Journal article
Determining the Anthropogenic Greenhouse Gas Contribution to the Observed Intensification of Extreme Precipitation
S Paik, SK Min, X Zhang, MG Donat, AD King, Q Sun
Geophysical Research Letters | American Geophysical Union | Published : 2020
DOI: 10.1029/2019GL086875
Abstract
This study conducts a detection and attribution analysis of the observed changes in extreme precipitation during 1951–2015. Observed and CMIP6 multimodel simulated changes in annual maximum daily and consecutive 5-day precipitation are compared using an optimal fingerprinting technique for different spatial scales from global land, Northern Hemisphere extratropics, tropics, three continental regions (North America and western and eastern Eurasia), and global “dry” and “wet” land areas (as defined by their average extreme precipitation intensities). Results indicate that anthropogenic greenhouse gas influence is robustly detected in the observed intensification of extreme precipitation over t..
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Grants
Awarded by Korea Meteorological Administration Research and Development Program
Awarded by National Research Foundation of Korea (NRF) - South Korean government (MSIT)
Awarded by Spanish Ministry for the Economy, Industry and Competitiveness Ramon y Cajal 2017 grant
Awarded by Horizon 2020 EUCP project
Awarded by Australian Research Council
Funding Acknowledgements
This study is supported by the Korea Meteorological Administration Research and Development Program under Grant KMI2018-03610 and by a National Research Foundation of Korea (NRF) grant funded by the South Korean government (MSIT) (NRF2018R1A5A1024958). M. G. D. is grateful for funding by the Spanish Ministry for the Economy, Industry and Competitiveness Ramon y Cajal 2017 grant (reference RYC-2017-22964) and the Horizon 2020 EUCP project (Grant Agreement 776613). A. D. K. receives funding from the Australian Research Council (DE180100638). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access (https://esgf-node.llnl.gov/projects/cmip6/), and the multiple funding agencies who support CMIP6 and ESGF.