Model skill measures in probabilistic regional climate projections for Ireland
Model skill measures in probabilistic regional climate projections for Ireland
复制标题
爱尔兰概率区域气候预测的模型技能测量
DOI：
10.3354/cr01140
复制
发表时间：
2013
期刊：
影响因子：
1.1
通讯作者：
J. Sweeney
中科院分区：
文献类型：
--
作者：
A. Foley;R. Fealy;J. Sweeney
在本研究中，使用了一系列区域气候模式进行检验
In the present study, a range of regional climate models have been used to test
approaches to Bayesian model averaging (BMA), particularly the quantification of model
weights/Bayesian priors. The results of skill assessments were used to inform probabilistic future
projections of Irish climate using a BMA approach in order to evaluate how different approaches
to skill assessment, based on representation of climate means, or of a large-scale driver (the NAO),
or a combination thereof, may influence the final climate projection. Results indicate that meansbased
skill assessments may not always provide a useful indication of model skill and that further
analyses are required to assess a model’s ability to simulate the dynamics of the climate system.
While this research illustrates that the use of metrics derived from the model predicted NAO
impacts on the regional projection, it also supports the inclusion of other large-scale model diagnostics.
When used to weight model projections to produce ensemble climate projections, the
choice of skill metric may have an impact on the shape of the probability distribution and the most
probable outcome of future climate predictions. The present study demonstrates that when working
with probabilistic outputs of ensemble climate modelling experiments, awareness of the
approaches used to evaluate models and the techniques used to combine them to formulate
ensemble projections are integral in enabling robust responses to the potential changes in climate
represented by models.