Local-Scale Weather Forecasts over a Complex Terrain in an Early Warning Framework: Performance Analysis for the Val d'Agri (Southern Italy) Case Study. (19th October 2022)

• Record Type: Journal Article
• Authors: Giunta, Giuseppe; Ceppi, Alessandro; Salerno, Raffaele
• Other Names: Baldi Marina Academic Editor.
• Is Part Of: Advances in meteorology. Volume 2022(2022)
• Publication Date: 2022-10-19
• Subjects: Meteorology -- Periodicals; Meteorology; Periodicals; 551.505
• DOI: 10.1155/2022/2179246
• Languages: English
• ISSNs: 1687-9309

Abstract

Abstract : Forecasting applications based on hourly meteorological predictions for weather variables are nowadays used in energy market operations, planning of gas and power supply, and renewable energy, among others. Available meteorological and climatological data, as well as critical thresholds of rainfall, may also have a key role in the hazard classification, related to slope instabilities of pipelines and critical infrastructures along routes. The present study concerns the performance of a weather forecast model in the framework of an early warning system (EWS) application, which supports the integrity management of oil and gas pipelines. This EWS has been applied on to a specific area: the Val d'Agri basin in the Basilicata region of Southern Italy, which is extensively affected by several landslides and floods. The hourly precipitation forecasts are provided by a dedicated meteorological model, the KALM-HD, using two different horizontal resolutions, 1.25 and 5 km, to analyze possible influences of the mesh grid size as well. On this area, several weather stations were specifically deployed to obtain observed data in a region where hydrogeological hazards are relevant for asset management. A comparison among observations and the KALM-HD scaled forecasts on six of these weather stations is presented to assess the model performance. Besides, precipitation, temperature, and wind speed are evaluated as well. The forecasting analysis is performed considering two years of data both on an overall and seasonal basis. Results show that the KALM-HD performs well with the 1.25 km grid, particularly on temperature and wind speed variables. Since weather stations can be gathered in two main sets depending on their positions, differences arise in the forecast quality of these two groups, related to orography and thermal effects, whose detection is difficult in the typical narrow valleys characterizing the area of study. This issue prevalently influences temperatures and local winds, which, these latter, are generally underestimated, while precipitation is mainly driven by synoptic circulation and its interaction with mesoscale meteorological features.