In this paper we introduce a general downscaling framework and apply it to L band microwave radiobrightness temperature fields retrieved from electronically scanned thinned array radiometer (ESTAR). The gist of the downscaling scheme presented in this paper is the statistical characterization of scale-invariant properties of the wavelet coefficients or fluctuations from long memory 1/f processes. We test the proposed downscaling framework with the radiobrightness temperature images collected during the Southern Great Plains hydrology experiment of 1997. We produce realizations of radiobrightness temperature at 800-m resolution given a mean-area value at approximately 30-km resolution (the near-future expected operational scale). The results obtained evince that the proposed downscaling methodology is capable of accurately preserving the variability and overall structure of spatial dependence of the observed radiobrightness temperature fields.