EMS Annual Meeting Abstracts
Vol. 21, EMS2024-592, 2024, updated on 05 Jul 2024
https://doi.org/10.5194/ems2024-592
EMS Annual Meeting 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Thursday, 05 Sep, 18:00–19:30 (CEST), Display time Thursday, 05 Sep, 13:30–Friday, 06 Sep, 16:00|

A WRF-based operational high-resolution numerical weather prediction system in northern Greece

Ioannis Pytharoulis1, Stergios Kartsios1, Christos Spyrou2,3, Ioannis Tegoulias1,4, Dimitrios Bampzelis1, and Prodromos Zanis1
Ioannis Pytharoulis et al.
  • 1Laboratory of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece (pyth@geo.auth.gr)
  • 2Raymetrics S.A., Athens, Greece
  • 3Research Centre for Atmospheric Physics and Climatology, Academy of Athens, Athens, Greece
  • 4Meteorological Applications Center, ELGA, Thessaloniki, Greece

The region of Central Macedonia in northern Greece has a vital role in the financial life of the country because of its tourism and agricultural production. A primary objective of the Agroray project, which is a collaboration of Raymetrics S.A. and the Laboratory of Meteorology and Climatology of the Aristotle University of Thessaloniki, is the development of an operational high-resolution numerical weather prediction system that focuses on Pieria and its surrounding areas. This system provides timely and valid forecasts and allow the farmers to optimize their activities and protect their production from intense or high-impact weather events. It is based on the non-hydrostatic Weather Research and Forecasting (WRF) model with the Advanced Research dynamic solver. Three model domains, using telescoping nesting, cover: i) Europe, the Mediterranean Sea and northern Africa, ii) a large part of Greece and iii) central Macedonia, part of Thessaly and western Macedonia (central and northern Greece), at horizontal grid-spacings of 9 km, 3 km and 1 km, respectively. In the framework of the Agroray project, the meteorological forecasts become available to the farmers and the public (https://meteoray.com/en/). Kalman filtering is applied to the numerical forecasts at locations with station observations in order to reduce their systematic errors. The aim of this research is to present the meteorological model setup and its operational use, as well as to validate its performance during selected intense weather events (related to frost or intense precipitation) that affected the area of interest. The statistical scores were computed against station measurements and weather radar-estimated precipitation, using point statistics and a neighborhood-based technique, to investigate the impact of different model characteristics and surface input data on the model performance.

Acknowledgments: This research was carried out as part of the Agroray project, entitled “Development of a forecasting system and geographical indicators for the agriculture” (project code: KMP6-0078047) under the framework of the action “Investment Plans of Innovation” of the Operational Program “Central Macedonia 2014–2020”, which is co-funded by the European Regional Development Fund and Greece.

How to cite: Pytharoulis, I., Kartsios, S., Spyrou, C., Tegoulias, I., Bampzelis, D., and Zanis, P.: A WRF-based operational high-resolution numerical weather prediction system in northern Greece, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-592, https://doi.org/10.5194/ems2024-592, 2024.