Surface Properties of Global Land Surface Microwave Emissivity Derived from FY-3D/MWRI Measurements.

brightness temperature land cover types land surface microwave emissivity microwave radiation imager remote sensing

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
13 Jun 2023
Historique:
received: 04 04 2023
revised: 07 06 2023
accepted: 09 06 2023
medline: 10 7 2023
pubmed: 8 7 2023
entrez: 8 7 2023
Statut: epublish

Résumé

Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes.

Identifiants

pubmed: 37420701
pii: s23125534
doi: 10.3390/s23125534
pmc: PMC10305531
pii:
doi:

Substances chimiques

Soil 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Key Research and Development Program of China
ID : 2018YFC1506500, 2021YFC3000300, and 2018YFB0504905
Organisme : FengYun Application Pioneering Project
ID : FY-APP-2021.0505
Organisme : Youth Innovation Team of China Meteorological Administration
ID : CMA2023QN08

Références

Nature. 2017 Oct 27;551(7678):13-14
pubmed: 29094714

Auteurs

Ronghan Xu (R)

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China.
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China.

Zharong Pan (Z)

General Institute of Water Resources and Hydropower Planning and Design, Ministry of Water Resources, Beijing 100120, China.

Yang Han (Y)

Earth System Modeling and Prediction Center, China Meteorological Administration, Beijing 100081, China.

Wei Zheng (W)

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China.
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China.

Shengli Wu (S)

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China.
Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China.

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Classifications MeSH