| Publisher | The Royal Society Publishing |
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| Volume / Issue | 373/1760 |
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| Total Pages | 10 pages |
| Article Link | https://royalsocietypublishing.org/doi/full/10.1098/rstb.2017.0406?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed |
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| DOI | doi.org/10.1098/rstb.2017.0406 |
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| Tags | reanalysis; validation; El Nino; southern oscillation; tropical forests |
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| Publication Date | October 08, 2018 |
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| Abstract | To understand the impacts of extreme climate events, it is first necessary to understand the spatio-temporal characteristics of the event. Gridded climate products are frequently used to describe climate patterns but have been shown to perform poorly over data-sparse regions such as tropical forests. Often, they are uncritically employed in a wide range of studies linking tropical forest processes to large-scale climate variability. Here, we conduct an inter-comparison and assessment of near-surface air temperature fields supplied by four state-of-the-art reanalysis products, along with precipitation estimates supplied by four merged satellite-gauge rainfall products. Firstly, spatio-temporal patterns of temperature and precipitation anomalies during the 2015–2016 El Niño are shown for each product to characterize the impact of the El Niño on the tropical forest biomes of Equatorial Africa, Southeast Asia and South America. Using meteorological station data, a two-stage assessment is then conducted to determine which products most reliably model tropical climates during the 2015–2016 El Niño, and which perform best over the longer-term satellite observation period (1980–2016). Results suggest that eastern Amazonia, parts of the Congo Basin and mainland Southeast Asia all experienced significant monthly mean temperature anomalies during the El Niño, while northeastern Amazonia, eastern Borneo and southern New Guinea experienced significant precipitation deficits. Our results suggest ERA-Interim and MERRA2 are the most reliable air temperature datasets, while TRMM 3B42 V7 and CHIRPS v2.0 are the best-performing rainfall datasets.
This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’. |
Created: 4/24/2019 3:35 PM (ET)
Modified: 4/24/2019 3:35 PM (ET)