Predictability of short-range forecasting: a multimodel approach

Abstract

A B S T R A C T Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).

Observational probability method to assess ensemble precipitation forecasts

“…• × 0.45 • , which is much coarser than the 0.25 Garc´ıa-Moya et al, 2011) has been developed at the AEMET and adopts a different approach from ECMWF to sample forecast uncertainty. The present study will not assess the differences in the way the sampling of uncertainty is carried out, but will solely assess the benefits of including observation uncertainty in the calculation of the verification scores.…”

Influence of targeted observations on short-term forecasts of high-impact weather events in the Mediterranean

“…However, there still exists significant space for improvement, especially in the forecast of high-impact weather. Two key sources underlie forecast errors: uncertainties in the initial conditions and the presence of inaccuracies in the forecast models (García-Moya et al, 2011).…”

“…Ensemble forecasting, a technique that runs a finite number of deterministic models to build such a PDF, has shown to be a valuable tool used in most operational centres (García-Moya et al, 2011).…”

Dynamic downscaling of the NCEP EPS forecast using the PROMES limited area model

“…model physics) should be addressed as well in order to create an efficient LAMEPS system. Possible directions for this future research would be: multi-analysis and multi-boundary method (as an example see García-Moya et al, 2011); multi-parameter and/or multi-parametrization method (Wang et al, 2011), or the application of stochastic physics (Buizza et al, 1999).…”

“…In the last decade, however, intensive research has started to apply the ensemble method in limited area forecasting as well (see e.g. Molteni et al, 2001;Marsigli et al, 2008;Gebhardt et al, 2008;Bowler et al, 2008;Frogner et al, 2006;Iversen et al, 2009;Hagel, 2010;García-Moya et al, 2011;or Wang et al, 2010 and.…”