Can severe rain events over the Mediterranean region be detected through simple numerical indices?
- 155 Downloads
This work evaluates two numerical warning indicators of severe weather. These indicators, the MKI and RDI indices, were developed within the framework of the EU-funded FLASH project which studies flash flood events in the Mediterranean Basin. The MKI (Modified K-Index) is a modification of the K-Index, which expresses probability of lightning activity, and the RDI (Rain Dynamical Index) is the integrated upward moisture flux. The indices were tested on 59 episodes which occurred during nine rainstorms in Israel, Greece, Spain, Italy, and Cyprus. The data for calculation of the indices included rain cell identification derived from microwave radiometer imagery of polar orbiting NOAA satellites, rain RADAR data, and lightning activity from the international ZEUS detection system. Atmospheric data with 0.5° × 0.5° spatial resolution and 6-h time resolution were used for the calculation and the display of the two indices. The indices were tested by calculating the spatially correlating locations with high index values and actual locations of intense rain and intense lightning. The RDI detected both event types: rain and lightning, with a statistically significant success rate and a low rate of false results. The MKI was successful in indicating intense lightning activity, but the rate of correct indications was not statistically significant and there was a high rate of false indications. The results suggest that the RDI computed with output of weather prediction models is a potentially good predictor of torrential rain and therefore can predict flash floods caused by such rain in the Mediterranean region.
KeywordsFlash flood Lightning activity Thermodynamic and dynamic indices Modified K-Index Dynamic rain index Mediterranean climate Extreme weather
- Doswell CA (2001) Severe convective storms, 3rd ed. Meteorological Monographs, vol. 28. Amer. Meteor Soc., BostonGoogle Scholar
- Doty BE (1988) Grid analysis and display system (GrADS). Center for Ocean-Land-Atmosphere Interactions, Institute for Global Environment and Society, CalvertonGoogle Scholar
- Geer IW (ed) (1996) Glossary of weather and climate. Am Meteor Soc, Boston, 272 pGoogle Scholar
- Harats N, Ziv B, Yair Y, Kotroni V, Dayan U (2010) Dynamic and thermodynamic predictors for lightning and flash floods in the Mediterranean. Adv Geophys 23:57–64Google Scholar
- Price C, Yair Y, Mugnai A, Lagouvardos K, Llasat MC, Michaelides S, Dayan U, Dietrich S, Galanti E, Garrote L, Harats N, Katsanos D, Kohn M, Kotroni V, Llasat-Botija M, Lynn B, Mediero L, Morin E, Nicolaides K, Rozalis S, Savvidou K, Ziv B (2011a) The FLASH project: using lightning data to better understand and predict flash floods. Environ Sci Policy 14:898–911CrossRefGoogle Scholar
- Price C, Yair Y, Mugnai A, Lagouvardos K, Llasat MC, Michaelides S, Dayan U, Dietrich S, Di Paola F, Galanti E, Garrote L, Harats N, Katsanos D, Kohn M, Kotroni V, Llasat-Botija M, Lynn B, Mediero L, Morin E, Nicolaides K, Rozalis S, Savvidou K, Ziv B (2011b) Using lightning data to better understand and predict flash floods in the Mediterranean. Surv Geophys 32:733–751. doi:10.1007/s10712-011-9146-y CrossRefGoogle Scholar
- Sanò P, Panegrossi G, Casella D, Di Paola F, Milani L, Mugnai A, Petracca M, Dietrich S (2015) The passive microwave neural network precipitation retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies. Atmos Meas Tech 8:837–857. doi:10.5194/amt-8-837-2015 CrossRefGoogle Scholar
- Yair Y, Lynn B, Price C, Kotroni V, Lagouvardos K, Morin E, Mugnai A, Llasat MdC (2010) Predicting the potential for lightning activity in Mediterranean storms based on the weather research and forecasting (WRF) model dynamic and microphysical fields. J Geophys Res 115:D04205. doi:10.1029/2008JD010868 CrossRefGoogle Scholar