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Advances in Atmospheric Sciences

, Volume 35, Issue 8, pp 1063–1076 | Cite as

Representation of the ENSO Combination Mode and its Asymmetric SST Response in Different Resolutions of HadGEM3

  • Jianghua Wan
  • Hongli Ren
  • Peili Wu
Original Paper
  • 43 Downloads

Abstract

Previous studies have revealed a combination mode (C-mode) occurring in the Indo-Pacific region, arising from nonlinear interactions between ENSO and the western Pacific warm pool annual cycle. This paper evaluates the simulation of this C-mode and its asymmetric SST response in HadGEM3 and its resolution sensitivity using three sets of simulations at horizontal resolutions of N96, N216 and N512. The results show that HadGEM3 can capture well the spatial pattern of the C-mode associated surface wind anomalies, as well as the asymmetric response of SST in the tropical Pacific, but it strongly overestimates the explained variability of the C-mode compared to the ENSO mode. The model with the three resolutions is able to reproduce the distinct spectral peaks of the C-mode at the near annual combination frequencies, but the performance in simulating the longer periods is not satisfactory, presumably due to the unrealistic simulation of the ENSO mode. Increasing the horizontal resolution can improve the consistency between atmospheric and oceanic representations of the C-mode, but not necessarily enhance the accuracy of C-mode simulation compared with observation.

Key words

ENSO combination mode asymmetric response Niño-A index HadGEM3 horizontal resolution 

摘要

前人研究表明印度洋-太平洋地区存在由ENSO变率和西太平洋暖池背景年循环非线性相互作用导致的衍生模态(C-mode). 本文基于N96、N216和N512三组不同空间分辨率的HadGEM3模式模拟结果, 评估了该模式对C-mode及其非对称SST响应的模拟情况, 和其对空间分辨率的敏感性. 结果表明HadGEM3能较好模拟表层风场中C-mode模态的空间分布, 以及该模态在热带太平洋SST中的非对称响应. 但是相比于ENSO模态, 模式对C-mode模态模拟过强. 不同分辨率的模式都能重现C-mode功率谱在接近年循环附近两个耦合频率的峰值, 但是在低频部分表现欠佳, 可能是因为ENSO模态模拟的不理想. 增加模式水平分辨率有助于提高模拟的C-mode在大气与海洋中的一致性, 但是与观测相比, 其模拟准确性并没有显著提升.

关键词

ENSO衍生模态 非对称响应 Niño-A指数 HadGEM3 水平分辨率 

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Notes

Acknowledgements

This work and its contributors were jointly supported by the China Meteorological Administration Special Public Welfare Research Fund (Grant No. GYHY201506013), the China National Science Foundation (Grant No. 41606019), and the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.

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Copyright information

© British Crown (administered by Met Office); Jianghua WAN and Hongli REN 2018

Authors and Affiliations

  1. 1.Laboratory for Climate Studies, and CMA-NJU Joint Laboratory for Climate Prediction Studies, National Climate CenterChina Meteorological AdministrationBeijingChina
  2. 2.Department of Atmospheric SciencesSchool of Environment Studies University of GeoscienceWuhanChina
  3. 3.Met Office Hadley CenterExeterUK

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