Permalink : http://hdl.handle.net/2115/83712

JaLCDOI : 10.14943/mem.fish.60.1

KEYWORDS : Front Detection;Sea Surface Temperature;Chlorophyll-a;Histogram-based Method;Scale-selective Frontal Pattern;Importance of Initial Smoothing;Scale Proportional to Window;Gaussian Filter;Median Filter

When a histogram-based method for front detection was applied to the sea surface temperature (SST) and chlorophyll-a (CHL) data by ‘Himawari’ and ‘Shikisai’ (GCOM-C) satellite, the obtained frontal patterns were scale-selective, corresponding to the window scales (W).　On this basis, the optimum initial smoothing condition as the data preprocessing was searched for, that maximizes the frontal edge point detection rate to the given W.　As the smoothing filter, the median filter (MF) and the Gaussian filter (GF) were used solely or co-used.　As the result, it was found that the frontal edge point detection rate was maximized when the original data were smoothed until the scale of about a half of W, that is, when the disturbances with the scales less than about a half of W were removed, for the low-latitude SST data of ‘Himawari’ with the co-use of MF and GF.　Namely, the optimum smoothing scale (D) that maximizes the frontal edge point detection rate is roughly proportional to W.　The mean values (Rm) of the ratio of D to W (R=D/W), averaged over the practical range of W for various data and regions, fall in a range 0.3 < Rm < 0.5.