Bologna Limited Area Model Research Articles

A comprehensive study on changes in coastal hydrodynamics associated with cyclonic activity

A Mediterranean cyclone is a weather phenomenon capable of producing extremely severe conditions, including heavy rainfall and strong winds. Between March 24 and 26, 2023, a cyclone passed along the western Egyptian Mediterranean coast, spanning three days. This paper aims to investigate the cyclone's impact on wave characteristics, focusing particularly on simulating changes in the energy transported from wind to waves during its passage, which constitutes the core objective of this study. The research methodology involved collecting meteorological and hydrodynamic data over five days from March 23 to 27, 2023, utilizing databases of the Bologna Limited Area Model (BOLAM) and the General Bathymetric Chart of the Oceans (GEBCO). This data, combined with field data for model calibration and validation, was analyzed using the Simulating the WAves Nearshore (SWAN) model packaged within the Delft 3D hydrodynamical model, integrated with other data manipulation tools. (SWAN) demonstrated the ability to simulate energy transport during extreme weather events along the coastal area with high resolution, up to 500 m. The results indicate a significant increase in significant wave height, reaching up to 2.5 m, and disturbances in wind direction, with velocities exceeding 10 m per second. These conditions pose risks to the infrastructure in some cities along the study area and have severe impacts on coastal communities. A notable finding from the simulations is the excess energy transport, which reached up to 12,000 watts per meter over the sea surface during the cyclone. Furthermore, calibration and validation results affirm the (SWAN) model's capability to accurately study wave characteristics.

Evaluation of BOLAM Fine Grid Weather Forecasts with Emphasis on Hydrological Applications

The evaluation of weather forecast accuracy is of major interest in decision making in almost every sector of the economy and in civil protection. To this, a detailed assessment of Bologna Limited-Area Model (BOLAM) seven days fine grid 3 h predictions is made for precipitation, air temperature, relative humidity, and wind speed over a large lowland agricultural area of a Mediterranean-type climate, characterized by hot summers and rainy moderate winters (plain of Arta, NW Greece). Timeseries that cover a four-year period (2016–2019) from seven agro-meteorological stations located at the study area are used to run a range of contingency and accuracy measures as well as Taylor diagrams, and the results are thoroughly discussed. The overall results showed that the model failed to comply with the precipitation regime throughout the study area, while the results were mediocre for wind speed. Considering relative humidity, the results revealed acceptable performance and good correlation between the model output and the observed values, for the early days of forecast. Only in air temperature, the forecasts exhibited very good performance. Discussion is made on the ability of the model to predict major rainfall events and to estimate water budget components as rainfall and reference evapotranspiration. The need for skilled weather forecasts from improved versions of the examined model that may incorporate post-processing techniques to improve predictions or from other forecasting services is underlined.

Heavy Precipitation over Italy from the Mediterranean Storm “Vaia” in October 2018: Assessing the Role of an Atmospheric River

Abstract The Mediterranean storm “Vaia” developed within a typical autumn synoptic circulation, generally associated with heavy rain conditions over the western Mediterranean Sea basin. Intense precipitation was responsible for floods over Italy between 27 and 30 October 2018, and the storm was accompanied by explosive cyclogenesis, storm surge, and extremely intense wind gusts that caused casualties and extensive damage, especially to the Alpine forests. This study investigates the contribution of different moisture sources to the extreme precipitation by means of numerical model simulations using the Bologna Limited Area Model (BOLAM). In particular, the attention is focused on the significant amount of water vapor transported into the Mediterranean basin from the Atlantic Ocean tropical area and organized along a narrow corridor across the African continent. First, a newly developed detection algorithm is applied to identify this transport as an atmospheric river (AR). Then, the implementation of an atmospheric water budget diagnostic, supported by sensitivity experiments, allows us to assess the role of the AR in terms of water supply to the precipitation systems. Although the transport of moisture from remote regions is known to be an important ingredient for the onset of heavy precipitation in the Mediterranean, the role of ARs, already identified in correspondence with some of these events, has not been deeply investigated and quantified yet in this specific area. The results demonstrate that the AR was critical for determining the magnitude of this heavy precipitation episode over Italy, whereas evaporation from the sea played a secondary role, especially for precipitation over the Alps.

