Affiliation:
1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Beijing, China
Abstract
AbstractThe global land monsoon region, with substantial monsoon rainfall and hence freshwater resources, is home to nearly two-thirds of the world’s population. However, it is overwhelmed by extreme precipitation, which is more intense than that on the rest of the land. Whether extreme precipitation has changed significantly, particularly in association with global warming, remains unclear for this region. This study investigates the presence of monotonic trends in extreme precipitation and its association with global warming over the past century over the global land monsoon regions, by employing the most comprehensive, long-running, and high-quality observational extreme precipitation records currently available. Based on a total of 5066 stations with at least 50 years of records, we found significant increases in the annual maximum daily precipitation and associations with global warming in regional monsoon domains, including the southern part of the South African monsoon region, the South Asian monsoon region (dominated by India), the North American monsoon region, and the eastern part of the South American monsoon region during the period of 1901–2010, with responses to global warming of ~10.4%–14.2% K−1, 7.9%–8.3% K−1, 6.4%–10.8% K−1, and 15.1%–24.8% K−1, respectively. For the global monsoon region as a whole, significant increases in extreme precipitation and associations with global warming are also identified, but with limited spatial coverage. The qualitative results on the significance of the changes on the regional scale are generally robust against different time periods, record lengths of stations, and datasets used. The uncertainty in the quantitative results arising from limited spatial and temporal coverages and use of different datasets deserves attention.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
International Partnership Program of Chinese Academy of Sciences
China Postdoctoral Science Foundation
Publisher
American Meteorological Society