Uncertainty assessment for climate change impact on intense precipitation: how many model runs do we need?
Uncertainty assessment for climate change impact on intense precipitation: how many model runs do we need?
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DOI：
10.1002/joc.5069
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发表时间：
2017-08-01
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影响因子：
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通讯作者：
Willems, Patrick
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作者：
Hosseinzadehtalaei, Parisa;Tabari, Hossein;Willems, Patrick
降水量预测通常是从不同未来情景下的大气环流模式（GCM）输出中获得的，然后将水文应用降尺度到流域或特定地点的尺度。然而，已知预测存在不确定性，需要加以量化。虽然大气环流模型通常被认为是气候变化水文影响评估不确定性的主要贡献者，但为了全面了解水文影响，必须考虑其他不确定性来源。本研究调查的不确定性相关的GCM，GCM初始条件和代表性的浓度路径（RCP）和它们的敏感性选择的GCM运行，以量化气候变化对极端降水和强度/持续时间/频率统计的影响。分析了140个CMIP 5 GCM试验的结果，包括15个GCM，3-10个GCM初始条件和4个RCP。尽管GCM的选择是所有重现期（1年，10年）和聚集水平（1，5，10，15和30天）的强降水变化不确定性的主要贡献者（在某些情况下高达65%），GCM初始条件和RCP的不确定性高达38%和23%，分别被发现在某些情况下。敏感性分析表明，GCM，RCP和GCM初始条件的不确定性的影响很大的一套气候模式运行考虑，特别是更极端的降水在更精细的时间尺度。
Precipitation projections are typically obtained from general circulation model (GCM) outputs under different future scenarios, then downscaled for hydrological applications to a watershed or site-specific scale. However, uncertainties in projections are known to be present and need to be quantified. Although GCMs are commonly considered the major contributor of uncertainty for hydrological impact assessment of climate change, other uncertainty sources must be taken into account for a thorough understanding of the hydrological impact. This study investigates uncertainties related to GCMs, GCM initial conditions and representative concentration pathways (RCPs) and their sensitivity to the selection of GCM runs in order to quantify the impact of climate change on extreme precipitation and intensity/duration/frequency statistics. The results from a large ensemble of 140 CMIP5 GCM runs including 15 GCMs, 3-10 GCM initial conditions and 4 RCPs are analysed. Albeit the choice of GCM is the major contributor (up to 65% for some cases) to intense precipitation change uncertainty for all return periods (1 year, 10 years) and aggregation levels (1-, 5-, 10-, 15-and 30-day), uncertainties related to the GCM initial conditions and RCPs of up to 38 and 23%, respectively, are found in some cases. The sensitivity analysis reveals that the GCM, RCP and GCM initial condition uncertainties are greatly influenced by the set of climate model runs considered, especially for more extreme precipitation at finer time scales.