全球氣候模式(GCMs)對於局地的區域性天氣特徵受限於解析度不足而難以清楚呈現，但若是使用GCMs資料透過動力降尺度方式提供給區域模式，則較能解決GCMs無法解析區域和局地氣候變化的問題。然而區域模式由於長期積分下，區域模式的表現有著隨時間快速變差的情形，因此若是在區域模式中配合使用波譜納進法(Spectral Nudging)，則可能解決此問題。
本研究使用Weather Research and Forecasting (WRF) 模式，針對2009年冬季進行三個月的模擬，將Climate Forecast System Reanalysis (CFSR)解析度0.5°的資料進行動力降尺度，並分為三個部份進行討論。首先比較四種不同長時間積分方法對15公里解析度之長期模擬的表現。其次討論Spectral Nudging的敏感度測試。最後討論高解析度的5公里網域，不同的Spectral Nudging及側邊界資料來源區域氣候模擬的影響。
本論文的研究結果顯示，使用Spectral Nudging並加入水氣調整之積分方法不僅能維持大尺度流場，避免產生錯誤的高低壓，模擬的降雨分佈亦能顯著改善且較合理。而當Spectral Nudging納進波數越多時，大尺度流場較接近分析場，但小尺度特徵則遭壓抑，造成降雨量低估；使用Spectral Nudging進行區域氣候模擬，大尺度流場不會受到區域尺度擾動支影響，而有沒有考慮Spin-up對於降雨表現上並未有明顯差異。而高解析之內層網格之側邊界及Spectral Nudging的資料，若直接使用全球模式之再分析資料，不論降雨或其他變數的模擬表現都比較好，同時也可以較準確的模擬出溫度及氣壓的日夜變化。綜合而言，使用Spectral Nudging進行區域氣候模擬確能顯著減少區域尺度之擾動對大尺度流場的影響，而能模擬出較好之區域氣候特徵。

General circulation models (GCMs) are unable to represent local subgrid-scale features because of their coarse resolution. Thus, the nested regional climate modeling technique, also refer to as dynamical downscaling, which GCMs are used to provide the initial (ICs) and lateral meterological and surface boundary condition (LBCs), are developed to produce the regional-scale features. However, the simulation of Regional Climate Models (RCMs) tends to drive away from the driving field and the skill will damp rapidly with time. Through the spectral nudging, the RCMs can alleviate the problems.
Here, we use the Weather Research and Forecasting (WRF) model over East Asia to dynamically downscale the 0.5-degree Climate Forecast System Reanalysis (CFSR). We perform the three phase of experiments for the winter in 2009. In phase one, we compare the different downscaling skill with a grid spacing at 15km for climate, including the long- and short-term integration and long-term with spectral nudging; besides, we add the specific humidity in spectral nudging to improve the result of precipitation. In phase two, we discuss two sensitivity test of spectral nudging. In the last phase, we compare the dynamically downscaling between different information of LBCs and spectral nudging with a grid spacing at 5km for climate.
Compare to ERA interim, the downscaling simulation using the spectral nudging with additionally adding moisture not only can keep the large-scale pattern, but significantly improve the realistic result of precipitation in phase one. In phase two, though spectral nudging with more wavenumber can generate the more reasonable pattern, it constrains the feature at small scale and the precipitation will be underestimated because of immature system. Through the spectral nudging, the large-scale pattern can be handled, and the result of cold and warm start show the similar result. In the phase three, simulation with GCMs for information of LBCs and nudging produce the highest skill. The spectral nudging can generate realistic regional-scale climate information. In particular, spectral nudging which are configured to nudge moisture can revise the error to generate reasonable precipitation pattern that are not resolved by simply updating the LBCs as done traditionally.

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