Validation of a limited area model in cases of mediterranean cyclogenesis: Surface fields and precipitation scores

Buzzi, A.; Fantini, Maurizio; Malguzzi, P.; Nerozzi, F.

doi:10.1007/bf01029609

Cited by 145 publications

(73 citation statements)

References 9 publications

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“…The prognostic variables are temperature, wind (u and v components), specific humidity, surface pressure and turbulent kinetic energy. The downscaling of atmospheric conditions to the sub-regional scale is done by running the model in two nested steps with successively embedded model configurations down to a resolution of 1/24 • (∼5 km) over the central Mediterranean area, and with outputs every 3 h. iv) For the application in Cyprus, the BOLAM model described by Buzzi et al (1994Buzzi et al ( , 1997Buzzi et al ( , 1998 and Buzzi and Foschini (2000) is used. It is a hydrostatic model on an Arakawa C grid (rotated lat./lon.…”

Section: Methodologiesmentioning

confidence: 99%

The RISKMED project: philosophy, methods and products

Bartzokas

Azzopardi

Bertotti

et al. 2010

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper presents RISKMED, a project targeted to create an Early Warning System (EWS) in case of severe or extreme weather events in the central and eastern Mediterranean and specifically in southern Italy, northwestern Greece, Malta and Cyprus. As severe or extreme weather events are considered, cases when the values of some meteorological parameters (temperature, wind, precipitation) exceed certain thresholds, and/or a severe weather phenomenon (thunderstorm, snowfall) occurs. For an accurate weather forecast, selected meteorological models have been operated daily, based on a nesting strategy using two or three domains, providing detailed forecasts over the above mentioned areas. The forecast results are further exploited for the evaluation and prediction of human discomfort and fire weather indices. Finally, sea wave models have also been operating daily over the central and eastern Mediterranean Sea. In case a severe or extreme weather event is forecasted within the next 48 or 72 h for selected target areas (sub-regions defined by their morphological and population characteristics), the local authorities and the public are informed via a user-friendly graphic system, the so-called RISK MAP. On the web page of the Project (http://www.riskmed.net), additional information is provided about the real-time values of some meteorological parameters, the latest satellite picture and the time and space distribution of lightning during the last 24 h.

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Section: Methodologiesmentioning

confidence: 99%

The RISKMED project: philosophy, methods and products

Bartzokas

Azzopardi

Bertotti

et al. 2010

Nat. Hazards Earth Syst. Sci.

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“…The three models are BOLAM (Buzzi et al, 1994), MM5 (Grell et al, 1994) and RAMS (Pielke et al, 1992).…”

Section: The Multi-model Multi-analysis Limited Area Ensemble and Thementioning

confidence: 99%

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

Marrocu

Chessa

2008

Meteorological Applications

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ABSTRACT:In 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.

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“…Following Vautard (1990), Plaut and Simonnet named Atlantic ridge (AR) the SLP regime when the high-pressure over mid-latitude North Atlantic induces north-westerlies over Western and Central Europe; Greenland anti-cyclone (GA) when a dipole of high-pressure over Greenland and low-pressure over mid-latitude North Atlantic causes aforementioned wind patterns. The 925 hPa geopotential heights are from the NCEP/DOE AMIP-II reanalysis (Kistler et al, 2001), while surface wind fields are simulations from the Limited Area Model BOLAM (Buzzi et al, 1994). The uppermost panels show the correspondence between AR-like configuration and maestro wind over Corsica (the event occurred on 21st January 2005); GA-like configuration is then compared to libeccio (21st October 2004); finally, WBL-like configuration gives rise to both sirocco (21st February 2004) and gregale (23rd November 2005) depending on the position of the low-pressure over Mediterranean.…”

Section: Synoptic and Local Forcing To Wind Climatementioning

confidence: 99%

Mesoscale wind climate analysis: identification of anemological regions and wind regimes

Burlando

Antonelli

Ratto

2007

Intl Journal of Climatology

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Following the idea that the climatological study of a physical variable should aim at the comprehension of its mean state as well as the characterization of its dynamics, cluster analysis has been applied to study the wind climate of Corsica (France) in order to identify the anemological regions (mean state) and the wind regimes (weather variability) which characterize its coastal areas. The analysis is based on a 3-year long time-series of measurements of the wind velocity from 11 anemometric stations located along the perimeter of the island. Since the present study was an analysis preliminary to the subsequent assessment of the wind potential of Corsica, we have worked only with wind intensities. Nevertheless, at the end of our analysis, we have also considered wind directions for the final interpretation of the results. The anemological regions are defined through the comparison of 15 different clustering techniques resulting from the combination of three distance measures and five agglomerative methods. As confirmed by geographical considerations, the results identify three distinct anemological regions: the eastern region (ER), the north-western region (NWR), the south-western region (SWR). The wind regimes are identified by means of a two-stage classification scheme based on a hierarchical cluster analysis followed by a partitional clustering. The final classification identifies eight regimes: the four wind regimes corresponding to the main weather patterns of Western Europe, as proposed by Plaut and Simonnet, and another four clusters corresponding to breeze regimes.

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Validation of a limited area model in cases of mediterranean cyclogenesis: Surface fields and precipitation scores

Cited by 145 publications

References 9 publications

The RISKMED project: philosophy, methods and products

The RISKMED project: philosophy, methods and products

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

Mesoscale wind climate analysis: identification of anemological regions and wind regimes

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