Regional climate modeling using regional climate models (RCMs) has matured over the past decade to enable meaningful utilization in a broad spectrum of applications. In this paper, the latest progress in regional climate modeling studies is reviewed, including RCM development, applications of RCMs to Challenges and potential directions of future research in this important area are discussed, with focus on those that have received less attention previously, such as the importance of ensemble simulations, further development and improvement of the regional climate modeling approach, modeling extreme climate events and sub-daily variation of clouds and precipitation, model evaluation and diagnostics, applications of RCMs to climate process studies and seasonal predictions, and development of regional earth system models.It is believed that with the demonstrated credibility of RCMs in reproducing not only monthly to seasonal mean climate and interannual variability, but also the extreme climate events when driven by good quality reanalysis and continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamical downscaling tool for providing the needed information for assessing climate change impacts, and seasonal climate predictions, and a powerful tool for improving our understanding of regional climate processes. Internationally coordinated efforts can be developed to further advance regional climate modeling studies. It is also recognized that since the final quality of the results from nested RCMs depends in part on the realism of the large-scale forcing provided by GCMs, the reduction of errors and improvement in physics parameterizations in both GCMs and RCMs remain a priority for the climate modeling community.

Phase one of the Regional Climate Model Intercomparison Project for Asia reveals the capacities of regional climate models (RCMs) for simulating the Asian monsoon climate and extreme events as well. (Mearns et al. 2001;Giorgi et al. 2001). At present, analysis of the coupled atmosphere-ocean GCM (AOGCM) simulations indicates that average biases at regional scales, when simulating present-day climate, are highly variable from region to region and across models. For example, Giorgi and Francisco (2000) find that temperature biases are typically within the range of ±4°C, but exceed ±5°C in some regions, particularly in the winter. They also find that precipitation biases are mostly between -40% and +80%, but exceed 100% in some regions. Thus, a high priority for climate research is to improve the downscaling of GCM climate change to regional scales so that potential impacts can be adequately assessed (Houghton et al. 1995(Houghton et al. , 2001 Simulating regional climate poses difficulties, such as capturing effects of forcing and circulation at the planetary, regional, and local scales, along with teleconnection effects of regional anomalies. These processes are characterized by a range of temporal variability scales and can be highly nonlinear. The East Asian summer monsoon is characterized by marked variability at seasonal, interannual, and interdecadal time scales (Fu and Zheng 1998). The uncertain timing of monsoon onset and the irregular pace of its seasonal, northward progression strongly influence water availability for agriculture and urban consumption (Tao and Chen 1987;Wu and Zhang 1998). Interannual changes, such as those linked with the ENSO cycle, affect the frequency of droughts, floods, and other weather extremes that occur during the summer monsoon (Fu and Teng 1993;Ju and Slingo 1995;Fasullo and Webster 2002). Finally, on decadal-to-century time scales, the rapidly growing economy and population of East Asia presents anthropogenic influences that may also alter monsoon behavior (Fu and Zheng 1998;Quan et al. 2003). However, coarse-resolution climate models generally fail to give satisfactory simulations of the East Asian monsoon (Lau and Yang 1996; Yu et al. 2000).To date, most studies of regional climate change over East Asia have used output of GCMs without applying any downscaling techniques (Hulme et al. 1992;Zhao and Wang 1994). However, a relatively high degree of uncertainty exists in the regional climate change information of East Asia from GCMs, which results from the scenario's construction, such as future emission variations and the GCMs' modeling of the climate responses to a given scenario. Several researchers have used RCMs for simulating the regional climate of East Asia. Many of these studies have shown that RCMs can simulate the spatial detail of monsoon climate better than GCMs (Liu et al. 1994(Liu et al. ,1996Fu et al. 1998;Lee and Suh 2000). However, multiyear simulations must be used to provide meaningful climate statistics and to identify significant model errors. Therefo...

