重新审视南半球冬季风暴轨迹趋势中再分析与模型之间的差异

IF 8.5 1区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES npj Climate and Atmospheric Science Pub Date : 2024-10-19 DOI:10.1038/s41612-024-00801-3
Joonsuk M. Kang, Tiffany A. Shaw, Sarah M. Kang, Isla R. Simpson, Yue Yu
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引用次数: 0

摘要

在卫星时代,南半球(SH)风暴增加,而最近的研究表明,综合气候模式大大低估了这一趋势。在此,我们重新审视了再分析与模式的趋势差异,以更好地理解其背后的机制。全面的同类分析表明,再分析的趋势具有很大的不确定性,耦合气候模式模拟的趋势弱于大多数再分析,但不是所有再分析。然而,具有规定海表温度(SST)的模拟显示出明显更大的风暴潮趋势,尤其是在南太平洋,这意味着耦合模拟中的 SST 趋势差异会影响风暴潮趋势。利用修正了南大洋和东太平洋热带海面温度趋势差异的起搏器模拟,我们发现耦合模拟中的暴雨趋势被低估了,因为它们没有捕捉到南大洋降温和类似拉尼娜的远距离联系趋势所导致的暴雨增强。我们的研究结果强调了再分析在 SH 环流趋势中的巨大不确定性,以及区域 SST 趋势差异对环流趋势的影响。
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Revisiting the reanalysis-model discrepancy in Southern Hemisphere winter storm track trends
Southern Hemisphere (SH) storminess has increased in the satellite era and recent work suggests comprehensive climate models significantly underestimate the trend. Here, we revisit this reanalysis-model trend discrepancy to better understand the mechanisms underlie it. A comprehensive like-for-like analysis shows reanalysis trends exhibit large uncertainty, and coupled climate model simulations exhibit weaker trends than most but not all reanalyses. However, simulations with prescribed sea surface temperature (SST) exhibit significantly greater storminess trends, particularly in the South Pacific, implying SST trend discrepancies in coupled simulations impact storminess trends. Using pacemaker simulations that correct Southern Ocean and tropical east Pacific SST trend discrepancies, we show that storminess trends in coupled simulations are underestimated because they do not capture the enhanced storminess resulting from Southern Ocean cooling and La-Nina-like teleconnection trends. Our findings emphasize large reanalysis uncertainty in SH circulation trends and the impact of regional SST trend discrepancies on circulation trends.
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来源期刊
npj Climate and Atmospheric Science
npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science
CiteScore
8.80
自引率
3.30%
发文量
87
审稿时长
21 weeks
期刊介绍: npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.
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