Uncertainty of lateral boundary conditions in a convection-permitting ensemble: a strategy of selection  for Mediterranean heavy precipitation events

Nuissier, Olivier; Joly, Bruno; Vié, Benoît; Ducrocq, Véronique

doi:10.5194/nhess-12-2993-2012

Cited by 34 publications

(44 citation statements)

References 39 publications

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“…It is scheduled for operational production for April 2017. In the experimental dataset used here, forecasts are initialized at 2100 UTC covering a forecast horizon of 45 h. Initial and lateral boundary conditions originate from the PEARP global ensemble model (Nuissier et al ., ; Bouttier et al ., ), and model uncertainties are represented by stochastic physics (Bouttier et al ., ) and surface perturbations (Bouttier et al ., ).…”

Section: Datamentioning

confidence: 97%

Short‐range probabilistic forecasting of convective risks for aviation based on a lagged‐average‐forecast ensemble approach

Osinski

Bouttier

2017

Meteorological Applications

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An hourly initialized numerical weather prediction model, AROME-NWC, optimized for nowcasting purposes was used in this study to predict the probabilities of occurrence of convective aviation risks by generating an ensemble of time-lagged forecasts. The objective is the prediction of echotop and reflectivity maximum based on simulated 3D radar reflectivity columns. Forecasts were postprocessed using an upscaling of the model output fields in order to account for uncertainties in horizontal positions. Simulated radar reflectivities were bias corrected using a quantile-to-quantile mapping resulting in an improvement of the ensemble performance. A lagged-average-forecast ensemble was then constructed in order to blend mesoscale deterministic and ensemble forecasts, using numerical weather prediction systems that will soon be available in real time. The probabilities of reflectivities predicted by the ensemble are shown to have objective value at thresholds that are meaningful for air traffic control. Possible applications for aviation management purposes are discussed.

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Section: Datamentioning

confidence: 97%

Short‐range probabilistic forecasting of convective risks for aviation based on a lagged‐average‐forecast ensemble approach

Osinski

Bouttier

2017

Meteorological Applications

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“…The AROME‐EPS ensemble set‐up is the following. The ensemble runs start daily at 1800 UTC and comprise seven ‘perturbed’ + one control ‘unperturbed’ member (eight members) up to 30 h forecast range. Lateral boundary conditions (LBCs) are provided by a subset of about seven members of the PEARP, selected according to the Nuissier et al () technique. The PEARP 35 member ensemble forecasts are classified by a complete‐linkage clustering technique.…”

Section: Description Of the Ensemble Experiments And Verification Scoresmentioning

confidence: 99%

Evaluation of two convection‐permitting ensemble systems in the HyMeX Special Observation Period (SOP1) framework

Nuissier

Marsigli

Vincendon

et al. 2016

Quart J Royal Meteoro Soc

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This study compares and evaluates two convection‐permitting ensemble systems based on Consortium for Small‐scale Modeling (COSMO) and Applications of Research to Operations at Mesoscale (AROME) models in the HyMeX framework. The performance of both AROME‐EPS and COSMO‐H2‐EPS (where EPS denotes Ensemble Prediction System) is assessed over the whole HyMeX special observation period SOP1. Afterwards, an analysis of the predictability of two heavy precipitation events observed during the intense observation period IOP16a of the first HyMeX special observation period SOP1 on 26 October 2012 is also undertaken. Ensemble discharge forecasts were carried out to reinforce the quantitative precipitation forecast evaluation. A probabilistic evaluation is conducted over a 53 day period of the HyMeX SOP1. AROME‐EPS has a more discriminating behaviour than COSMO‐H2‐EPS, especially when comparing both ensembles over a verification domain including a strong variability in precipitation events. AROME‐EPS still has slightly better reliability, but the statistical resolution is nearly the same for both convection‐permitting ensemble prediction systems (CPEPS). For the specific case of heavy precipitation occurring over the Var region (southeastern France), the fine‐scale surface precipitation prediction is strongly sensitive to the good behaviour of a surface low pressure simulated by the ensembles, focusing strong low‐level moisture towards Var. The convergence between strong moistened southerly low‐level inflow and northerly cold air blowing from the Po Valley is a key factor controlling the predictability of the heavy precipitation episode over the Liguria region (northwestern Italy). The two convection‐permitting ensembles, though different in their characteristics, exhibit a good amount of probabilistic skill in forecasting heavy precipitation at a relatively high spatial and temporal resolution. Therefore they can be regarded as promising tools for operational forecasts.

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“…Gebhardt et al , ). Model and large‐scale boundary condition errors have been studied in several ensemble systems including AROME‐EPS; although their current representation is far from perfect, they are not the focus of this article, and we shall use the perturbation methods already documented by Bouttier et al () for the model errors, and Nuissier et al () for the large‐scale boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX

Bouttier

Raynaud

Nuissier

et al. 2015

Quart J Royal Meteoro Soc

101

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The AROME-EPS convection-permitting ensemble prediction system has been evaluated over the HyMeX-SOP1 period. Objective verification scores are computed using dense observing networks prepared for the HyMeX experiment. In probabilistic terms, the AROME-EPS ensemble performs better than the AROME-France deterministic prediction system, and a state-of-the-art ensemble at a lower resolution. The strengths and weaknesses of AROME-EPS are discussed. Here, impact experiments are used to study perturbation schemes for the initial conditions and the model surface. Both have a significant effect on the ensemble performance. The interactions between the perturbations of lateral boundaries, initial conditions and surface perturbations are studied. The consistency between initial and lateral perturbations is found to be unimportant from a meteorological point of view. Ensemble data assimilation is not as effective as a simpler surface perturbation scheme, and it is noted that both approaches could be usefully combined.

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Uncertainty of lateral boundary conditions in a convection-permitting ensemble: a strategy of selection for Mediterranean heavy precipitation events

Cited by 34 publications

References 39 publications

Short‐range probabilistic forecasting of convective risks for aviation based on a lagged‐average‐forecast ensemble approach

Short‐range probabilistic forecasting of convective risks for aviation based on a lagged‐average‐forecast ensemble approach

Evaluation of two convection‐permitting ensemble systems in the HyMeX Special Observation Period (SOP1) framework

Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX

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