Fitting Microphysical Observations of Nonsteady Convective Clouds to a Numerical Model: An Application of the Adjoint Technique of Data Assimilation to a Kinematic Model

Abstract Rapid advances in the quality and quantity of atmospheric observations have placed a demand for the development of techniques to assimilate these data sources into numerical forecasting models. Four-dimensional variational assimilation is a promising technique that has been applied to atmospheric and oceanic dynamical models, and to the retrieval of three-dimensional wind fields from single-Doppler radar observations. This study investigates the feasibility of using space–time variational assimilation for a complex discontinuous numerical model including cloud physics. Two test models were developed: a one-dimensional and a two-dimensional liquid physics kinematic microphysical model. These models were used in identical-twin experiments, with observations taken intermittently. Small random errors were introduced into the observations. The retrieval runs were initialized with a large perturbation of the observation run initial conditions. The models were able to retrieve the original initial condi...