Interannual variation of the surface temperature of tropical forests from satellite observations

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2015-05-17

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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. 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).

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10.1155/2016/4741390

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Gao, H, S Zhang, R Fu, W Li and RE Dickinson (2015). Interannual variation of the surface temperature of tropical forests from satellite observations. Advances in Meteorology, 2016. 10.1155/2016/4741390 Retrieved from https://hdl.handle.net/10161/10239.

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Scholars@Duke

Li

Wenhong Li

Associate Professor of Climate

Dr. Li's research interests focus primarily on climate dynamics, land-atmosphere interaction, hydroclimatology, and climate modeling. Her current research is to understand how the hydrological cycle changes in the current and future climate and their impacts on the ecosystems, subtropical high variability and change, unforced global temperature variability, and climate and health issues.


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