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北美多模式集合中的印度夏季风变率预测。

Indian summer monsoon variability forecasts in the North American multimodel ensemble.

作者信息

Singh Bohar, Cash Ben, Kinter Iii James L

机构信息

1George Mason University, Fairfax, VA 22031 USA.

2Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, VA 22031 USA.

出版信息

Clim Dyn. 2019;53(12):7321-7334. doi: 10.1007/s00382-018-4203-6. Epub 2018 Apr 12.

DOI:10.1007/s00382-018-4203-6
PMID:31929686
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6934244/
Abstract

The representation of the seasonal mean and interannual variability of the Indian summer monsoon rainfall (ISMR) in nine global ocean-atmosphere coupled models that participated in the North American Multimodal Ensemble (NMME) phase 1 (NMME:1), and in nine global ocean-atmosphere coupled models participating in the NMME phase 2 (NMME:2) from 1982-2009, is evaluated over the Indo-Pacific domain with May initial conditions. The multi-model ensemble (MME) represents the Indian monsoon rainfall with modest skill and systematic biases. There is no significant improvement in the seasonal forecast skill or interannual variability of ISMR in NMME:2 as compared to NMME:1. The NMME skillfully predicts seasonal mean sea surface temperature (SST) and some of the teleconnections with seasonal mean rainfall. However, the SST-rainfall teleconnections are stronger in the NMME than observed. The NMME is not able to capture the extremes of seasonal mean rainfall and the simulated Indian Ocean-monsoon teleconnections are opposite to what are observed.

摘要

对参与北美多模式集合（NMME）第一阶段（NMME:1）的9个全球海洋-大气耦合模式以及参与1982 - 2009年NMME第二阶段（NMME:2）的9个全球海洋-大气耦合模式中印度夏季风降雨（ISMR）的季节平均值和年际变率表示进行了评估，评估范围为印度洋-太平洋区域，初始条件为5月。多模式集合（MME）对印度季风降雨的表示具有一定技巧，但存在系统性偏差。与NMME:1相比，NMME:2在ISMR的季节预测技巧或年际变率方面没有显著改善。NMME能够巧妙地预测季节平均海表面温度（SST）以及一些与季节平均降雨的遥相关。然而，NMME中SST - 降雨遥相关比观测到的更强。NMME无法捕捉到季节平均降雨的极端情况，并且模拟的印度洋 - 季风遥相关与观测结果相反。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/3d5725287cfc/382_2018_4203_Fig14_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/3d5725287cfc/382_2018_4203_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/4a292108f31a/382_2018_4203_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/be734121fcf2/382_2018_4203_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/dcbf386df07c/382_2018_4203_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/a1966aaf4e01/382_2018_4203_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/dc57d1699ad3/382_2018_4203_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/d509d9d2a396/382_2018_4203_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/1cfd9ae88f21/382_2018_4203_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/0f6e8bb96a3c/382_2018_4203_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/ee0bd18e3b51/382_2018_4203_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/3ad4e1f9f877/382_2018_4203_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/a68c7b3c57aa/382_2018_4203_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/24b3494b2540/382_2018_4203_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/eb13f2d3cec9/382_2018_4203_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1eb/6934244/3d5725287cfc/382_2018_4203_Fig14_HTML.jpg

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