Variational data assimilation in the tropics using precipitation data part I: Column model

Summary This paper describes initial effort in the development of a four-dimensional variational data assimilation (4D-Var) in the tropics using precipitation data derived from remote sensing. The method of 4D-Var using precipitation data is formulated, and modifications to the parameterization schemes of moist processes to remove zeroth-order discontinuities are described. Variational data assimilation experiments are carried out using a column model to investigate the problems caused by discontinuities in parameterization schemes and assess the impact of assimilating precipitation data in the tropics.It is found that variational data assimilation with discontinuous parameterization schemes exhibits large fluctuations during the minimization process, slow convergence rates, and large analysis errors. The fluctuations become much more serious when precipitation data is assimilated. Precipitation data is very useful to estimate divergence in the tropics, provided that the temporal resolution of the data is sufficiently high. However, its impact on the analysis of temperature and moisture is not clear in the column model assimilation experiments, possibly due to the absence of horizontal advection.