David S. Richardson

Current status and future developments of the ECMWF Ensemble Prediction System

The two latest changes introduced during 1998 into the Ensemble Prediction System (EPS) operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) are described. The first change, the inclusion of instabilities growing during the data assimilation period in the generation of the EPS initial perturbations, increased the probability that the analysis lies inside the ensemble forecast range. The second change, the introduction of a simulation of random model errors due to parametrized physical processes, improved in particular the prediction of precipitation. The performance of the ECMWF Ensemble Prediction System from 1 May 1994 to 2 March 1999 is assessed using different statistical measures. Results indicate that the general performance of the EPS has been improving over the years. Finally, ongoing research projects on predictability issues developed either at ECMWF or at European research institutes in collaboration with ECMWF are discussed Copyright

Intercomparison of Global Model Precipitation Forecast Skill in 2010/11 Using the SEEPS Score

AbstractPrecipitation forecasts from five global numerical weather prediction (NWP) models are verified against rain gauge observations using the new stable equitable error in probability space (SEEPS) score. It is based on a 3 × 3 contingency table and measures the ability of a forecast to discriminate between “dry,” “light precipitation,” and “heavy precipitation.” In SEEPS, the threshold defining the boundary between the light and heavy categories varies systematically with precipitation climate. Results obtained for SEEPS are compared to those of more well-known scores, and are broken down with regard to individual contributions from the contingency table. It is found that differences in skill between the models are consistent for different scores, but are small compared to seasonal and geographical variations, which themselves can be largely ascribed to the varying prevalence of deep convection. Differences between the tropics and extratropics are quite pronounced. SEEPS scores at forecast day 1 in t...

ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

In winter, heavy precipitation and floods along the west coasts of mid-latitude continents are largely caused by intense water vapour transport (integrated vapour transport IVT) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts (ECMWF) Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialised in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

An Assessment of the ECMWF Extreme Forecast Index for Water Vapor Transport during Boreal Winter

AbstractEarly awareness of extreme precipitation can provide the time necessary to make adequate event preparations. At the European Centre for Medium-Range Weather Forecasts (ECMWF), one tool that condenses the forecast information from the Integrated Forecasting System ensemble (ENS) is the extreme forecast index (EFI), an index that highlights regions that are forecast to have potentially anomalous weather conditions compared to the local climate. This paper builds on previous findings by undertaking a global verification throughout the medium-range forecast horizon (out to 15 days) on the ability of the EFI for water vapor transport [integrated vapor transport (IVT)] and precipitation to capture extreme observed precipitation. Using the ECMWF ENS for winters 2015/16 and 2016/17 and daily surface precipitation observations, the relative operating characteristic is used to show that the IVT EFI is more skillful than the precipitation EFI in forecast week 2 over Europe and western North America. It is th...

Medium- and Extended-Range Ensemble Weather Forecasting

The chapter provides an overview of ensemble weather forecasting for the medium- and extended-range (days to weeks ahead). It reviews the methods used to account for uncertainties in the initial conditions and in the forecast models themselves. The chapter explores the challenges of making useful forecasts for the sub-seasonal timescale, beyond the typical limit for skilful day-to-day forecasts, and considers some of the sources of predictability such as the Madden-Julian oscillation (MJO) that make this possible. It then introduces some of the ensemble-based forecast products and concludes with a case study for a European heat wave that demonstrates how ensemble weather forecasts can be used to guide decision making for weather-dependent activities.