We apply a methodology to identify and count records (events of unprecedented intensity) in daily precipitation time series to two sets of data: (1) different observational and reanalysis products for recent decades and (2) twenty-first century projections (RCP8.5 and RCP2.6 scenarios) completed with two regional climate models driven by three global climate models over nine continental-scale domains. Comparison of the detected (or actual) number of records with the corresponding number theoretically expected in stationary climate conditions (or “reference” number of records) provides indications of trends in daily precipitation extremes, as expected in a changing climate. In particular, we measure deviations from stationary conditions using the ratio of actual to reference records (RAtR) as a basic metric. We find that the observational products provide mixed indications of precipitation record trends across regions, while in the reanalysis products and the model simula- tions for the historical period the RAtR value shows a prevailing increasing trend with time over most continents. The RAtR shows a consistent and pronounced increase in all RCP8.5 continental-scale projections, when sustained warming occurs throughout the 21st century, while smaller to no significant trends are found in the RCP2.6 scenario, when the warming stabilizes after about mid-21st century. These results are indicative of an increase in precipitation extremes with global warming as measured by the higher number of local precipitation events of unprecedented intensity compared to what expected in stationary climate conditions, although a marked variability of this response is found across different regions. Our method can have useful applications in detection and attribution of hydroclimatic extremes and in impact and vulnerability assessment studies.

Continental-scale trends of daily precipitation records in late 20th century decades and 21st century projections: An analysis of observations, reanalyses and CORDEX-CORE projections

Maugeri M.
Writing – Original Draft Preparation
;
Ranzi R.
Writing – Original Draft Preparation
;
2023-01-01

Abstract

We apply a methodology to identify and count records (events of unprecedented intensity) in daily precipitation time series to two sets of data: (1) different observational and reanalysis products for recent decades and (2) twenty-first century projections (RCP8.5 and RCP2.6 scenarios) completed with two regional climate models driven by three global climate models over nine continental-scale domains. Comparison of the detected (or actual) number of records with the corresponding number theoretically expected in stationary climate conditions (or “reference” number of records) provides indications of trends in daily precipitation extremes, as expected in a changing climate. In particular, we measure deviations from stationary conditions using the ratio of actual to reference records (RAtR) as a basic metric. We find that the observational products provide mixed indications of precipitation record trends across regions, while in the reanalysis products and the model simula- tions for the historical period the RAtR value shows a prevailing increasing trend with time over most continents. The RAtR shows a consistent and pronounced increase in all RCP8.5 continental-scale projections, when sustained warming occurs throughout the 21st century, while smaller to no significant trends are found in the RCP2.6 scenario, when the warming stabilizes after about mid-21st century. These results are indicative of an increase in precipitation extremes with global warming as measured by the higher number of local precipitation events of unprecedented intensity compared to what expected in stationary climate conditions, although a marked variability of this response is found across different regions. Our method can have useful applications in detection and attribution of hydroclimatic extremes and in impact and vulnerability assessment studies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/584767
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