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STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP
Abstract
An ensemble‐based probabilistic precipitation forecasting scheme has been developed that blends an extrapolation nowcast with a downscaled NWP forecast, known as STEPS: Short‐Term Ensemble Prediction System. The uncertainties in the motion and evolution of radar‐inferred precipitation fields are quantified, and the uncertainty in the evolution of the precipitation pattern is shown to be the more important. The use of ensembles allows the scheme to be used for applications that require forecasts of the probability density function of areal and temporal averages of precipitation, such as fluvial flood forecasting—a capability that has not been provided by previous probabilistic precipitation nowcast schemes. The output from a NWP forecast model is downscaled so that the small scales not represented accurately by the model are injected into the forecast using stochastic noise. This allows the scheme to better represent the distribution of precipitation rate at spatial scales finer than those adequately resolved by operational NWP. The performance of the scheme has been assessed over the month of March 2003. Performance evaluation statistics show that the scheme possesses predictive skill at lead times in excess of six hours. © Crown copyright, 2006.
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Verification of forecasts expressed in terms of probability
BRIER, G. W. (1950) · Monthly Weather Review · doi:10.1175/1520-0493(1950)078%3c0001:vofeit%3e2.0.co;2 · cited 1×
“(b) Brier skill score The Brier skill score (Brier 1950) is a useful measure for determining the skill of a probabilistic forecast.”
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Cited by
Skilful precipitation nowcasting using deep generative models of radar
Ravuri, S., Lenc, K., Willson, M., Kangin, D., Lam, R., Mirowski, P., Fitzsimons, M., Athanassiadou, M., Kashem, S., Madge, S., et al. (2021) · Nature · doi:10.1038/s41586-021-03854-z · Cited by 1,024
Fletcher, T. D., Andrieu, H., & Hamel, P. (2013) · Advances in Water Resources · doi:10.1016/j.advwatres.2012.09.001 · Cited by 1,015
A review of advances in flash flood forecasting
Hapuarachchi, H. A. P., Wang, Q. J., & Pagano, T. C. (2011) · Hydrological Processes · doi:10.1002/hyp.8040 · Cited by 560
Operational early warning systems for water-related hazards in Europe
Alfieri, L., Salamon, P., Pappenberger, F., Wetterhall, F., & Thielen, J. (2012) · Environmental Science & Policy · doi:10.1016/j.envsci.2012.01.008 · Cited by 323
Forecast verification: Current status and future directions
Casati, B., Wilson, L. J., Stephenson, D. B., Nurmi, P., Ghelli, A., Pocernich, M., Damrath, U., Ebert, E. E., Brown, B. G., & Mason, S. (2008) · Meteorological Applications · doi:10.1002/met.52 · Cited by 306
Metadata
- Authors
- Bowler, N. E., Pierce, C. E., & Seed, A. W.
- Venue
- Quarterly Journal of the Royal Meteorological Society
- Publisher
- Wiley
- Published
- 2006-10
- Volume
- 132
- Issue
- 620
- Pages
- 2127-2155
- ISSN
- 0035-9009 (ISSN-L)
- 1477-870X
- OpenAlex
- W2114473878
- Cited by
- 429
- References
- 1
- FWCI
- 3.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bowler, N. E., Pierce, C. E., & Seed, A. W. (2006). STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1256/qj.04.100
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