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On the role of domain size and resolution in the simulations with the HIRHAM region climate model
On the role of domain size and resolution in the simulations with the HIRHAM region climate model
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On the role of domain size and resolution in the simulations with the HIRHAM region climate model
On the role of domain size and resolution in the simulations with the HIRHAM region climate model

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On the role of domain size and resolution in the simulations with the HIRHAM region climate model
On the role of domain size and resolution in the simulations with the HIRHAM region climate model
Journal Article

On the role of domain size and resolution in the simulations with the HIRHAM region climate model

2013
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Overview
We investigate the simulated temperature and precipitation of the HIRHAM regional climate model using systematic variations in domain size, resolution and detailed location in a total of eight simulations. HIRHAM was forced by ERA-Interim boundary data and the simulations focused on higher resolutions in the range of 5.5–12 km. HIRHAM outputs of seasonal precipitation and temperature were assessed by calculating distributed model errors against a higher resolution data set covering Denmark and a 0.25° resolution data set covering Europe. Furthermore the simulations were statistically tested against the Danish data set using bootstrap statistics. The results from the distributed validation of precipitation showed lower errors for the winter (DJF) season compared to the spring (MAM), fall (SON) and, in particular, summer (JJA) seasons for both validation data sets. For temperature, the pattern was in the opposite direction, with the lowest errors occurring for the JJA season. These seasonal patterns between precipitation and temperature are seen in the bootstrap analysis. It also showed that using a 4,000 × 2,800 km simulation with an 11 km resolution produced the highest significance levels. Also, the temperature errors were more highly significant than precipitation. In similarly sized domains, 12 of 16 combinations of variables, observation validation data and seasons showed better results for the highest resolution domain, but generally the most significant improvements were seen when varying the domain size.