Assessment and correction of BCC_CSM's performance in capturing leading modes of summer precipitation over North Asia

气候学 降水 环境科学 大气科学 地质学 气象学 地理
作者
Zhiqiang Gong,Muhammad Mubashar Dogar,Shaobo Qiao,Peng Hu,Guolin Feng
出处
期刊:International Journal of Climatology [Wiley]
卷期号:38 (5): 2201-2214 被引量:16
标识
DOI:10.1002/joc.5327
摘要

ABSTRACT This article examines the ability of Beijing Climate Center Climate System Model (BCC_CSM) in demonstrating the prediction accuracy and the leading modes of the summer precipitation over North Asia (NA). A dynamic‐statistic combined approach for improving the prediction accuracy and the prediction of the leading modes of the summer precipitation over NA is proposed. Our results show that the BCC_CSM can capture part of the spatial anomaly features of the first two leading modes of NA summer precipitation. Moreover, BCC_CSM regains relationships such that the first and second mode of the empirical orthogonal function (EOF1 and EOF2) of NA summer precipitation, respectively, corresponds to the development of the El Niño and La Niña conditions in the tropical East Pacific. Nevertheless, BCC_CSM exhibits limited prediction skill over most part of NA and presents a deficiency in reproducing the EOF1's and EOF2's spatial pattern over central NA and EOF2's interannual variability. This can be attributed as the possible reasons why the model is unable to capture the correct relationships among the basic climate elements over the central NA, lacks in its ability to reproduce a consistent zonal atmospheric pattern over NA, and has bias in predicting the relevant Sea Surface Temperature (SST) modes over the tropical Pacific and Indian Ocean regions. Based on the proposed dynamic‐statistic combined correction approach, compared with the leading modes of BCC_CSM's original prediction, anomaly correlation coefficients of corrected EOF1/EOF2 with the tropical Indian Ocean SST are improved from 0.18/0.36 to 0.51/0.62. Hence, the proposed correction approach suggests that the BCC_CSM's prediction skill for the summer precipitation prediction over NA and its ability to capture the dominant modes could be certainly improved by choosing proper historical analogue information.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小蘑菇应助乐观的幼珊采纳,获得10
1秒前
cookie完成签到,获得积分10
1秒前
2秒前
JamesPei应助干净采珊采纳,获得10
3秒前
xzq发布了新的文献求助10
3秒前
科研通AI6.2应助吴豁采纳,获得10
4秒前
4秒前
4秒前
4秒前
CC完成签到,获得积分10
5秒前
搜集达人应助qiu采纳,获得10
7秒前
7秒前
11发布了新的文献求助10
7秒前
朱富强完成签到,获得积分20
8秒前
小橙完成签到 ,获得积分10
8秒前
搜集达人应助小果儿采纳,获得10
9秒前
9秒前
9秒前
生尽证提完成签到,获得积分10
9秒前
柳景凇发布了新的文献求助10
9秒前
song完成签到 ,获得积分10
10秒前
强砸完成签到,获得积分10
10秒前
可爱的函函应助满意的天采纳,获得10
11秒前
可靠如风发布了新的文献求助10
11秒前
11秒前
狮子清明尊完成签到,获得积分10
12秒前
13秒前
crown1010完成签到,获得积分10
13秒前
小大夫完成签到 ,获得积分10
14秒前
CFD应助xzq采纳,获得30
14秒前
YunjiangZhang发布了新的文献求助10
15秒前
泷生发布了新的文献求助10
15秒前
NSS完成签到,获得积分10
15秒前
xinxin完成签到,获得积分10
17秒前
gmat50发布了新的文献求助10
17秒前
17秒前
17秒前
无敌猫猫头完成签到,获得积分10
17秒前
18秒前
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Developing Genetic Editing Tools for Lysobacter 2000
卤化钙钛矿人工突触的研究 2000
Моделирование процессов самоорганизации в кристаллообразующих системах 1000
History of U.S. Space Surveillance and Satellite Cataloging 1000
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6517669
求助须知:如何正确求助?哪些是违规求助? 8310643
关于积分的说明 17766146
捐赠科研通 5619836
什么是DOI,文献DOI怎么找? 2926068
邀请新用户注册赠送积分活动 1902896
关于科研通互助平台的介绍 1763873