A 3.5-Dimensional Variational Method for Doppler Radar Data Assimilation and Its Application to Phased-Array Radar Observations

Abstract EN

A 3.5-dimensional variational method is developed for Doppler radar data assimilation.

In this method, incremental analyses are performed in three steps to update the model state upon the background state provided by the model prediction.

First, radar radial-velocity observations from three consecutive volume scans are analyzed on the model grid.

The analyzed radial-velocity fields are then used in step 2 to produce incremental analyses for the vector velocity fields at two time levels between the three volume scans.

The analyzed vector velocity fields are used in step 3 to produce incremental analyses for the thermodynamic fields at the central time level accompanied by the adjustments in water vapor and hydrometeor mixing ratios based on radar reflectivity observations.

The finite element B-spline representations and recursive filter are used to reduce the dimension of the analysis space and enhance the computational efficiency.

The method is applied to a squall line case observed by the phased-array radar with rapid volume scans at the National Weather Radar Testbed and is shown to be effective in assimilating the phased-array radar observations and improve the prediction of the subsequent evolution of the squall line.