An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa
An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa
复制标题
COSMO-CLM区域气候模型模拟中部非洲降水的评估
DOI：
10.1002/joc.6372
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
A. Lenouo
中科院分区：
文献类型：
--
作者：
Gabriel Fotso‐Kamga;Thierry C. Fotso‐Nguemo;I. Diallo;Z. Yepdo;W. Pokam;D. Vondou;A. Lenouo
在这项研究中，利用ERA-TIMAL(ERAINT)再分析数据，与气候模式小规模模拟联盟(CCLM)合作，对中部非洲(CA)区域的现代气候模拟(1998-2008年)进行了分析。评估了CCLM模拟观测降水的能力，特别是对平均空间型、低层环流、季节循环和日特征的模拟。同样，还考察了区域模式CCLM与驱动再分析ERAINT的附加值。结果表明，ERAINT和CCLm表现出明显不同的偏差信号，这表明了内部变率和细尺度过程表示对地面气候模拟的重要性。尽管CCLM在南加州持续干燥，但模式成功地再现了降水和低层环流特征的平均空间型，以及整个南加州和选定的五个分析子区的大部分季节周期。结果还表明，日降水量指数具有较好的代表性，但较好的表现在很大程度上取决于所考虑的季节。尽管如此，CCLM的表现大大优于ERAINT的日降水特征，从而突出了该区域缩减尺度工作的附加值。对日降水指数的分析还表明，模式的干燥特征可能与低估了模拟的较弱事件有关，从而导致了对模拟干旱持续时间的高估。
In this study, an analysis of present day climate simulation (1998–2008) is presented for the Central African (CA) region with the COnsortium for Small‐scale MOdelling in CLimate Mode (CCLM) regional climate model, forced by the ERA‐Interim (ERAINT) reanalysis data. The ability of the CCLM to simulate the observed precipitation with particular focus on the mean spatial pattern, low‐level circulation, seasonal cycles, and daily characteristics is evaluated. Likewise, the added value of the regional model CCLM compared to the driving ERAINT reanalysis is also investigated. It is shown that ERAINT and CCLM exhibit quite different sign of bias, which is an indication of the importance of internal variability and fine scale processes representation for the simulation of surface climate. Despite the CCLM is constantly dry over southern CA, the model succeeds to reproduce reasonably the mean spatial patterns of precipitation and low‐level circulation features, along with the associated seasonal cycles over the whole CA and majority of the five selected analysis sub‐regions. Results also show that daily precipitation indices are well represented, although the better performance greatly depends on the considered seasons. Nevertheless, CCLM substantially outperforms the ERAINT daily precipitation characteristics, thus highlighting the added value of the downscaling exercise over the region. The analysis of daily precipitation indices also reveals that the dry character of the model could probably be connected to the underestimation of the simulated less intense events, which in turn result to an overestimation of the simulated dry spell duration.
影响因子：
5.2
作者：
Ross Maidment;R. Allan;E. Black
通讯作者：
Ross Maidment;R. Allan;E. Black
影响因子：
4.4
作者：
Sillmann, J.;Kharin, V. V.;Bronaugh, D.
通讯作者：
Bronaugh, D.