Spectral Analysis of GCM Output using Digital Filtering Techniques

Complexity of climatic variables on time– spatial scales shows necessity of using efficient methods such as spectral analysis and digital filtering as a useful tool to study climate patterns. In this paper, spectral analysis has been employed to validate a GCM with observations over Iran. Precipitation values obtained from the 20C3M (run1) experiment of the GFDL general circulation model (CM2.1) and CPC Merged Analysis of Precipitation (CMAP) from NCEP .The daily maximum rainfall, daily minimum temperature, and seasonal variation of precipitation used in the period 1961-2010. In addition, some kind of low pass filter such as Hamming filter for smoothing the time series were investigated. Results, show that first, second , third harmonic amplitudes and phases of precipitation provide a useful source of comparison between model output and observational data.Also,results indicate that the method of harmonic analysis delineates regional boundaries of the various temperature and precipitation regimes in this region.But the GCM does not capture a significant amount of the regional detail in precipitation climatology when its results are decomposed by harmonic analysis