High resolution forecast of heavy precipitation with Lokal Modell: analysis of two case studies in the Alpine area

Northern Italy is frequently affected by severe precipitation conditions often inducing flood events with associated loss of properties, damages and casualties. The capability of correctly forecast these events, strongly required for an efficient support to civil protection actions, is still nowadays a challenge. This difficulty is also related with the complex structure of the precipitation field in the Alpine area and, more generally, over the Italian territory. Recently a new generation of non-hydrostatic meteorological models, suitable to be used at very high spatial resolution, has been developed. <P style='line-height: 20px;'> In this paper the performance of the non-hydrostatic Lokal Modell developed by the COSMO Consortium, is analysed with regard to a couple of intense precipitation events occurred in the Piemonte region in Northern Italy. These events were selected among the reference cases of the Hydroptimet/INTERREG IIIB project. <P style='line-height: 20px;'> LM run at the operational resolution of 7km provides a good forecast of the general rain structure, with an unsatisfactory representation of the precipitation distribution across the mountain ranges. It is shown that the inclusion of the new prognostic equations for cloud ice, rain and snow produces a remarkable improvement, reducing the precipitation in the upwind side and extending the intense rainfall area to the downwind side. The unrealistic maxima are decreased towards observed values. The use of very high horizontal resolution (2.8 km) improves the general shape of the precipitation field in the flat area of the Piemonte region but, keeping active the moist convection scheme, sparse and more intense rainfall peaks are produced. When convective precipitation is not parametrised but explicitly represented by the model, this negative effect is removed

Performance of the ARPA-SMR limited-area ensemble prediction system: two flood cases

The performance of the ARPA-SMR Limited-area Ensemble Prediction System (LEPS), generated by nesting a limited-area model on selected members of the ECMWF targeted ensemble, is evaluated for two flood events that occurred during September 1992. The predictability of the events is studied for forecast times ranging from 2 to 4 days. The extent to which floods localised in time and space can be forecast at high resolution in probabilistic terms was investigated. Rainfall probability maps generated by both LEPS and ECMWF targeted ensembles are compared for different precipitation thresholds in order to assess the impact of enhanced resolution. At all considered forecast ranges, LEPS performs better, providing a more accurate description of the event with respect to the spatio-temporal location, as well as its intensity. In both flood cases, LEPS probability maps turn out to be a very valuable tool to assist forecasters to issue flood alerts at different forecast ranges. It is also shown that at the shortest forecast range, the deterministic prediction provided by the limited area model, when run in a higher-resolution configuration, provides a very accurate rainfall pattern and a good quantitative estimate of the total rainfall deployed in the flooded regions

Data assimilation of radar reflectivity volumes in a LETKF scheme

Quantitative precipitation forecast (QPF) is still a challenge for numerical weather prediction (NWP), despite the continuous improvement of models and data assimilation systems. In this regard, the assimilation of radar reflectivity volumes should be beneficial, since the accuracy of analysis is the element that most affects short-term QPFs. Up to now, few attempts have been made to assimilate these observations in an operational set-up, due to the large amount of computational resources needed and due to several open issues, like the rise of imbalances in the analyses and the estimation of the observational error. In this work, we evaluate the impact of the assimilation of radar reflectivity volumes employing a local ensemble transform Kalman filter (LETKF), implemented for the convection-permitting model of the COnsortium for Small-scale MOdelling (COSMO). A 4-day test case on February 2017 is considered and the verification of QPFs is performed using the fractions skill score (FSS) and the SAL technique, an object-based method which allows one to decompose the error in precipitation fields in terms of structure (S), amplitude (A) and location (L). Results obtained assimilating both conventional data and radar reflectivity volumes are compared to those of the operational system of the Hydro-Meteo-Climate Service of the Emilia-Romagna Region (Arpae-SIMC), in which only conventional observations are employed and latent heat nudging (LHN) is applied using surface rainfall intensity (SRI) estimated from the Italian radar network data. The impact of assimilating reflectivity volumes using LETKF in combination or not with LHN is assessed. Furthermore, some sensitivity tests are performed to evaluate the effects of the length of the assimilation window and of the reflectivity observational error (roe). Moreover, balance issues are assessed in terms of kinetic energy spectra and providing some examples of how these affect prognostic fields. Results show that the assimilation of reflectivity volumes has a positive impact on QPF accuracy in the first few hours of forecast, both when it is combined with LHN or not. The improvement is further slightly enhanced when only observations collected close to the analysis time are assimilated, while the shortening of cycle length worsens QPF accuracy. Finally, the employment of too small a value of roe introduces imbalances into the analyses, resulting in a severe degradation of forecast accuracy, especially when very short assimilation cycles are used.</p

