = "Effective temperature, L-band, Rough surfaces, Soil, soil emission, Soil measurements, soil moisture (SM), Soil Moisture Active Passive (SMAP), Surface roughness, surface roughness, Surface topography, Temperature measurement, Tibetan Plateau, topography., ITC-ISI-JOURNAL-ARTICLE",
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Assessment of the SMAP Soil Emission Model and Soil Moisture Retrieval Algorithms for a Tibetan Desert Ecosystem. / Zheng, Donghai; van der Velde, R.; Wen, Jun; Wang, Xin; Ferrazzoli, Paolo; Schwank, Mike; Colliander, Andreas; Bindlish, Rajat; Su, Zhongbo.

In: IEEE transactions on geoscience and remote sensing, Vol. 56, No. 7, 07.2018, p. 3786-3799.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Assessment of the SMAP Soil Emission Model and Soil Moisture Retrieval Algorithms for a Tibetan Desert Ecosystem

AU - Zheng, Donghai

AU - van der Velde, R.

AU - Wen, Jun

AU - Wang, Xin

AU - Ferrazzoli, Paolo

AU - Schwank, Mike

AU - Colliander, Andreas

AU - Bindlish, Rajat

AU - Su, Zhongbo

PY - 2018/7

Y1 - 2018/7

N2 - The Soil Moisture Active Passive (SMAP) satellite mission launched in January 2015 provides worldwide soil moisture (SM) monitoring based on L-band brightness temperature (TBp) measurements at horizontal (TBH) and vertical (TBV) polarizations. This paper presents a performance assessment of SMAP soil emission model and SM retrieval algorithms for a Tibetan desert ecosystem. It is found that the SMAP emission model largely underestimates the SMAP measured TBH (≈ 15 K), and the TBV is underestimated during dry-down episodes. A cold bias is noted for the SMAP effective temperature due to underestimation of soil temperature, leading to the TBp underestimation (>5 K). The remaining TBH underestimation is found to be related to the surface roughness parameterization that underestimates its effect on modulating the TBp measurements. Further, the topography and uncertainty of soil information are found to have minor impacts on the TBp simulations. The SMAP baseline SM products produced by single-channel algorithm (SCA) using the TBV measurements capture the measured SM dynamics well, while an underestimation is noted for the dry-down periods because of TBV underestimation. The products based on the SCA with TBH measurements underestimate the SM due to underestimation of TBH, and the dual-channel algorithm overestimates the SM. After implementing a new surface roughness parameterization and improving the soil temperature and texture information, the deficiencies noted above in TBp simulation and SM retrieval are greatly resolved. This indicates that the SMAP SM retrievals can be enhanced by improving both surface roughness and adopted soil temperature and texture information for Tibetan desert ecosystem.

AB - The Soil Moisture Active Passive (SMAP) satellite mission launched in January 2015 provides worldwide soil moisture (SM) monitoring based on L-band brightness temperature (TBp) measurements at horizontal (TBH) and vertical (TBV) polarizations. This paper presents a performance assessment of SMAP soil emission model and SM retrieval algorithms for a Tibetan desert ecosystem. It is found that the SMAP emission model largely underestimates the SMAP measured TBH (≈ 15 K), and the TBV is underestimated during dry-down episodes. A cold bias is noted for the SMAP effective temperature due to underestimation of soil temperature, leading to the TBp underestimation (>5 K). The remaining TBH underestimation is found to be related to the surface roughness parameterization that underestimates its effect on modulating the TBp measurements. Further, the topography and uncertainty of soil information are found to have minor impacts on the TBp simulations. The SMAP baseline SM products produced by single-channel algorithm (SCA) using the TBV measurements capture the measured SM dynamics well, while an underestimation is noted for the dry-down periods because of TBV underestimation. The products based on the SCA with TBH measurements underestimate the SM due to underestimation of TBH, and the dual-channel algorithm overestimates the SM. After implementing a new surface roughness parameterization and improving the soil temperature and texture information, the deficiencies noted above in TBp simulation and SM retrieval are greatly resolved. This indicates that the SMAP SM retrievals can be enhanced by improving both surface roughness and adopted soil temperature and texture information for Tibetan desert ecosystem.

KW - Effective temperature

KW - L-band

KW - Rough surfaces

KW - Soil

KW - soil emission

KW - Soil measurements

KW - soil moisture (SM)

KW - Soil Moisture Active Passive (SMAP)

KW - Surface roughness

KW - surface roughness

KW - Surface topography

KW - Temperature measurement

KW - Tibetan Plateau

KW - topography.

KW - ITC-ISI-JOURNAL-ARTICLE

UR - https://ezproxy2.utwente.nl/login?url=https://doi.org/0.1109/TGRS.2018.2811318

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2018/isi/vandervelde_ass.pdf

U2 - 10.1109/TGRS.2018.2811318

DO - 10.1109/TGRS.2018.2811318

M3 - Article

AN - SCOPUS:85044378015

VL - 56

SP - 3786

EP - 3799

JO - IEEE transactions on geoscience and remote sensing

JF - IEEE transactions on geoscience and remote sensing

SN - 0196-2892

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ER -