Three-model ensemble wind prediction in southern Italy

Abstract. Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

AbstractCoupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

A numerical study of the windstorm Klaus: sensitivity to sea surface temperature

<p>This article investigates the role of sea surface temperature (SST) as well as the effects of evaporation and moisture convergence on the evolution of cyclone Klaus, which occurred on January 23 and 24, 2009. To elucidate the role of sea surface temperature (SST) and air–sea fluxes in the dynamics of the cyclone, ten hydrostatic mesoscale simulations were performed by Bologna Limited Area Model (BOLAM). The first one was a control experiment with European Centre for Medium-Range Weather Forecasts (ECMWF) SST analysis. The nine following simulations are sensitivity experiments where the SST are obtained by adding a constant value by 1 to 9 K to the ECMWF field. Results show that a warmer sea increases the surface latent heat fluxes and the moisture convergence, favoring the development of convection in the storm. Convection is affected immediately by the increased SST. Later on, drop of mean sea level pressure (MSLP) occurs together with increasing of surface winds. The cyclone trajectory is not sensitive to change in SST differently from MSLP and convective precipitation.</p>

QPF performance of the updated SIMM forecasting system using reforecasts

In late 2009, the meteorological component of the Institute for Environmental Protection and Research (ISPRA)'s Hydro-Meteo-Marine Forecasting System (Sistema Idro-Meteo-Mare – SIMM), namely the hydrostatic Quadrics BOlogna Limited Area Model (QBOLAM), was replaced by an up-to-date version of the same model. This new version, which is simply referred to as BOLAM, deploys advanced parameterization schemes for cumulus convection, radiation, soil, and exchange of turbulent fluxes and uses the explicit advection of five hydrometeors. As a part of the SIMM verification programme, it was judged objectively how these changes affected the quality of quantitative precipitation forecasts (QPFs). This was done by intercomparing the current operational BOLAM against QBOLAM. Observational analyses, from April to September 2001, deployed earlier to evaluate the QBOLAM performance, were considered for this intercomparison. An ad hoc reforecast campaign was performed to generate the database of the corresponding retrospective QPFs for BOLAM. A multimethod verification approach was used to assess the spatial scales resolved by the intercompared model versions and the skill at forecasting both frequent, high-base rate and rare, low-base rate precipitation events. The effect on performance measures of differences in bias between the intercompared versions was also evaluated. The results indicate an improved performance of BOLAM compared with the older version not only when considering the native 0.1° model grid, where the intercomparison may be affected by differences in the resolved scales, but also when using a coarser 0.5° grid, where the two remapped QPF series show similar spatial scales. Fewer false alarms are produced by BOLAM during the verification time period.

Factors affecting the quality of QPF: a multi‐method verification of multi‐configuration BOLAM reforecasts against MAP D‐PHASE observations

ABSTRACTThis paper discusses the results of a quantitative precipitation forecast (QPF) verification study aimed at comparing different alternative new configurations of the meteorological BOlogna Limited Area Model (BOLAM) to be implemented in 2013 into the ISPRA's Hydro‐Meteo‐Marine forecasting system (SIMM) in place of the currently operational version, dated 2009. Five new configurations are defined after considering several combinations of the following model settings: horizontal grid spacing, domain extension, initial and boundary conditions, nesting design and the BOLAM code version. Such testing configurations are inter‐compared with the operational BOLAM version following a multi‐method approach including Fourier spectral analysis, several categorical scores, quasi‐relative operating characteristic diagram and visual inspection of the spatial distributions of the contingency table elements. Rain gauge measurements available between June and November 2007 within the international initiative ‘Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region’ of the Mesoscale Alpine Programme (MAP D‐PHASE) are considered as observational dataset. A 6 month reforecast campaign is performed in order to produce, for each compared configuration, the corresponding forecast series. Results show that decreasing model grid spacing and simultaneously increasing model domain extension is effective in improving the QPF quality when higher‐resolution initial and boundary conditions are directly applied to BOLAM, without using a coarser‐resolution parent model run. Therefore, such skilful configuration has been deployed in late 2012 within the international research programme ‘HYdrological cycle in Mediterranean EXperiment’ (HyMeX). On the contrary, when keeping the low‐resolution, double nesting configuration, improving input data decreases the QPF performance. Copyright © 2013 Royal Meteorological Society

The Meteorological Global Model GLOBO at the ISAC-CNR of Italy Assessment of 1.5 Yr of Experimental Use for Medium-Range Weather Forecasts