The Soverato flood in Southern Italy: performance of global and limited-area ensemble forecasts

The predictability of the flood event affecting Soverato (Southern Italy) in September 2000 is investigated by considering three different configurations of ECMWF ensemble: the operational Ensemble Prediction System (EPS), the targeted EPS and a high-resolution version of EPS. For each configuration, three successive runs of ECMWF ensemble with the same verification time are grouped together so as to generate a highly-populated &quot;super-ensemble&quot;. Then, five members are selected from the super-ensemble and used to provide initial and boundary conditions for the integrations with a limited-area model, whose runs generate a Limited-area Ensemble Prediction System (LEPS). The relative impact of targeting the initial perturbations against increasing the horizontal resolution is assessed for the global ensembles as well as for the properties transferred to LEPS integrations, the attention being focussed on the probabilistic prediction of rainfall over a localised area. At the 108, 84 and 60- hour forecast ranges, the overall performance of the global ensembles is not particularly accurate and the best results are obtained by the high-resolution version of EPS. The LEPS performance is very satisfactory in all configurations and the rainfall maps show probability peaks in the correct regions. LEPS products would have been of great assistance to issue flood risk alerts on the basis of limited-area ensemble forecasts. For the 60-hour forecast range, the sensitivity of the results to the LEPS ensemble size is discussed by comparing a 5-member against a 51-member LEPS, where the limited-area model is nested on all EPS members. Little sensitivity is found as concerns the detection of the regions most likely affected by heavy precipitation, the probability peaks being approximately the same in both configurations

Provision of boundary conditions for a convection-permitting ensemble: comparison of two different approaches

The current resolution of the operational global models favours the possibility of driving convection-permitting limited-area model (LAM) simulations directly, sparing the necessity for an intermediate step with a coarser-resolution LAM. Though the resolution of global ensemble systems is generally lower than that of deterministic ones, it is also possible to consider this opportunity in the field of ensemble forecasting. The aim of this paper is to investigate the effect of this choice for driving a convection-permitting ensemble based on the COSMO model, for a specific application, namely the forecast of intense autumn precipitation events over Italy. The impact of the direct nesting in the ECMWF global ensemble is compared to a two-step nesting, which makes use of a LAM ensemble system with parametrised convection. Results show that the variability introduced in the geopotential field by the direct nesting is usually contained within the uncertainty described by the standard ensemble, and differences between pairs of members following different nesting approaches are generally smaller than the ensemble error, computed with respect to analysis. The relation between spread and error is even improved by the direct nesting approach. In terms of precipitation, it is found that the forecasts issued by members with different nesting approaches generally have differences at spatial scales between 16 and 180 km, depending on the case, hence not negligible. Nevertheless, the skill of the LAM ensemble precipitation forecasts, evaluated by means of an objective verification, is comparable. Therefore, the overall quality of the 2.8 km ensemble for the specific application is not deteriorated by the provision of lower resolution lateral boundary conditions directly from the global ensemble

A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

International audienceThe precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF), conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast. The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines). These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines. The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing) for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision

Overview of the first HyMeX Special Observation Period over Italy: observations and model results

Abstract. The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19)

Quantifying the discharge forecast uncertainty by different approaches to probabilistic quantitative precipitation forecast

International audienceA probabilistic approach to flood prediction over the Reno river basin, a medium-sized catchment in Northern Italy, has been tested using two different meteorological ensemble systems. The future precipitation scenarios are provided either by an analogue-based technique (statistical approach) or by a limited-area ensemble prediction system (dynamical approach), then used as different inputs to a distributed rainfall-runoff model. The ensemble of possible future flows so generated allows to convey a quantification of uncertainty about the discharge forecast. The probabilistic discharge forecasts, based on the precipitation forecast provided by the two ensembles, are then compared to the deterministic one obtained by the rainfall-runoff model fed on precipitation input provided by a non-hydrostatic meteorological model, run at 7km of horizontal resolution. For this case study, the dynamical approach appears to be more feasible in providing useful discharge ensemble forecast than the statistical one, because the observed large spread among members obtained with the analogue method makes difficult to issue real-time flood warnings