Improved destriping of GOES images using finite impulse response filters

GOES data are known to be contaminated with stripes whose presence affects the usefulness of the data in quantitative studies. This article: 1) reviews the causes of the striping; 2) develops frequency domain and spatial domain finite impulse response (FIR) filters for minimizing the stripes in the data while simultaneously introducing minimum distortion into the filtered data; and 3) quantitatively compares the results obtained with these new filtering methods with those produced by traditional destriping methods (e.g., simple smoothing, moment matching, histogram matching). Results from 81 GOES scenes show that a finite impulse response filter (i.e., target filter), implemented in either the spatial or Fourier domain, is superior to all other methods evaluated. The importance of proper destriping of GOES data for both accurate cloud detection and radiative flux computations also is demonstrated. The sensitivity of histogram matching to the choice of reference state is evaluated, and a way to minimize the sensitivity is presented.