Assessment of Unforced Variability as a Source of Uncertainty in Regional Hydroclimate Simulations and Projections

嵌套区域气候模式（RCMs）是全球范围内用于生成气候变化预测和适合水文研究的尺度长期模拟的主要工具。需要资金来进行我的创新性非定向研究，以调查对评估区域气候预测和水资源管理模拟的不确定性至关重要的问题。一般的看法是，与排放情景或大气环流模型缺陷相关的不确定性相比，大气环流模型或区域环流模型内部变异性（IV）对总体不确定性的影响较小。然而，De Wit等人（2007年）指出，同一大气环流模式强迫的不同区域环流模式产生不同的平均季节降水和蒸发模式，Horton等人（2006年）发现，特定排放情景的模拟排放显示，驱动大气环流模式和驱动区域环流模式都引起了很大的变异性。这些研究表明，由相同的GCM强迫的RCM集合可以产生与不同GCM驱动的相同RCM产生的变化相同幅度的水相关变量的变化。最近，Musíc和Caya（准备中）表明，GCM IV对流域尺度径流不确定性的贡献可以与使用不同GCM引入的贡献一样大。Braun等人（2011年）表明，在流域尺度径流分析中，使用大区域的区域气候模型中的IV值可能接近GCM IV值。因此，在任何使用区域气候模型的水文研究中，都必须考虑到大气环流模型和区域气候模型的非强迫变率。所有上述研究都忽略了非强迫变异性的贡献。目前的建议是要估计的空间分布的非受迫变异及其相对贡献的整体不确定性。由Ouranos（在我的领导下）生成的集合，旨在解决这种非受迫变率分析，现在已经完成并可用。将使用最近可用的区域模拟集合对非受迫变率进行全面分析。

Nested Regional Climate Models (RCMs) are the main tool used worldwide to generate climate change projections and long simulations at scales suitable for hydrological studies. Funds to pursue my innovative non-directed research are required to investigate issues that are vital for the estimation of uncertainty in regional climate projections and simulations for water management. The general perception is that GCM or RCM internal variabilities (IV) are minor contributors to the overall uncertainty in comparison to uncertainty associated to emissions scenarios or to deficiencies in GCMs. However, De Wit et al. (2007) stated that different RCMs forced by the same GCM generate different mean seasonal precipitation and evaporation patterns and Horton et al. (2006) found that the simulated discharges for a given emissions scenario show large variability induced by both, the driving GCMs and the driven RCMs. These studies demonstrated that a RCM ensemble forced by the same GCM could generate variability in water related variables of the same magnitude as the variability produced by using the same RCM driven by different GCMs. Recently, Musíc and Caya (in preparation) showed that the GCM IV contribution to uncertainty in runoff at the watershed scale can be as large as the one introduced by using a different GCM. Braun et al. (2011) showed that the IV in RCM using large domains could reach values close the GCM IV in analysis of runoff made at the watershed scale. Therefore, the unforced variability in both GCMs and RCMs has to be taken into account in every hydrology studies using RCMs. All of the above studies neglected the contribution from the unforced variability. The present proposal wants to estimate the spatial distribution of the unforced variability and its relative contribution to the overall uncertainty. The ensemble generated by Ouranos (under my leadership) that was designed to address this unforced variability analysis is now complete and available. A complete analysis of the unforced variability will be conducted using this recently available ensemble of regional simulations.