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Abstract. This paper presents a 10-year (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)

In this study, the severe flood case over East Asia during the 1998 summer was simulated using a regional climate model (SNURCM) with 60 km horizontal resolution (EX60), and the model performance in reproducing the extreme climate events was evaluated. An experiment with higher horizontal resolution of 20 km (EX20) was also performed in order to assess the impact of increased resolution on precipitation simulation of the severe flood.The model reproduced the severe precipitation events occurring in central China in June. In EX60, the temporal and spatial variations of the abnormal Meiyu monsoon fronts, which were well observed were also simulated reasonably except in southern China. The area-averaged daily precipitation and surface air temperatures were underestimated, but their temporal evolutions were in good agreement with observation. In the higher resolution experiment (EX20), simulated downward solar radiation, latent heat flux and convective rain were increased in the major severe rain area over the Yangtze River Basin. The increased precipitation in EX20, which was attributed mainly to the increase of convective rain, resulted in the enhanced precipitation intensity, but only slightly affected total precipitation amounts. The improvement in the higher horizontal resolution simulation appeared in precipitation resulting, in particular, from increased convective activity due to increased latent heat flux at the surface. Nevertheless, the model had significant precipitation bias in some areas with disagreement between the simulated precipitation patterns and distribution, and the observations. The model also had surface air temperature bias resulting from cold biases of the land surface model. With horizontal resolution increased to 20 km, the convective and non-convective precipitation was increased for the late afternoon and early evening time, increasing the total precipitation slightly.

[1] This study examines simulated typhoon sensitivities to spectral nudging (SN) to investigate the effects on values added by regional climate models, which are not properly resolved by low-resolution global models. SN is suitably modified to mitigate its negative effects while maintaining the positive effects, and the effects of the modified SN are investigated through seasonal simulations. In the sensitivity experiments to nudging intervals of SN, the tracks of simulated typhoons are improved as the SN effect increases; however, the intensities of the simulated typhoons decrease due to the suppression of the typhoon developing process by SN. To avoid such suppression, SN is applied at intermittent intervals only when the deviation between the large-scale driving forcing and the model solution is large. In seasonal simulations, intermittent SN is applied for only 7% of the total time steps; however, this results in not only maintaining the large-scale features of monsoon circulation and precipitation corresponding to observations but also improving the intensification of mesoscale features by reducing the suppression.

A new scheme that can define three rainy seasons, and the hydrological summer monsoon in Korea, has been proposed, examined, and verified to be effective. In the scheme, the Available Water Resources Index (AWRI) that is the accumulated precipitation value in which daily reduction of water, and the duration of accumulation are taken into account quantitatively.With this scheme, the onset and ending dates of three rainy seasons are defined by such singularities as the smallest, the biggest, the minimum, and the maximum of the AWRI in a year. The intensities of these rainy seasons are defined by the value of the maximum AWRI, flood index, and drought index.The first rainy season (Bom-Changma) starts in early April, when the minimum value of the AWRI in a year appears, and when the mean southerly wind at 925 hPa level become stronger then that at the 500 hPa level, and ends at May 15. The second rainy season (Changma) starts in late June and ends at 16-20 July. The third rainy season (Kaul-Changma) starts at mid August, and ends at 3-5 September that has the maximum value of the AWRI in a year, and that is the last date of mean southerly wind at the 925 hPa level.Finally, the hydrological summer monsoon is proposed to be defined as the period of increasing water resources that is from the minimum to the maximum of the AWRI, from the onset of Bom-Changma till the end of Kaul-Changma. From a turning point of meridional wind system to the end of mean southerly wind in the low level atmosphere, and that is concurrent with the summer monsoon.

[1] In this study, the systematic errors in regional climate simulation of 28-year summer monsoon over East Asia and the western North Pacific (WNP) and the impact of the spectral nudging technique (SNT) on the reduction of the systematic errors are investigated. The experiment in which the SNT is not applied (the CLT run) has large systematic errors in seasonal mean climatology such as overestimated precipitation, weakened subtropical high, and enhanced low-level southwesterly over the subtropical WNP, while in the experiment using the SNT (the SP run) considerably smaller systematic errors are resulted. In the CTL run, the systematic error of simulated precipitation over the ocean increases significantly after mid-June, since the CTL run cannot reproduce the principal intraseasonal variation of summer monsoon precipitation. The SP run can appropriately capture the spatial distribution as well as temporal variation of the principal empirical orthogonal function mode, and therefore, the systematic error over the ocean does not increase after mid-June. The systematic error of simulated precipitation over the subtropical WNP in the CTL run results from the unreasonable positive feedback between precipitation and surface latent heat flux induced by the warm sea surface temperature anomaly. Since the SNT plays a role in decreasing the positive feedback by improving monsoon circulations, the SP run can considerably reduce the systematic errors of simulated precipitation as well as atmospheric fields over the subtropical WNP region.