Interannual variation of the surface temperature of tropical forests from satellite observations
Abstract
Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability of cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).
- Authors:
-
- Texas A & M Univ., College Station, TX (United States)
- Univ. of Texas at Austin, Austin, TX (United States)
- Duke Univ., Duke, NC (United States)
- Publication Date:
- Research Org.:
- Univ. of Texas, Austin, TX (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1242966
- Grant/Contract Number:
- SC0011117
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Advances in Meteorology
- Additional Journal Information:
- Journal Volume: 2016; Journal ID: ISSN 1687-9309
- Publisher:
- Hindawi
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Gao, Huilin, Zhang, Shuai, Fu, Rong, Li, Wenhong, and Dickinson, Robert E. Interannual variation of the surface temperature of tropical forests from satellite observations. United States: N. p., 2016.
Web. doi:10.1155/2016/4741390.
Gao, Huilin, Zhang, Shuai, Fu, Rong, Li, Wenhong, & Dickinson, Robert E. Interannual variation of the surface temperature of tropical forests from satellite observations. United States. https://doi.org/10.1155/2016/4741390
Gao, Huilin, Zhang, Shuai, Fu, Rong, Li, Wenhong, and Dickinson, Robert E. Fri .
"Interannual variation of the surface temperature of tropical forests from satellite observations". United States. https://doi.org/10.1155/2016/4741390. https://www.osti.gov/servlets/purl/1242966.
@article{osti_1242966,
title = {Interannual variation of the surface temperature of tropical forests from satellite observations},
author = {Gao, Huilin and Zhang, Shuai and Fu, Rong and Li, Wenhong and Dickinson, Robert E.},
abstractNote = {Land surface temperatures (LSTs) within tropical forests contribute to climate variations. However, observational data are very limited in such regions. This study used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS), providing observations under all weather conditions, to investigate the LST over the Amazon and Congo rainforests. The SSM/I and SSMIS data were collected from 1996 to 2012. The morning and afternoon observations from passive microwave remote sensing facilitate the investigation of the interannual changes of LST anomalies on a diurnal basis. As a result of the variability of cloud cover and the corresponding reduction of solar radiation, the afternoon LST anomalies tend to vary more than the morning LST anomalies. The dominant spatial and temporal patterns for interseasonal variations of the LST anomalies over the tropical rainforest were analyzed. The impacts of droughts and El Niños on this LST were also investigated. Lastly, the differences between early morning and late afternoon LST anomalies were identified by the remote sensing product, with the morning LST anomalies controlled by humidity (according to comparisons with the National Centers for Environmental Prediction (NCEP) reanalysis data).},
doi = {10.1155/2016/4741390},
journal = {Advances in Meteorology},
number = ,
volume = 2016,
place = {United States},
year = {Fri Jan 01 00:00:00 EST 2016},
month = {Fri Jan 01 00:00:00 EST 2016}
}
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Works referencing / citing this record:
Assessment of the impacts of climate variability on total water storage across Africa: implications for groundwater resources management
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