A scheme to assimilate "no rain" observations from Doppler radar

However, low-reflectivity (or so-called no rain) echoes have often been ignored or not effectively used in radar data assimilation schemes. In this paper, a scheme to assimilate no-rain radar observations is described within the framework of the Weather Research and Forecasting Model's three-dimensional variational data assimilation (3DVar) system, and its impact on precipitation forecasts is demonstrated.

The key feature of the scheme is a neighborhood-based approach to adjusting water vapor when a grid point is deemed as no rain. The performance of the scheme is first examined using a severe convective case in the Front Range of the Colorado Rocky Mountains and then verified by running the 3DVar system in the same region, with and without the no-rain assimilation scheme for 68 days and 3-hourly rapid update cycles. It is shown that the no-rain data assimilation method reduces the bias and false alarm ratio of precipitation over its counterpart without that assimilation.