2019
DOI: 10.1002/joc.6323
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Evaluation of multi‐RCM high‐resolution hindcast over the CORDEX East Asia Phase II region: Mean, annual cycle and interannual variations

Abstract: Based on the Coordinated Regional Downscaling Experiment‐East Asia second phase (CORDEX‐EA‐II) with higher resolution, model results driven by ERA‐Interim reanalysis using WRF, RegCM4 and CCLM are evaluated against the observational datasets including CN05.1, CRU and GPCP during the period of 1989–2009. The results show that the RCMs have the capability to simulate the annual and seasonal mean surface air temperature and precipitation, however, some biases are produced. The biases are highly dependent on the g… Show more

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Cited by 41 publications
(35 citation statements)
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“…This dataset contains daily average, maximum and minimum temperature and precipitation in the period of 1961-2007. It has been widely used for model verification and evaluation (Yu et al, 2019).…”
Section: Observational Data and Model Datamentioning
confidence: 99%
See 2 more Smart Citations
“…This dataset contains daily average, maximum and minimum temperature and precipitation in the period of 1961-2007. It has been widely used for model verification and evaluation (Yu et al, 2019).…”
Section: Observational Data and Model Datamentioning
confidence: 99%
“…Due to the uncertainty of a single RCM, evident differences exist among different models, which has a great adverse effect on the projection of future climate changes. In order to reduce the uncertainty, multi-GCMs-driven RCM simulations and ensemble methods are adopted to obtain more reliable projections of extreme precipitation changes (Yu et al, 2019;Zhou et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Although the RCM's downscaling skill is strongly limited by the skill of its driving GCM (Racherla et al, 2012), the performance of the two RCMs is dependent on geophysical locations, RCM applied, and extreme indices (Hui et al, 2018a; Yu et al, 2019). In terms of spatial correlation of whole Eastern China, WRF shows advantages in the representation of V95p, R95t, and SDII while PRECIS works better for the number of wet days and CDD.…”
Section: Model Evaluationmentioning
confidence: 99%
“…Dynamic downscaling based on regional climate models (RCMs), which have high spatial resolution, finer surface parameters, and more complicated parameterization schemes, are widely adopted to study regional and local climate and extreme events (Bao et al, 2015; Bürger et al, 2013; Gao et al, 2012; Knutson et al, 2013; Pielke & Wilby, 2012; Singh et al, 2013; Tang et al, 2016; Yu et al, 2019; Zhai et al, 2005; Zou & Zhou et al, 2018; Zhou, 2013). Dynamic downscaling is of great predominance compared to GCM simulations in mean climate and extreme climate event and performs better over East Asia (Gao et al, 2002, 2008, 2012; Hui et al, 2018a; Lee et al, 2014; Park et al, 2016; Wang et al, 2012; Yu et al, 2014).…”
Section: Introductionmentioning
confidence: 99%