Predictability of Precipitation from Continental Radar Images. Part V: Growth and Decay

Abstract

n a Lagrangian frame of reference, the accuracy of rainfall systems predicted by nowcasting algorithms can be improved by incorporating the growth and decay of the rainfall. The scale dependence of predictability of growth and decay of continental-scale precipitating systems is studied with the help of the U.S. national radar composites. The growth and decay of precipitating systems is estimated in a time interval τ by correcting the precipitation image for advection and rotation at time t + τ with respect to the precipitation image at time t and then subtracting the former from the latter. Results show that the two-dimensional correlation of growth and decay has an elliptical structure, indicating that growth and decay is nonisotropic. The probability density function of precipitation intensities and of growth and decay follows a Gaussian distribution. The scale-dependence analysis of growth and decay patterns indicates that the growth and decay of rainfall may be predictable up to about 2 h for scales larger than 250 km.