The Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection (FRANC) project undertook a series of studies to design and test efficient and effective ways of assimilating moisture information from observations that respect the intricate dynamical and physical relationships that operate in the atmosphere. The aim of this work was, if successful, that such new approaches would allow better use of cloud and rain affected observations than previously. Predicting convective rain is made harder by the fact that some events are inherently unpredictable, even with good data assimilation and models, due to their high sensitivity to even small errors in the initial conditions. Studies were also made to look at the dynamical reasons for the low predictability of such events using diagnostics derived from models and observations. To these ends this collection contains data from two of the studies within this project plus helical scan data from the Met Office's Wardon Hill radar utilised by the project team.
The two datasets from the project team cover ensemble member output from runs of the Met Office's Unified Model conducted to support the project and Doppler radar radial wind observations and associated observation-minus-model residuals from the Met Office UKV 3D Var assimilation scheme. Please see the individual datasets for additional information.
For further details of the FRANC project please also see Dance et al. (2019) article in the online resources linked to from this record: Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project.
Dataset supports the following projects:
|Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection (FRANC) Project|
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