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

Two test models were developed: a one-dimensional and 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 conditions to a satisfactory degree when observations of all the model prognostic variables were used. Greater overdetermination of the degrees of freedom (the initial condition being retrieved) resulted in greater improvement of the errors in the observations of the initial conditions, but at a rapid increase in computational cost. Experiments where only some of the prognostic variables were observed also improved the initial conditions, but at a greater cost. To substantially improve the first guess of the field not observed, some spot observations are needed. -from Authors