Abstract Since August 2009, the GLOBO atmospheric general circulation model has been running experimentally at the Institute of Atmospheric Sciences and Climate (ISAC) of the National Council of Research of Italy. GLOBO is derived from the Bologna Limited Area Model (BOLAM), a gridpoint limited-area meteorological model that was developed at the same institute and that has been extended to the entire earth atmosphere. The main dynamical features and physical parameterizations of GLOBO are presented. Starting from initial conditions obtained from the analysis of the NCEP Global Forecast System (GFS) model valid at 0000 UTC, 6-day forecasts with average horizontal resolution of 32 km were performed on a daily basis and in real time. The assessment of the forecast skill during the 1.5-yr period included the calculation of the monthly averaged root-mean-square errors (model prediction versus gridded analyses) of geopotential height at 500 hPa and mean sea level pressure for the northern and southern extratropics, performed accordingly to WMO Commission for Basic Systems (CBS) standards. The verification results are compared with models from other global data processing and forecasting system centers, as are available in the literature. The GLOBO skill for medium-range forecasts turns out to be comparable to that of the above models. The lack of analyses based on model forecasts and data assimilation is likely to penalize the scores for shorter-term forecasts.

Evaluating the improvements of the BOLAM model of the ISPRA Sistema Idro-Meteo-Mare on the December 2008 flood event in Rome

Abstract. The Sistema Idro-Meteo-Mare is an integrated meteo-marine forecasting chain for the Mediterranean basin. The recent update of the meteorological segment, based on the hydrostatic BOlogna Limited Area Model (BOLAM), gives the opportunity for a comparative verification study on a Mediterranean cyclone. The 10–12 December 2008 flood event in Rome has been chosen as case study. This disastrous event was claimed to be an extreme one by mass-media; however, its return time is shown here to be about 5 years. The Mediterranean cyclone responsible for the flood offers a tough case study in order to verify the model's ability in reproducing the evolution of meso-synoptic features in the Mediterranean environment. A qualitative comparison, employing satellite data and derived products, is performed. Results suggest that the upgraded model provides a more realistic representation of the cyclone warm sector – where the main rainfall peak took place – whereas the error in the cyclone trajectory and shape evolution is less affected by the BOLAM improvement.

Multisensor Comparison and Numerical Modeling of Atmospheric Water Fields: A VOLTAIRE Case Study over Cyprus

Abstract This paper presents a study performed within the framework of the European Union’s (EU) VOLTAIRE project (Fifth Framework Programme). Among other tasks, the project aimed at the integration of the Tropical Rainfall Measuring Mission (TRMM) data with ground-based observations and at the comparison between water fields (precipitation and total column water vapor) as estimated by multisensor observations and predicted by NWP models. In particular, the VOLTAIRE project had as one of its main objectives the goal of assessing the application of satellite-borne instrument measures to model verification. The island of Cyprus was chosen as the main “test bed,” because it is one of the few European territories covered by the passage of the TRMM Precipitation Radar (PR) and it has a dense rain gauge network and an operational weather radar. TRMM PR provides, until now, the most reliable space-borne spatial high-resolution precipitation measurements. Attention is focused on the attempt to define a methodology, using state-of-the-art diagnostic methods, for a comprehensive evaluation of water fields as forecast by a limited area model (LAM). An event that occurred on 5 March 2003, associated with a slow cyclone moving eastward over the Mediterranean Sea, is presented as a case study. The atmospheric water fields were forecast over the eastern Mediterranean Sea using the Bologna Limited Area Model (BOLAM). Data from the Cyprus ground-based radar, the Cyprus rain gauge network, the Special Sensor Microwave Imager (SSM/I), and the TRMM PR were used in the comparison. Ground-based radar and rain gauge data were merged together in order to obtain a better representation of the rainfall event over the island. TRMM PR measurements were employed to range-adjust the ground-based radar data using a linear regression algorithm. The observed total column water vapor has been employed to assess the forecast quality of large-scale atmospheric patterns; such an assessment has been performed by means of the Hoffman diagnostic method applied to the entire total column water vapor field. Subsequently, in order to quantify the spatial forecast error at the finer BOLAM scale (0.09°), the object-oriented contiguous rain area (CRA) analysis was chosen as a comparison method for precipitation. An assessment of the main difficulties in employing CRA in an operational framework, especially over such a small verification domain, is also discussed in the paper.

