Hailstorms in Northern Greece Evangelos Tsagalidis, Ph.D.
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1 Hailstorms in Northern Greece Evangelos Tsagalidis, Ph.D. Head of Meteorological Applications Centre Hellenic Agricultural Insurance Organization ELGA International Airport Macedonia, Thessaloniki, GREECE
2 The Presentation Greek National Hail Suppression Program Main entities: Meteorological conditions Hailstorms Seeding operations Typical cases according to different hailstorm types Seeding strategies, operational view
3 Greek National Hail Suppression Program
4 Greek National Hail Suppression Program Seeding material & Hailpad network
5 Hailstorms types Browning, K. A., 1977 Unicellular storms of a Single ordinary cell Unicellular storms of a Super-cell Multi-cell storms Line storms
6 I. Unicellular storm of a Single ordinary cell
7 I. Unicellular storm of a Single ordinary cell Temp. ( 0 C) Pressure (hpa) GPH (gpm) Wind (az./kt) Trop Cl. top FL Cl. base SFC
8 II. Unicellular storm of a Super cell
9 II. Unicellular storm of a Super cell Temp. ( 0 C) Pressure (hpa) GPH (gpm) Wind (az./kt) Cl. top Trop FL Cl. base SFC
10 III. Multi cell storm
11 III. Multi cell storm Temp. ( 0 C) Pressure (hpa) GPH (gpm) Wind (az./kt) Trop Cl. top FL Cl. base SFC
12 IV. Line storms
13 IV. Line storms Temp. ( 0 C) Pressure (hpa) GPH (gpm) Wind (az./kt) Cl. top -47, Trop. -43, FL Cl. base 18, SFC
14 Hail Suppression - Cloud Seeding Conceptual model of Beneficial competition Seeding techniques: Top seeding (-10 0 C level) Base seeding, seldom because of the terrain Methodology: Cloud seeding is concentrated on the time evolving updraft of ordinary cells or daughter clouds (40%), and on the updrafts of developing feeder clouds that flank mature multi-cell storms (60%)
15 Hail Suppression - Cloud Seeding Conceptual model of Beneficial competition
16 Seeding strategies, Operational view Operational requirement: Seeding according to conceptual model of beneficial competition in every storm that meets the seeding criteria Issue: The availability of the aircrafts for seeding every candidate storm in the frequent case to be numerous storms simultaneously.
17 Seeding strategies, Operational view I. Best possible seeding by one aircraft in many storms Neighboring storms
18 Seeding strategies, Operational view I. Best possible seeding by one aircraft in many storms Cluster of cells
19 Seeding strategies, Operational view I. Best possible seeding by one aircraft in many storms Line storms
20 Seeding strategies, Operational view II. Two aircrafts simultaneously in a project area (safe separation, by flight level and by azimuth or range) if there are not restrictions by Air Traffic Control
21 Seeding strategies, Operational view II. Two aircrafts simultaneously in a project area The operational processes of the GNHSP have been analyzed with the development and implementation of a stochastic discrete event simulation model. Operational Research, Simulation (E. Tsagalidis, 2009) Metrics 1 A/F 2 A/F Percentage of non seeded storms 19% 2.8% Percentage of seeded storms with QS 100% 74% 92% 70% 87% 97% The possibility to immediately start seeding 48% 65% Average delayed time to start seeding 5.6min 0.6min Maximum delayed time to start seeding 17.5min 3.1min Average required seeding time : 20.1min Quality of Seeding as a service (QS) : The ratio of the real seeding time of each storm to its required seeding time.
22 Seeding strategies, Operational view III. Selection of a storm according to the cultivation, defining priorities in parts of the project areas
23 Seeding strategies, Operational view III. Selection of a storm according to the storm type, evolution and development stage of each storm
24 Seeding strategies, Operational view III. Selection of a storm according to the storm type, evolution and development stage of each storm
25 Seeding strategies, Operational view III. Selection of a storm according to the storm type, evolution and development stage of each storm
26 Seeding strategies, Operational view III. Selection of a storm according to the trend to enter or leave the project area
27 Seeding strategies, Operational view IV. Aircraft replacement
28 Seeding strategies, Operational view IV. Aircraft replacement
29 Seeding strategies, Operational view The availability of the aircrafts for seeding every candidate storm in the frequent case to be numerous storms simultaneously: I. Best possible seeding by one aircraft in many storms: Neighboring storms, Cluster of cells, Line storms. II. Two aircrafts simultaneously in a project area (safe separation, by flight level and by azimuth or range) if there are not restrictions by Air Traffic Control. III. Selection of a storm according to a. the cultivation defining priorities in parts of the project areas, b. storm type, evolution and development stage of each storm, c. the trend to enter or leave the project area. IV. Aircraft replacement V. Best management of the aircrafts. Important the role of weather forecast and nowcasting.
30 References Browning, K. A., 1977: The structure and mechanisms of hailstorms, Meteor. Monogr., 38, Dixon, M., and G. Wiener, 1993: TITAN: thunderstorm identification, tracking, analysis, and nowcasting a radar based methodology. J. Atmos. Ocean. Technol., 10(6), Karacostas, T. A.: The design of the Greek National Hail Suppression Program. Proc. 9th Conf. on Wea. Mod., AMS, Park City, Utah, 26-27, Tsagalidis E. and K. Tsitouridis: Storm Cell Complexes. Types, comparison of characteristics and location, 5th National Conference of Meteorology, Climatology and Physics of Atmosphere, Thessaloniki, E. Tsagalidis, E. Hatzi, D. Boucouvala, April 2006: Comparison of the hailstorm characteristics between two different areas in Greece, Journal of Weather Modification, Volume 38, p S. Tzoumaki, E. Tsagalidis, E. Hatzi, S. Dimoutsi, April 2006: Seeding operations in the Greek National Hail Suppression Program, Journal of Weather Modification, Volume 38, p E. G. Tsagalidis, A. C. Georgiou, January 2009: Using simulation modeling to support decisions in hail suppression programmes with airborne means, Journal of the Operational Research Society, Volume 60, Number 1, pp E. Tsagalidis, K. Tsitouridis, G. Evangelidis, and D. Dervos April 2010: Maximum Hail Size Prediction, Journal of Weather Modification, Volume 42, p.7-12.
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