Interpolation is essential in radar data coordinate transformation and radar network process due to the polar coordinate storage of radar data. In order to improve the effect and observation ability of radar network, an interpolation method based on Fourier spectrum analysis ("Fourier interpolation method" for short) has been developed for weather radar echo imagery data. The principle of this method is based on fitting discrete radar-sampling points with Fourier spectrum analysis and then re-sampling for the purpose of interpolation. The algorithm is introduced by steps and cases like typhoon and heavy rain radar images detected by Fuzhou radar and Nanjing SA radar have been studied by comparing Fourier interpolation with bilinear interpolation method in processing radar echo image at low angle. Bilinear interpolation method could narrow the strong echo area because of its "average" process, but Fourier interpolation method can avoid this problem in a certain extent with spectral analysis and sampling properties. Fourier interpolation method can highlight the structural characteristics of strong echo area when processing cumuliform cloud echo derived from convective precipitation in a proper distance, and in the far distance it can interpolate the strong echo centers that low resolution radar cannot detect. Due to the fitting equation, in the strong echo area, the results of Fourier interpolation have a better consistency with true value (fitting degree R2 is more than 0.98; slope is 0.98; intercept is only 0.31 dBZ, closed to 0 dBZ), but the consistency between the bilinear interpolation and the true value is worse (fitting degree R2 is 0.94, the slope is only 0.79, intercept is more than 8.04 dBZ). Fourier interpolation method performs better than the commonly-used bilinear interpolation method in highlighting the structure characteristics of strong echoes in severe convective area and is conducive to showing some severe convective centers which cannot be detected because of the lower spatial resolution at long distance. Due to the large amount of calculation, further research is needed to shorten the calculation time.
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