A multi‐model/multi‐analysis limited area ensemble: calibration issues

AbstractIn this paper four different post‐processing techniques: the Bayesian model averaging (BMA), the ensemble model output statistics (EMOS) with a variant known as EMOS+ and a new dressing kernel (DRESS) are applied and compared, in a pre‐operational context, to calibrate a mesoscale multi‐model multi‐analysis ensemble. The ensemble makes use of three different limited area models (Bologna Limited Area Model (BOLAM), MM5 and RAMS), one of them used twice with different setups, fed with two sets of analysis and boundary conditions obtained from the European Centre for Medium‐Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP) general circulation models. The resulting ensemble of eight members was run for a period of 6 months (from October 2002 to April 2003) in a Euro–Atlantic domain. The forecast was validated against 2 m temperature measured at 21 meteorological stations scattered across Sardinia (Italy). For each method the calibration ability was assessed evaluating the flatness of the rank histogram, the coverage of the expected forecast intervals and the width of the associated probability distribution function. Results show that BMA and DRESS are the best in improving the calibration of the raw ensemble whereas EMOS and EMOS+ have proven worse, with the latter marginally better. Copyright © 2008 Royal Meteorological Society

Searching for systematic location errors of quantitative precipitation forecasts over the Calabria region

AbstractThis article statistically analyses the location errors of the precipitation patterns forecast by three limited area models, namely the Fifth‐Generation NCAR/Penn State Mesoscale Model (MM5), the QUADRICS BOlogna Limited Area Model (QBOLAM) and the Regional Atmospheric Modelling System (RAMS), over the Calabria region (Italy) for the period October 2000–May 2002. Contiguous rain area (CRA) analysis is the diagnostic tool used to assess and quantify the position errors of the precipitation forecasts with respect to the observed precipitation patterns. Observation gridded analyses were obtained by means of the Barnes algorithm on the available rain gauge observations.Moreover, an approach to measure the quality of precipitation forecasts routinely by means of a global indicator called CRA Mean Shift (CMS) that summarizes the CRA verification outcomes is proposed. The CMS index would represent a statistical indicator of model quality in forecasting the correct positions of precipitation patterns.The model's tendency to misplace the forecast precipitation patterns towards a particular direction was tested by using a bootstrap procedure.All models seem to show statistically poor abilities in forecasting the correct precipitation pattern position over the verification domain considered. As far as the tendency towards a particular direction is concerned, only the RAMS model seems to show a systematic horizontal misplacement of precipitation patterns towards a particular direction. Copyright © 2008 Royal Meteorological Society

A GIS tool for the evaluation of the precipitation forecasts of a numerical weather prediction model using satellite data

In this study, the possibility of implementing Geographic Information Systems (GIS) for developing an integrated and automatic operational system for the real-time evaluation of the precipitation forecasts of the numerical weather prediction model BOLAM (BOlogna Limited Area Model) in Greece, is examined. In fact, the precipitation estimates derived by an infrared satellite technique are used for real-time qualitative and quantitative verification of the precipitation forecasts of the model BOLAM through the use of a GIS tool named as precipitation forecasts evaluator (PFE). The application of the developed tool in a case associated with intense precipitation in Greece, suggested that PFE could be a very important support tool for nowcasting and very short-range forecasting of such events.

Intercomparison of satellite‐based and model‐based rainfall analyses

AbstractFour satellite rain estimations based on microwave (MW), infrared (IR) or combined MW‐IR techniques are compared with the BOlogna Limited Area Model (BOLAM) rain forecast for a severe weather event (8–13 November 2001) over the western Mediterranean Sea.Two of the investigated multi‐channel MW rainfall algorithms use data from the Tropical Rainfall Measuring Mission (TRMM). The Frequency Difference Algorithm relies on data from the TRMM Microwave Imager (TMI) and the other one combines data from the Precipitation Radar (PR) with those from the nine‐channel radiometer TMI, called PR Adjusted TMI Estimations of Rainfall (PATER) algorithm. The pure IR Rain Estimator uses geostationary IR METEOSAT data and the combined Naval Research Laboratory algorithm uses both MW data from low orbiting satellites and IR data from the geostationary orbit.Validation results, computed over a common grid, which is independent of the different field of view sizes of the applied data sets, indicate that there is generally a better performance for heavy rain (>6 mm h−1) than for light rain (<1 mm h−1). Both MW algorithms perform rather similarly, although PATER shows some rain detection problems due to thick aerosol loads originating from the desert. The BOLAM model presents a good agreement with the MW and only a minor location error of a heavy rain area was detected. Both IR‐based algorithms have problems in identifying the correct rainy areas compared to MW. Overall, the results suggest that there are advantages in combining both techniques –the well‐known rain physics of the MW channels with the high temporal resolution of IR algorithms –to retrieve precipitation from satellite data. Copyright © 2006 John Wiley & Sons, Ltd.

