Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project

Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project

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 pr...

Full description

Bibliographic Details
Main Authors: Sarah L. Dance, Susan P. Ballard, Ross N. Bannister, Peter Clark, Hannah L. Cloke, Timothy Darlington, David L. A. Flack, Suzanne L. Gray, Lee Hawkness-Smith, Nawal Husnoo, Anthony J. Illingworth, Graeme A. Kelly, Humphrey W. Lean, Dingmin Li, Nancy K. Nichols, John C. Nicol, Andrew Oxley, Robert S. Plant, Nigel M. Roberts, Ian Roulstone, David Simonin, Robert J. Thompson, Joanne A. Waller
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Atmosphere
Subjects:
flooding
convection
intense rainfall
radar reflectivity
radar refractivity
Doppler radar winds
data assimilation
observation uncertainty
initial condition uncertainty
predictability
Online Access:http://www.mdpi.com/2073-4433/10/3/125

Similar Items

Similar Items