Abstract.The demand for verification of numerical models is still very high, especially for what concerns the operational Quantitative Precipitation Forecast (QPF) used, among others, for evaluating the issuing of warnings to the population. In this study, a comparative verification of the QPF, predicted by two operational Limited Area Models (LAMs) for the Italian territory is presented: COSMO-I7 (developed in the framework of the COSMO Consortium) and WRF-NMM (developed at NOAA-NCEP). The observational dataset is the precipitation recorded by the high-resolution non-GTS rain gauges network of the National Civil Protection Department (NCPD) over two years (2007)(2008). Observed and forecasted precipitation have been treated as areal quantity (areal average of the values accumulated in 6 and 24 h periods) over the 102 "warning areas", defined by the NCPD both for administrative and hydrological purposes. Statistics are presented through a series of conventional indices (BIAS, POD and POFD) and, in addition, the Extreme Dependency Score (EDS) and the Base Rate (BS or 1-BS) have been used for keeping into account the vanishing of the indices as the events become rare. Results for long-period verification (the whole 2 yr) with increasing thresholds, seasonal trend (3 months period), diurnal error cycle and error maps, are presented. Results indicate that WRF has a general tendency of QPF overestimation for low thresholds and underestimation for higher ones, while COSMO-I7 tends to overestimate for all thresholds. Both models show a seasonal trend, with a bigger overestimation during summer and spring, while during autumn and winter the models tend to be more accurate.
Abstract. The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle). The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particu- Milelli (m.milelli@arpa.piemonte.it) larly improved by the new-data assimilation, but, on the other hand, it has not been destroyed. It has to be pointed out that a correct description of the planetary boundary layer, even only the lowest part of it, could be helpful to the forecasters and, in general, to the users, in order to deal with meteorological hazards such as snow (in particular snow/rain limit definition), or fog (description of temperature inversions).
Abstract. This study is embedded into a wider project named "Tackle deficiencies in Quantitative Precipitation Forecast (QPF)" in the framework of the COSMO (COnsortium for Small-scale MOdelling) community. In fact QPF is an important purpose of a numerical weather prediction model, for forecasters and customers. Unfortunately, precipitation is also a very difficult parameter to forecast quantitatively. This priority project aims at looking into the COSMO Model deficiencies concerning QPF by running different numerical simulations of various events not correctly predicted by the model. In particular, this work refers to a severe event (moist convection) happened in Piemonte region during summer 2006. On one side the results suggest that details in orography representation have a strong influence on accuracy of QPF. On the other side COSMO Model exhibits a poor sensitivity on changes in numerical and physical settings when measured in terms of QPF improvements. The conclusions, although not too general, give some hint towards the behaviour of the COSMO Model in a typical convective situation.
The HYDROPTIMET Project, Interreg IIIB EU program, is developed in the framework of the prediction and prevention of natural hazards related to severe hydrometeorological events and aims to the optimisation of Hydro-Meteorological warning systems by the experimentation of new tools (such as numerical models) to be used operationally for risk assessment. The object of the research are the Mesoscale weather phenomena and the response of watersheds with size ranging from 10 2 to 10 3 km 2 . Nonhydrostatic meteorological models are used to catch such phenomena at a regional level focusing on the Quantitative Precipitation Forecast (QPF). Furthermore hydrological Quantitative Discharge Forecast (QDF) are performed by the simulation of run-off generation and flood propagation in the main rivers of the interested territory. In this way observed data and QPF are used, in a real-time configuration, for one-way forcing of the hydrological model that works operationally connected to the Piemonte Region Alert System. The main hydro-meteorological events that interested Piemonte Region in the last years are studied, these are the HYDROPTIMET selected test cases of 14-18 November 2002 and 23-26 November 2002. The results obtained in terms of QPF and QDF offer a sound basis to evaluate the sensitivity of the whole hydro-meteorological chain to the uncertainties in the numerical simulations. Different configurations of non-hydrostatic meteorological models are also analysed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.