Radar adjusted data versus modelled precipitation: a case study over Cyprus

Abstract. In the framework of the European VOLTAIRE project (Fifth Framework Programme), simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM) forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM) satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA) analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

Estimation of dispersion coefficient in the troposphere from satellite images of volcanic plumes: Application to Mt. Etna, Italy

The lateral dispersion of volcanic plumes in the troposphere is investigated using satellite images. Two plume images have been selected from the Mount Etna eruption that occurred in October/November 2002. To reproduce the satellite images two modelling approaches are presented. The first one uses deterministic trajectories released from a line source extending over a range of altitudes chosen from direct observations. The second uses stochastic trajectories from an area source located at a fixed height, where the source size and the effective diffusion coefficient are determined by data analysis. The meteorological model BOLAM (Bologna Limited Area Model) supplies the atmospheric dynamics. Both approaches reproduce the main features of the observed plumes, with differences in the cross section distribution of the density.

Verification of Precipitation Forecasts from Two Limited-Area Models over Italy and Comparison with ECMWF Forecasts Using a Resampling Technique

Abstract This paper presents the first systematic limited area model (LAM) precipitation verification work over Italy. A resampling technique was used to provide skill score results along with confidence intervals. Two years of data were used, starting in October 2000. Two operational LAMs have been considered, the Limited Area Model Bologna (LAMBO) operating at the Agenzia Regionale Prevenzione e Ambiente-Servizio Meteorologico Regionale (ARPA-SMR) of the Emilia–Romagna region, and the QUADRICS Bologna Limited Area Model (QBOLAM) running at the Agenzia per la Protezione dell’Ambiente e per i Servizi Tecnici (APAT). A 24-h forecast skill score comparison was first performed on the native 0.1° high-resolution grids, using a Barnes scheme to produce the observed 24-h accumulated rainfall analysis. Two nonparametric skill scores were used: the equitable threat score (ETS) and the Hanssen and Kuipers score (HK). Frequency biases (BIA) were also calculated. LAM forecasts were also remapped on a lower-resolution grid (0.5°), using a nearest-neighbor average method; this remapping allowed for comparison with ECMWF model forecasts, and for LAM intercomparisons at lower resolution, with the advantage of reducing the skill score sensitivity to small displacements errors. LAM skill scores depend on the resolution of the verification grid, with an increase when they are verified on a lower-resolution grid. The selected LAMs have a higher BIA compared to ECMWF, showing a tendency to overforecast precipitation, especially along mountain ranges, possibly due to undesired effects from the large-scale and/or convective precipitation parameterizations. Lower ECMWF BIA accounts for skill score differences. LAMBO precipitation forecasts during winter (adjusted for BIA differences) have less misses than ECMWF over the islands of Sardinia and Sicily. Higher-resolution orography definitely adds value to LAM forecasts.

A Nudging Scheme for the Assimilation of Precipitation Data into a Mesoscale Model

Abstract A nudging procedure for the assimilation of rainfall data into a mesoscale model [the Bologna Limited Area Model (BOLAM)] has been developed in order to improve short-range forecasting. The scheme modifies the model specific humidity profiles at every time step, according to the difference between observed and forecast precipitation. Different relaxation procedures are applied depending on the precipitation type (large-scale or convective rain), as estimated by the model itself. Optimizations of the nudging parameters and assessment of the scheme's performance was carried out in an idealized framework [(Observing System Simulation Experiment) OSSE-type strategy], implementing a lagged forecast scheme. Two events were selected for this purpose, both characterized by heavy precipitation in the Mediterranean Basin. The first was a severe orographic rainfall event, associated with the passage of a frontal system over the Alps during the Mesoscale Alpine Programme (MAP) field phase, in September 1999....

The Meteorological Model BOLAM at the National Observatory of Athens: Assessment of Two-Year Operational Use

Abstract Since November 1999, the hydrostatic meteorological Bologna Limited-Area Model (BOLAM) has been running operationally at the National Observatory of Athens. The assessment of the model forecast skill during the 2-yr period included (a) calculation of the root-mean-square errors (model vs gridded analyses) of geopotential height and temperature at 850 and 500 hPa, (b) evaluation of the model's quantitative precipitation forecast skill for the most important events, and (c) evaluation of the model skill in the prediction of surface winds in comparison with buoy observations. Comparison of the verification results with those provided in the literature showed that BOLAM has a high forecast skill, even for precipitation, which is the most difficult parameter to forecast. Especially for precipitation, the comparison between coarse (∼21 km) and fine (∼6.5 km) grid spacing forecasts showed that for the low and medium precipitation amounts, the finer-grid forecasts are not as good as the coarse-grid forec...