Evaluation of CMIP6 GCMs for Simulating Atmospheric Rivers: Relating The Model Skill For Key AR Variables to the Skill for Winds and Water Vapor

IF 2.2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Jinwon Kim, Tae-Jun Kim, Jin-Uk Kim, Chu-Yong Chung, Young-Hwa Byun
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引用次数: 0

Abstract

Fifteen GCMs in the Coupled Model Intercomparison Project Phase 6 are evaluated for the skill in simulating the atmospheric river (AR) frequency (FAR) and integrated vapor transport (IVT) during 1995–2014. All GCMs simulate well the annual and seasonal climatology of FAR and IVT for both the global and East Asia domains. Large biases in FAR and IVT occur in the same regions characterized by high AR activities including the midlatitude Pacific and Atlantic oceans, the Southern Ocean, and the tropical region from the eastern Indian Ocean to the western Pacific. The sign and magnitude of large model errors vary across the GCMs to result in small model-mean biases. The seasonal variation of the skill of individual GCMs is smaller than the variation of the skill across the GCMs, implying that the model skill varies more widely by the difference in model formulations than the response of individual GCMs to seasonal forcing variations. A novel method to relate the skill for simulating FAR and IVT to that for winds and water vapor is introduced. The method shows that the vertical integration of the covariance of wind and water vapor in the definition of IVT can be well approximated by the multiplication of two separate functions obtained by vertically integrating either winds or water vapor, especially in the regions of strong AR activities. Spearman’s rank correlation in conjunction with this method suggests that the model skill for FAR and IVT is significantly related only to that for winds.

Abstract Image

CMIP6 GCMs对大气河流模拟的评价:关键AR变量模式技能与风和水汽技能的关系
对耦合模式比对项目第6阶段15个gcm在1995-2014年模拟大气河(AR)频率(FAR)和综合水汽输送(IVT)的能力进行了评价。所有gcm都很好地模拟了FAR和IVT在全球和东亚地区的年和季节气候学。FAR和IVT的较大偏差发生在具有高AR活动特征的相同区域,包括中纬度太平洋和大西洋、南大洋以及从东印度洋到西太平洋的热带地区。大模型误差的符号和大小在不同的gcm中变化,导致较小的模型均值偏差。单个gcm技能的季节变化小于整个gcm技能的变化,这意味着模式技能因模式配方的差异而变化的范围比单个gcm对季节强迫变化的响应更大。本文介绍了一种将模拟风和水汽的技术与模拟远场和IVT技术联系起来的新方法。该方法表明,在IVT定义中,风和水汽的协方差的垂直积分可以很好地近似为由风或水汽垂直积分得到的两个独立函数的乘法,特别是在强AR活动区域。Spearman的等级相关性与该方法结合表明,FAR和IVT的模型技能仅与风的模型技能显著相关。
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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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