ENSO Impacts on Extreme Precipitation: What can be Inferred from over 20 years of TRMM/GPM Data?
Abstract
The impacts of the El Nino-Southern Oscillation (ENSO) on precipitation has been studied for nearly a century, yet their quantification remains uncertain, particularly, in terms of extreme precipitation events. Previous research has shown that this persistent interaction of anomalous sea surface temperatures and pressures have teleconnective behaviors that affect extreme weather patterns globally. However, most analysis has been limited by the spatial or temporal resolution of the available datasets, or uncertainties in measurement or modeling results. There are now over 20 years of active satellite precipitation radar (PR) data gathered by the Tropical Rainfall Measurement Mission (TRMM; 1997-2014) and the Global Precipitation Measurement (GPM; 2014-present) mission, providing the most comprehensive three-dimensional snapshot of rainfall to date over the tropics and subtropics. The goal of this research is to use this novel dataset to visualize and quantify the impacts of ENSO on extreme precipitation and compare to previous findings.
The TRMM and GPM datasets are combined using cumulative distribution matching and projected onto a 1⁰ grid, while the Oceanic Nino Index (ONI) is used to parse the data into the different ENSO phases and seasons. This study focuses on the percent change in monthly counts of certain extreme events (25, 50, and 100 mm/hr) during the different ENSO phases. In order to test significance, create useful confidence bounds, and overcome sample size limitations, bootstrapping is performed at each grid cell utilizing the University of Minnesota's supercomputing facilities. Overall, the impacts of ENSO on extreme precipitation typically follow the impacts on mean precipitation and the results are not completely symmetric, meaning, increased frequency in extremes during La Nina do not necessarily mean decreased frequency during El Nino and vice versa. We have identified the key impact regions of ENSO and quantify how much more or less frequently extreme events occur in these key areas based on rainfall intensity. This research validates previous findings with a novel dataset, while providing robust methods and results for quantifying and understanding the effects of ENSO on extreme precipitation.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H54B..04S
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 1817 Extreme events;
- HYDROLOGYDE: 1847 Modeling;
- HYDROLOGY