Civil protection. (public, government and local authorities institutions)

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1 23 Civil protection (public, government and local authorities institutions) Overview Statistics from the Centre for Research on the Epidemiology of Disasters (CRED) at the University of Leuven, Belgium, reveal that from , about 90% of natural disasters were meteorological or hydrological in origin (Golnaraghi, 2005). Due to various sources of hazards different meteorological data may be useful for the civil protection services. E.g. because of dangerous substances in air the air temperature, wind speed and direction, information about rain etc., constitute very important data for fire brigades, as the most present measurements and forecasts. The main advantages of weather radar data that result from their features, enable the users to: real time monitoring of the rainfall over specific watersheds, accurate and real time monitoring of the rainfall over vulnerable areas, anticipation of flooding risks, flood forecasting (nowcasting), decision-making aid fast and reliable in the event of exceptional weather events, warning for sewer system management in urban areas, safety of vulnerable areas for a cost defying any competition, detection of exceptional weather events and the set up of alarm systems, evaluation of aquifer recovery. Nowcasting (ultra-short term forecasting) Using radar data, a forecaster can determine the nature of any existing weather systems and follow their movement and evolution (Mecklenburg et al., 2005). This is a valuable tool for making short term weather predictions. Data usefulness meteorological maps for specific domain: ground precipitation, especially heavy one, type of precipitation, wind vectors monitored using GIS-based tools, high-resolution: at least 1 km, every from 10 min to 1 hour, real-time and nowcasted data, built-in weather warning system nowcasting-based is desirable.

2 24 Examples of implementations Local authorities institutions (crisis management departments) Weather hazard phenomena monitoring and warnings (especially: precipitation intensity and accumulation, precipitation type, wind velocity and direction, lightning, etc.) is a main goal of this kind of institutions. GIS-based real-time systems supply by weather radar data are developed for such usages (e.g. MeteoGIS system, see Fig. 1). The users of the systems are neither meteorologists nor hydrologists, but governmental employees. Therefore the systems should be designed in such way that most of operations are automatic, and work with operating the system is simple and based on user s intuition. Tornadoes Fig. 1. Example of GIS-based application for weather hazard phenomena monitoring (Jurczyk et al., 2009). The most important phenomena associated with severe convection are tornadoes. The tornado is defined as a violently rotating column of air in contact with the ground and pendent from a cumulonimbus cloud (Fig. 2). When a tornado is present, it is usually small enough that it fits within one or two beam widths. Depending upon the geometry of the beam, the distance of the tornado from the radar, and the location of the beam relative to the tornado, the strong winds of the tornado will typically occupy one or two pixels. Adjacent pixels will have sharply different velocities, typically with one inbound and one outbound. Tornadoes are often located at the center of a hook-shaped echo on the southwest side of thunderstorms. The hook is best observed in the reflectivity field. Another way to determine if a storm is tornadic is to examine the radial velocity field. A mesocyclone, the small rotating circulation with its center beneath the updraft of a supercell thunderstorm, is detectable as a velocity couplet.

3 25 (a) (b) Hurricanes Fig. 2. Tornadoes in radar image: a) radar reflectivity field, b) radial velocity field (Tennessee and Kentucky, USA, 18 May 1995) (source: Hurricanes are tropical cyclones with winds that exceed 33 m/s and circulate counterclockwise about their centers in the Northern Hemisphere (clockwise in the Southern Hemisphere). Hurricanes show up clearly on radar as circular areas of moderate to high reflectivity, often surrounding a low reflectivity center (Fig. 3). Fire Fig. 3. Hurricane in radar reflectivity image (hurricane Andrew, USA, August 1992) (source: Meteorological data are essential for forest fire risk from coming into being to development of the fire. Forest fires are a very complex phenomena that depend on many factors, some of them of socio-economic nature, but also and mainly on physical factors. Climatological and meteorological factors are by far those that have an overwhelming importance on fire occurrence. Meteorological Fire Danger Index is basically a method to assess the probability of fires or large fires occurrences in a given day in a given region. There are many methods of estimating fire danger related to meteorological factors. Mostly the following parameters are employed: precipitation, relative humidity, wind speed, temperature. Software models used for fire extension due to meteorological conditions are employed in civil protection institutions and fire brigades (Fig. 4).

