What is it about?
This study compares seven different global precipitation datasets to see how well they match up with biological data like vegetation greenness and tree growth over time. The best precipitation datasets are those that can explain more changes in biological data. Various types of precipitation data were evaluated, like those derived from rain gauges, satellites, and a mix of both that also includes modelling estimates. The results showed that a dataset MSWEP performed best in more recent years, especially in places with fewer weather stations, like Africa. For longer time periods, another dataset called UDEL-TS performed well, particularly before the 1940s, especially in northern Asia and the Himalayas. Depending on the region and the time period being studied, researchers can use this information to choose the best precipitation dataset for their ecological research.
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Why is it important?
When performing ecological research the choice of data can influence results and choosing the best dataset is not always an easy task since they may use different validation techniques and performance metrics. By comparing all products against the same biological data, researchers have an objective way of comparing their ecological performance and improve the quality of their research.
Perspectives
This research was based on my own challenges in selecting a dataset for ecological research. I hope it provides a framework for others to explore the best dataset for their research or maybe just directly provides them with a good option with more confidence.
Vinicius Manvailer
University of Alberta
Read the Original
This page is a summary of: Validation of global precipitation time series products against tree ring records and remotely sensed vegetation greenness, PLoS ONE, February 2024, PLOS,
DOI: 10.1371/journal.pone.0299111.
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