Page 1© Crown copyright 2004 Development of a stochastic precipitation nowcast scheme for flood forecasting and warning Clive Pierce 1, Alan Seed 2, Neill Bowler 3 1. Met Office, Joint Centre for Hydro-Meteorological Research, Wallingford, Oxfordshire, UK, OX10 8BB 2. Cooperative Research Centre for Catchment Hydrology, Bureau of Meteorology, Melbourne, Australia 3. Met Office, FitzRoy Road, Exeter, Devon, UK, EX1 3PB

Page 2© Crown copyright 2004 Overview  A stochastic QPN scheme - STEPS  Overview of the Short Term Ensemble Prediction System  Cascade modelling framework  STEPS cascade model  Uncertainties in advection & Lagrangian temporal evolution  Formulation of STEPS  Towards stochastic fluvial forecasting  Propagating uncertainty in QPNs through a rainfall-run-off model  Plans

Page 3© Crown copyright 2004 Short Term Ensemble Prediction System  Model design  Cascade framework (Lovejoy et al., 1996; Seed, 2003) to model dynamic scaling behaviour  merging extrapolation nowcasts with NWP forecast  Sources of uncertainty / error  diagnosed velocity fields (Bowler et al., 2004)  Lagrangian temporal evolution  NWP forecast  initial state  Forecast evolution  blends extrapolation, NWP and noise cascades  stochastic noise  replaces extrapolated features beyond their life times  introduces features unresolved by NWP  ensemble produced

Page 4© Crown copyright 2004  Radar based precipitation field  2-D FFT  Bandpass filter per pixel, k=1,8  Inverse transform  Additive cascade  Normalise X k (t)  Based upon S-PROG cascade - Seed (2003) STEPS cascade model

Page 5© Crown copyright 2004 Cascade decomposition km km64-32 km km16-8 km4-2 km8-4 km courtesy of Alan Seed, Bureau of Meteorology, Australia

Page 6© Crown copyright 2004 Uncertainty in the extrapolation nowcast  Uncertainty in field evolution  Modelled in Lagrangian reference frame  Noise replaces extrapolated features beyond predicted life time   k,i,j = temporally independent noise cascade   Uncertainty in advection velocities  Add perturbation to velocities

Page 7© Crown copyright 2004 Formulation of STEPS  A blend of three cascades  Extrapolation  Noise  NWP  Weights assigned according to skill of extrapolation and NWP components  Advection velocities  blend perturbed velocity, e with NWP diagnosed velocity, m

Page 8© Crown copyright 2004 STEPS - products  Ensemble members - T+15 minutes

Page 9© Crown copyright 2004  Probability of precipitation STEPS - products

Page 10© Crown copyright 2004 Towards stochastic fluvial flood forecasting and warning  Uncertainty in rainfall input dominates (Moore, 2002)  Ignore errors in rainfall-runoff model  PDF of river flow from PDF of rain accumulation  Underestimates total uncertainty (Krzyztofowicz, 2001)  Cost-loss decision making model (Mylne, 2002)

Page 11© Crown copyright 2004 Flow forecast ensembles courtesy of Bob Moore, Centre for Ecology and Hydrology, UK

Page 12© Crown copyright 2004 Plans  STEPS operational trial in the UK and Australia  starts autumn 2005  pdf s of rain accumulation and river flow (PDM – Moore, 1985)  cost-loss model (Mylne, 2002) for pluvial & fluvial flood warning  verification of deterministic and probabilistic forecasts

Page 13© Crown copyright 2004 Thank you