image: (a) Map showing Eastern Asia's prevailing monsoon climates and the sampling site location. The topographic map comes from https://www.gebco.net/data_and_products/gridded_bathymetry_data/, and the red-filled circle and the white-filled circle represent the sampling site and Beijing, respectively. Abbreviations: ISM, Indian Summer Monsoon; EASM, East Asia Summer Monsoon; EAWM, East Asia Winter Monsoon. (b) The multi-year average monthly T, P, and δ18Oprecipitation in Zhengzhou (IAEA, http://www.iaea.org/water). The grey bar represents the growing seasons for Cathaica fasciola at Zhengzhou. The monthly mean T > 10oC from April to October. (c) Land snail Cathaica fasciola and the schematic flow chart for the cutting and sampling of snail shells. The red lines represent the sampling path of the subsamples for GSMS determination; The yellow arrows represent the direction of sampling, which is opposite to the growth direction. The enlarged section shows the sampling spots of SIMS analysis.
Credit: ©Science China Press
Extreme weather events, such as rainstorms, tropical cyclones, and heatwaves can occur across several days or even a few hours, and cause great damage to ecosystems and human settlements. An extreme rainstorm battered Zhengzhou, central China during July 17th to 22nd 2021 (then named “7.20” super rainstorm). Local daily precipitation was over 300mm and the region experienced nearly an entire year’s worth of precipitation within three days. This rainstorm has been regarded as an “once-in-a-millennium” weather event in meteorological statistics.
However, the “once-in-a-millennium” was so named from the instrumental data of the past hundred years. With rapid global warming, the climate background of extreme weather events is also changing rapidly. Therefore, whether “7.20” super rainstorm is an “once-in-a-millennium” disaster or a new normal event under a warmer world is still a pressing question to clarify. Given this uncertainty, obtaining extreme weather event variability under various climate conditions could greatly improve our understanding about mechanisms and dynamics of extreme weather events. However, due to the short time-span of most modern instrumental data (no more than 100 years) and coarse temporal resolution of most current paleoclimate records (ranging from years to millennia), it is fair to say that our knowledge about the intrinsic relationship between extreme weather variability and climate background is almost non-existent up to now.
Recently, the team of Dr. Hong Yan from Institute of Earth Environment, Chinese Academy of Sciences, tried to reconstructed the “7.20” super rainstorm using local land snail shells. Four modern land snail shells (Cathaica fasciola) were collected in the Zhengzhou-Xingyang area, one of the centers hit by the “7.20” super rainstorm (Fig. 1). Weekly and daily resolved snail shell δ18O records from June to September of 2021 were obtained by gas-source mass spectrometry (GSMS) and secondary ion mass spectrometry (SIMS). The daily resolved records show a dramatic negative shift between June 18th and September 18th, which is very likely to be related to the “7.20” super rainstorm according to the established age framework. Furthermore, the theoretical precipitation amounts of “7.20” super rainstorm calculated by the amplitude of this δ18O shift using flux balance model closely approaches to the precipitation amount observed at the local meteorological station (Fig. 2).
In fact, this study reveals, for the first time, that terrestrial synoptic scale extreme rainstorm events can be quantitively reconstructed by a natural paleoclimate archive. The application of current work on fossil snail shells in the older sedimentary strata may offer an opportunity to reveal the frequency and intensity of synoptic scale extreme rainstorms under different climate backgrounds (Fig. 3). These paleoweather information sources may prove to be essential sources to help understand the law and dynamics of regional extreme rainstorms, especially for calibrating numerical climatic models and predicting the future trend of extreme rainstorms.
Journal
Science Bulletin