Flood forecasting using medium-range probabilistic weather prediction

Long-range Weather Forecasting

Probabilistic Weather Forecasting in R

Abstract This article describes two R packages for probabilistic weather forecasting, ensembleBMA, which offers ensemble postprocessing via Bayesian model averaging (BMA), and ProbForecastGOP, which implements the geostatistical output perturbation (GOP) method. BMA forecasting models use mixture distributions, in which each component corresponds to an ensemble member, and the form of the compo...

Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron MLP neural network. The MLP architecture was optimize...

Lecture Notes on Numerical Weather Prediction Predictability, Probabilistic Forecasting and Ensemble Prediction Systems

Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990’s in numerical centers around the world due to the increase of computation ability. One of the main purposes of numerical ensemble forecast tends to assimilate initial uncertainty (both observation and analysis errors) and forecast uncertainty (model errors) by applying either initial perturbation me...

Probabilistic Weather Forecasting for Winter Road Maintenance

Road maintenance is one of the main problems Departments of Transportation face during winter time. Anti-icing, i.e. applying chemicals to the road to prevent ice formation, is often used to keep the roads free of ice. Given the preventive nature of anti-icing, accurate predictions of road ice are needed. Currently, anti-icing decisions are usually based on deterministic weather forecasts. Howe...