A Critical Evaluation and Future Projection of Extreme Precipitation Over South Korea in Observation-Based Products and a High-Resolution Model Simulation

IF 2.2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Christian L. E. Franzke, Lichao Yang, Jun-Hyeok Son, June-Yi Lee, Kyung-Ja Ha, Sun-Seon Lee
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Abstract

For climate risk assessments accurate gridded data sets are needed. An important aspect of such data sets is that they reliably represent the spatial and temporal characteristics of extreme events. This is particularly important for precipitation extreme events which are still not well represented in climate models. Here, we compare South Korean station data with two observation-based gridded data sets (APHRODITE and ERA5-Land) and data from global high-resolution Community Earth System Model (CESM) simulations with an atmospheric resolution of about 25km. We find that the two observation-based data sets have a lower level of the 99th percentile than the station data, but that CESM reproduces extreme events better. Our study provides evidence for an overall historical decrease in very large extreme events in the station data, which is not the case in the two gridded data sets. However, changes in extremes are locally dependent as shown by local quantile regression analysis; where local historical increases in precipitation extremes are statistically significant. The spatial dependence of extreme precipitation events is not well reproduced by the two gridded data sets but well by CESM. The temporal clustering of precipitation extremes is well reproduced by all data sets. Compared to the present day simulation, the CESM simulation of a warmer climate state shows an overall increase in mean precipitation and precipitation extremes and regionally dependent changes in temporal clustering. The model results also provide evidence for a change in spatial dependence in a warmer climate with spatially larger extreme precipitation systems possible. Our results highlight the need to produce better observation-based gridded data sets and also the need to adapt to more intense and frequent extreme precipitation events in the future in South Korea.

Abstract Image

基于观测的产品和高分辨率模型模拟对韩国极端降水的严格评估和未来预测
气候风险评估需要精确的网格数据集。这些数据集的一个重要方面是它们能可靠地反映极端事件的时空特征。这一点对于降水极端事件尤为重要,因为气候模式还不能很好地反映降水极端事件。在这里,我们将韩国的站点数据与两个基于观测的网格数据集(APHRODITE 和 ERA5-Land)以及大气分辨率约为 25km 的全球高分辨率群落地球系统模式(CESM)模拟数据进行了比较。我们发现,这两个基于观测的数据集的第 99 百分位数水平低于站点数据,但 CESM 对极端事件的再现效果更好。我们的研究提供的证据表明,在气象站数据中,超大型极端事件在历史上总体上有所减少,而在两套网格数据中却并非如此。然而,正如局部量值回归分析所显示的那样,极端事件的变化与局部地区有关;在局部地区,历史上极端降水量的增加具有显著的统计学意义。两个网格数据集不能很好地再现极端降水事件的空间依赖性,但 CESM 却能很好地再现。所有数据集都很好地再现了极端降水的时间聚类。与现在的模拟结果相比,CESM 对气候变暖状态的模拟结果表明,平均降水量和极端降水量总体上有所增加,时间聚类的变化也与区域有关。模型结果还证明,在气候变暖的情况下,空间依赖性也会发生变化,极端降水系统的空间范围可能会更大。我们的研究结果突出表明,需要制作更好的基于观测的网格数据集,也需要适应韩国未来更强烈、更频繁的极端降水事件。
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来源期刊
Asia-Pacific Journal of Atmospheric Sciences
Asia-Pacific Journal of Atmospheric Sciences 地学-气象与大气科学
CiteScore
5.50
自引率
4.30%
发文量
34
审稿时长
>12 weeks
期刊介绍: The Asia-Pacific Journal of Atmospheric Sciences (APJAS) is an international journal of the Korean Meteorological Society (KMS), published fully in English. It has started from 2008 by succeeding the KMS'' former journal, the Journal of the Korean Meteorological Society (JKMS), which published a total of 47 volumes as of 2011, in its time-honored tradition since 1965. Since 2008, the APJAS is included in the journal list of Thomson Reuters’ SCIE (Science Citation Index Expanded) and also in SCOPUS, the Elsevier Bibliographic Database, indicating the increased awareness and quality of the journal.
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