Steps Towards Ingesting Radar Estimated Refractivity Into Numerical Weather Prediction Models

Ingesting radar refractivity fields in the numerical weather prediction (NWP) models has the potential to improve the highly variable initial conditions of low-level moisture and temperature fields for storm-scale NWP models. But in order to quantitatively use radar refractivity fields in data assimilation, good knowledge on errors is required. We undertook the task of evaluating refractivity errors in three steps: 1) biases were understood and corrected such as those caused by the changes in vertical gradient of refractivity and the height difference between the radar and targets; 2) the observational error of refractivity was estimated based on the uncertainty in the phase measurements and data processing procedures; and 3) the representativeness of the refractivity measurement by radar was considered.

In parallel, we also considered how to use radar refractivity measurements outside the limited coverage of radar refractivity. At regional-model scale, the areal average of radar refractivity is more representative than any point measurement and provides an extremely accurate constraint for such models for a few model grid points. We investigated the extent with which radar refractivity from operational radar networks could contribute to the analysis of regional NWP model. Background error covariance of refractivity from ensemble regional model was examined, and it suggests that especially in areas with limited orography, refractivity measurements from a radar can help constraint the analysis of humidity up to ranges of a few hundred kilometers.