Statistical characteristics of extreme daily precipitation during 1501 BCE–1849 CE in the Community Earth System Model

Woon Mi Kim,Christoph C Raible,Michael Sigl,Richard Blender,Martina Messmer

doi:10.5194/cp-17-2031-2021

Abstract

Abstract. In this study, we analyze extreme daily precipitation during the pre-industrial period from 1501 BCE to 1849 CE in simulations from the Community Earth System Model version 1.2.2. A peak-over-threshold (POT) extreme value analysis is employed to examine characteristics of extreme precipitation and to identify connections of extreme precipitation with the external forcing and with modes of internal variability. The POT analysis shows that extreme precipitation with similar statistical characteristics, i.e., the probability density distributions, tends to cluster spatially. There are differences in the distribution of extreme precipitation between the Pacific and Atlantic sectors and between the northern high and southern low latitudes. Extreme precipitation during the pre-industrial period is largely influenced by modes of internal variability, such as El Niño–Southern Oscillation (ENSO), the Pacific North American, and Pacific South American patterns, among others, and regional surface temperatures. In general, the modes of variability exhibit a statistically significant connection to extreme precipitation in the vicinity to their regions of action. The exception is ENSO, which shows more widespread influence on extreme precipitation across the Earth. In addition, the regions with which extreme precipitation is more associated, either by a mode of variability or by the regional surface temperature, are distinguished. Regional surface temperatures are associated with extreme precipitation over lands at the extratropical latitudes and over the tropical oceans. In other regions, the influence of modes of variability is still dominant. Effects of the changes in the orbital parameters on extreme precipitation are rather weak compared to those of the modes of internal variability and of the regional surface temperatures. Still, some regions in central Africa, southern Asia, and the tropical Atlantic ocean show statistically significant connections between extreme precipitation and orbital forcing, implying that in these regions, extreme precipitation has increased linearly during the 3351-year pre-industrial period. Tropical volcanic eruptions affect extreme precipitation more clearly in the short term up to a few years, altering both the intensity and frequency of extreme precipitation. However, more apparent changes are found in the frequency than the intensity of extreme precipitation. After eruptions, the return periods of extreme precipitation increase over the extratropical regions and the tropical Pacific, while a decrease is found in other regions. The post-eruption changes in the frequency of extreme precipitation are associated with ENSO, which itself is influenced by tropical eruptions. Overall, the results show that climate simulations are useful to complement the information on pre-industrial extreme precipitation, as they elucidate statistical characteristics and long-term connections of extreme events with natural variability.

Highlights

Extreme daily precipitation, which often causes devastating flood events, is a difficult phenomenon to study due to its rare occurrence and short-lived nature
The results show that climate simulations are useful to complement the information on pre-industrial extreme precipitation, as they elucidate statistical characteristics and long-term connections of extreme events with natural variability
We compare the daily precipitation in ERA5 and Community Earth System Model (CESM) for the period 1979–2008 CE to evaluate the model’s ability to represent the mean and extreme daily precipitation

Summary

Introduction

Extreme daily precipitation, which often causes devastating flood events, is a difficult phenomenon to study due to its rare occurrence and short-lived nature. While mean precipitation is expected to follow largely the “wet gets wetter, and dry gets drier” rule (Trenberth et al, 2003; Chou and Neelin, 2004; Chou et al, 2009), extreme precipitation is projected to increase over the entire globe (Trenberth et al, 2003; Donat et al, 2016; Fischer and Knutti, 2016). The “wet gets wetter, and dry gets drier” pattern denotes the intensification of the global hydrological cycle, which is controlled by a tropospheric energy budget (Boer, 1993; Allen and Ingram, 2002; Yang et al, 2003). It is noted that this pattern for the future mean precipitation is more heterogeneous over land areas in observations and climate models (Roderick et al, 2014; Byrne and O’Gorman, 2015) and breaks in the tropics in CMIP5 models (Chadwick et al, 2013)

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