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47<br />

Evaluation of dynamical downscaling of the East Asian regional climate<br />

using the HadGEM3-RA: Summer monsoon of 1997 and 1998<br />

Johan Lee 1 , Suhee Park 1 , Wilfran Moufouma-Okia 2 , David Hassell 2 , Richard Jones 2 , Hyun-Suk Kang 1 ,<br />

Young-Hwa Byun 1 , and Won-Tae Kwon 1<br />

1 National Institute of Meteorological Research/Korea Meteorological Administration, Seoul, Republic of Korea,<br />

Johan.lee@kma.go.kr, 2 Met Office Hadley Centre, Exeter, UK<br />

1. Introduction<br />

The HadGEM3-RA is a regional atmospheric model based<br />

on the global atmospheric model of the Met Office Hadley<br />

Centre (MOHC). Korea Meteorological Administration<br />

(KMA) has a plan to adopt this model for dynamical<br />

downscaling from seasonal to decadal scales over the East<br />

Asian region according to the collaboration agreement<br />

between MOHC and KMA.<br />

As the first stage of this effort, the performance of the<br />

HadGEM3-RA for the East Asian summer monsoon is<br />

investigated. The East Asian summer monsoon is the most<br />

prominent feature in the East Asian region climate and a<br />

distinct component of the Asian summer monsoon system.<br />

Therefore, it is important to examine the model’s capability<br />

to simulate the East Asian summer monsoon before utilizing<br />

the model for downscaling for longer time scales over the<br />

East Asian region.<br />

In this paper, we will show a preliminary evaluation of its<br />

performance for the East Asian summer monsoon.<br />

2. Experiment design<br />

The model domain is the East Asian monsoon region<br />

including Korean Peninsula, East China, Mongolia, and<br />

Japan. Number of grid points are 190 (in west-east) by 158<br />

(in north-south) and horizontal resolution is selected to be<br />

0.22 degree, about 25 km. The buffer zone for lateral<br />

boundary conditions is 8 grids for each direction.<br />

Configuration of HadGEM3-RA for the East Asian region is<br />

almost the same as that of the HadGEM3-A, except that the<br />

dynamic settings are taken from the operational limited area<br />

model. Dynamics core and physical packages are described<br />

in Davies et al. (2005) and Martin et al. (2006), respectively.<br />

Atmospheric initial conditions were obtained from the<br />

European Centre for Medium-Range Weather Forecasts<br />

(ECMWF) 40-year reanalysis (ERA40) data. Lateral<br />

boundary conditions to drive HadGEM3-RA were derived<br />

from the 6-hourly data. Sea surface temperature and sea ice<br />

were prescribed by Atmospheric Model Inter-comparison<br />

Project (AMIP) II data.<br />

We selected two summer seasons to examine the model’s<br />

capability to simulate the East Asian summer monsoon and<br />

its interannual variation. The model integration periods are 3<br />

months from 0000 UTC 1 June 1997 and 1998, respectively.<br />

Typical characteristics of the East Asian summer are heavy<br />

rainfall from June to July and heat waves from late July to<br />

August. The two selected summers represented extreme<br />

climatic events which were opposite extremes in terms of<br />

precipitation. In summer of 1997, there were drought and<br />

heat waves in North China. In the other hand, there were<br />

abnormal heavy rains in summer of 1998 which had caused<br />

severe flooding in the Yangtze River valley and northeast<br />

China and record-breaking daily precipitations over the<br />

Korean Peninsula. Therefore, the model’s capability to<br />

capture interannual variability of the summer monsoon can<br />

be evaluated by comparing the simulations of 1998 and<br />

1997.<br />

3. Results and discussions<br />

Figure 1 shows observed and simulated precipitations for<br />

summer of 1998. As mentioned above, East Asia<br />

experienced severe heavy rainfall in summer of 1998. In<br />

Fig. 1a, there are intense rainbands over central China<br />

around the Yangtze River basin, the Korean Peninsula,<br />

and Japan. On the contrary the major rainband is weaker<br />

and shifted southward (not shown) in 1997. Therefore, in<br />

the difference between 1998 and 1997, positive anomalies<br />

occur in central China, Korea, and the northwest Pacific<br />

Ocean, and a negative anomaly in south China and Taiwan<br />

(Fig.1b). HadGEM3-RA reproduces well the observed<br />

features of both summers in terms of the distribution of<br />

seasonal precipitation. The pattern correlation coefficients<br />

are 0.53 and 0.61 for 1998 and 1997, respectively, and the<br />

model reproduces well the anomaly from 1998 to 1997<br />

(Table 1). In Fig. 2b, the rainfall deficit over south China<br />

and its surplus across central China and the Korean<br />

Peninsula are distinct as in the observations. However, the<br />

HadGEM3-RA tends to overestimate the intensity of<br />

precipitations. Simulated precipitations of 1998 and 1997<br />

are greater than observations and wet biases are 66.5% and<br />

47.9%, respectively (Table 1).<br />

Simulations of surface air temperature are better than<br />

those of precipitation. The pattern correlations are 0.96 for<br />

both summers (Table 1) with the distribution and<br />

magnitude of surface air temperature very close to<br />

observations (not shown). In addition, the features of 1998<br />

and 1997 anomalies are well captured, e.g. the cold<br />

anomaly in north China and warm anomalies in south<br />

China and the north-eastern region of Asia. The simulated<br />

surface air temperature is generally warmer than<br />

observations with area averaged biases of 0.5 °C and 0.9<br />

°C respectively (Table 1).<br />

Table 1. Comparison of statistical values for<br />

precipitation and surface air temperature of<br />

observation and simulations. In case of biases of<br />

precipitation, the ratio (%) of bias to observation is<br />

presented in parentheses.<br />

Observed<br />

mean<br />

Simulated<br />

mean<br />

Bias<br />

Precipitation Temperature<br />

1998 1997 1998 1997<br />

5.27 4.35 21.0 21.4<br />

8.78 6.44 21.5 22.3<br />

3.51<br />

(66.5)<br />

2.09<br />

(47.9)<br />

0.5 0.9<br />

RMSE 4.32 2.66 1.0 1.3<br />

Pattern<br />

Correlation<br />

0.53 0.63 0.96 0.96

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