CMIP6 GCMs模拟越南湄公河三角洲降水和温度的性能评价

IF 0.7 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Climate Change Pub Date : 2023-06-17 DOI:10.3233/jcc230013
Tran Van Ty, Le Hai Tri, Nguyen Van Tho, Nguyen Van Toan, Giap Minh Nhat, N. Downes, Pankaj Kumar, Huỳnh Vương Thu Minh
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引用次数: 0

摘要

本研究评估了越南湄公河三角洲(VMD)气候模式比较项目第6阶段(CMIP6)历史运行中模拟降水和最高、最低温度的表现。利用归一化均方根误差(NRMSE)、偏倚百分比(PBIAS)、纳什-萨特克利夫效率(NSE)、决定系数(R2)和体积效率(VE)等统计指标,将16个环流模式(GCMs)的降水以及最高和最低气温输出与12个站点1980-2014年的观测结果进行了比较。最后进行排名(总分- TS),并采用概率分布函数(PDF)和泰勒图确定排名。结果表明,不同的统计指标揭示了16种gcm的变化排序。基于RS排序,表明每种模拟GCM在不同指标下表现不同,没有单一模型在所有指标下表现最好。基于TS的前5位GCMs分别为HadGEM3-GC31-LL、ACCESS-CM2、CanESM5、NESM3和CanESM5- canoe;CNRM-CM6-1、CNRM-ESM2-1、GFDL-ESM4、NESM3和INM-CM5-0最大;CNRM-CM6-1、CNRM-ESM2-1、GFDL-ESM4、NESM3和INM-CM5-0的最低温度。我们还观察到在研究区域降水的低估和温度的高估。TS方法对基于不同统计指标的多模式集合gcm进行了有效的聚合,这些统计指标有时是相互矛盾的。本研究的结果为选择适合气候变化应用的gcm提供了有益的指导。
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Evaluating the Performance of CMIP6 GCMs to Simulate Precipitation and Temperature Over the Vietnamese Mekong Delta
This study evaluates the performance of simulated precipitation and maximum and minimum temperatures in the historical runs of the Climate Model Intercomparison Project Phase 6 (CMIP6) for the Vietnamese Mekong Delta (VMD). The precipitation, as well as maximum and minimum temperatures outputs from 16 general circulation models (GCMs), were compared with observations from 12 stations for the period 1980–2014, using a set of statistical metrics, namely, normalised root mean square error (NRMSE), percentage of bias (PBIAS), Nash–Sutcliffe efficiency (NSE), coefficient of determination (R2), and volumetric efficiency (VE). Finally, ranking (total score - TS) was carried out and the probability distribution function (PDF) and Taylor diagram were used to confirm rankings. The results show that different statistical indicators reveal variation ranking order of the 16 GCMs. Based on RS ranking, it is indicated that each simulation GCM performed differently under the different metrics and no single model performed best for all metrics. The top five highest ranked GCMs based on TS were HadGEM3-GC31-LL, ACCESS-CM2, CanESM5, NESM3 and CanESM5-CanOE for precipitation; and CNRM-CM6-1, CNRM-ESM2-1, GFDL-ESM4, NESM3 and INM-CM5-0 for the maximum; and CNRM-CM6-1, CNRM-ESM2-1, GFDL-ESM4, NESM3 and INM-CM5-0 for minimum temperatures, respectively. We also observed an underestimation of precipitation and an overestimation of temperature over the study area. The TS method demonstrates efficiency to aggregate the multi-model ensemble GCMs based on different statistical indicators which were sometimes contradictory. The findings from this study provide useful guidance in the selection of GCMs for climate change applications in the VMD.
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来源期刊
Journal of Climate Change
Journal of Climate Change METEOROLOGY & ATMOSPHERIC SCIENCES-
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16.70%
发文量
18
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