Abstract
The FRANC project (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) has researched improvements in numerical weather prediction of convective rainfall via the reduction of initial condition uncertainty. This article provides an overview of the project’s achievements. We highlight new radar techniques: correcting for attenuation of the radar return; correction for beams that are over 90% blocked by trees or towers close to the radar; and direct assimilation of radar reflectivity and refractivity. We discuss the treatment of uncertainty in data assimilation: new methods for estimation of observation uncertainties with novel applications to Doppler radar winds, Atmospheric Motion Vectors, and satellite radiances; a new algorithm for implementation of spatially-correlated observation error statistics in operational data assimilation; and innovative treatment of moist processes in the background error covariance model. We present results indicating a link between the spatial predictability of convection and convective regimes, with potential to allow improved forecast interpretation. The research was carried out as a partnership between University researchers and the Met Office (UK). We discuss the benefits of this approach and the impact of our research, which has helped to improve operational forecasts for convective rainfall events.
Highlights
Brief periods of intense rainfall can lead to flooding with the potential to cause damage to property and to threaten lives
The dual polarisation technology upgrade to the radars was developed in-house by Met Office staff, which allowed for access and control over the hardware and signal processing and enabled some of the novel developments in the FRANC project [28]*
We found similar results in a study of the assimilation of Doppler radar winds into the Deutsche Wetterdienst (DWD) convection-permitting system [59]*
Summary
Brief periods of intense rainfall can lead to flooding with the potential to cause damage to property and to threaten lives. To improve the prediction of these events, more accurate forecasts of convective rainfall are needed, and these can be used to inform flood guidance and warning systems (e.g., [2]). This programme has the objective of reducing the risks of damage and loss of life by surface water and flash floods through improved identification, characterisation and prediction of interacting meteorological, hydrological and hydro-morphological processes that contribute to flooding associated with high intensity rainfall events.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