4 26 Chemical disasters Fig. 4. Simulation of fire spread due to wind field (Brown, 2005). This term includes the uncontrolled release of gases, explosives, corrosives, flammable liquids and solids, oxidizers, poisons, or radioactive materials at fixed sites or during transportation. Meteorological conditions are essential for prediction of their extension like in the case of fire events. Volcanic eruption cloud Fig. 5. Time series of selected MAX (maximum of reflectivity) images covering the first 12 h of the Hekla 2000 eruption, Iceland (Lacasse et al., 2004).

5 27 Selected radar images displayed by MAX and echotop screens are shown in Figs. 5 and 6 for The Hekla volcano (Iceland) eruption cloud on 26 February 2000 (Lacasse et al., 2004). The echo is represented by a small region with strong reflectivity (Fig. 5) between 45 and 60 dbz, attributed to high initial column concentrations of ice- or snow-encased lapilli and coarse ash, and possible large snowflakes containing ash. Information from the corresponding Echotop image on Fig. 6 indicates that the head of the eruption column reached over km height a.s.l., between the third (18:20) and fifth minute (18:22) after eruption onset (18:17). Fig. 6. Time series of selected echo top images covering the first 12 h of the Hekla 2000 eruption (Iceland), Iceland (Lacasse et al., 2004). Although weather radars are designed to monitor precipitation clouds and not specifically designed for volcanological use, as, for example, the NEXRAD system developed in the Cook Inlet volcanic region of Alaska, the weather radar can also be used to locate and track volcanic clouds over the volcanic region. Near-real-time monitoring of volcanic clouds can be achieved and provides invaluable information for relevant meteorological centres and aviation authorities that are concerned with preventing encounters of aircrafts with volcanic clouds. Air pollution forecasting Meteorology is one of the major factors contributing to air-pollution episodes. More accurate representation of meteorological fields has been possible in recent years through the use of remote sensing systems, high-speed computers and fine-mesh meteorological models. Over the next years, better meteorological inputs for air quality studies will depend

6 28 on making better use of a wealth of new remotely sensed observations in more advanced data assimilation systems. Improvements in the meteorological observing systems, data assimilation and modeling, coupled with advancements in air-chemistry modeling, will soon lead to operational forecasting of air quality in Europe (Seaman, 2003). Floods Unlike the hydrologist community, the local authorities employees are more interested in output from rainfall-runoff model than input precipitation data. However, especially in the cases of flash floods, overall information about present and future precipitation is expected. Since the radar reflectivity is closely related to the precipitation rate, the total amount of precipitation falling on a region over a fixed period of time can be determined by analyzing reflectivity field over that period. Flash flood warnings would be issued for the stream and river basins which drain these areas. The hydrological usage of weather radar data is described in Section Hydrology. Literature Brown, T.J., Fire Management: Science, decision-making and sustainable partnerships. Wild Fire Workshop, Melbourne, 6-10 June 2005 ( Golnaraghi, M., Early warning systems. Environment & Poverty Times, 2005, No. 03. Jurczyk, A., Ośródka, K., Tkocz, G., and Szturc, J., MeteoGIS : GIS-based system for monitoring of meteorological phenomena for local authorities. 34th Conference on Radar Meteorology, 5-9 October 2009, Williamsburg VA, USA (CD). Lacasse, C., Karlsdóttir, S., Larsen, G,. Soosalu, H., Rose, W.I., and Ernst, G.G.J., Weather radar observations of the Hekla 2000 eruption cloud, Iceland. Bull. Volcanol., 66, Mecklenburg, S., Jurczyk, A., Szturc, J., and Ośródka, K., Quantitative precipitation forecasts (QPF) based on radar data for hydrological models. COST Action 717. Use of radar observations in hydrological and NWP models, Luxembourg Radar meteorology. Online remote sensing guide. University of Illinois ( Seaman, N.L., Future directions of meteorology related to air-quality research. Environment International, 29, Viegas, D.X., Forest fire meteorology research and application. Wild Fire Workshop, Melbourne, 6-10 June 2005 ( workshop_jun_05/06viegas.pdf).