CHARACTERISATION OF STORM SEVERITY BY USE OF SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM SATELLITE DATA

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1 CHARACTERISATION OF STORM SEVERITY BY USE OF SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM SATELLITE DATA Piotr Struzik Institute of Meteorology and Water Management, Satellite Remote Sensing Centre 14 P. Borowego Str., Krakow, Poland Abstract Rapid development of convective clouds leading to storm occurrence is a process which is still investigated. Deep convection and storms are forecasted with significant uncertainty. In many cases, storm severity cannot be predicted properly. An information characterising convective cell development are required for storm monitoring, nowcasting and if lead time is sufficient, also for warning. Satellite data allow for monitoring of convection development from the early beginning. Presented work is an analysis of main parameters characterising convection development connected with cloud top features (i.e. overshooting tops and cloud top temperature) with relation to storm severity. Application of thresholds determined outside Europe or even in different region of Europe leads frequently to misinterpretation of the phenomena. Storm severity cannot be determined by a simple indicator. There are many phenomena which characterize storm severity: lightnings, precipitation intensity, hail occurrence, wind speed etc.. The relation between thermal cloud top characteristics determined with use of: cloud top temperature and overshooting tops occurrence (WV-IR temperature difference) to storm severity estimated by electrical activity was analysed, taking into account recent storm seasons in Poland. In this study, electric activity of storm cell determined from lightning detection system PERUN, operational in Poland, was used as an indicator of storm severity. Additionally, comparison of observed at the ground Synop present weather were compared to the occurrence of mentioned satellite derived cloud top features. Obtained results were discussed to show benefits and limitations of this approach connected with proper determination of cloud properties using satellite data and from the second hand appropriate determination of storm severity with use of lightning detection. The purpose of this work was to contribute to better determination of proper criteria for deep convection and storms analysis. STORM SEVERITY HOW WE CAN DEFINE IT? Storm severity cannot be determined by a simple indicator. In the regions of tropical storms and frequent tornadoes are used different scales. In such regions like Europe, storm severity is rather related to meteorological phenomena, electric activity or damages resulted by: wind, hail, heavy rainfalls, tornadoes. There are many features which can characterize storm: number of lightnings, type of lightnings (CC, CG-, CG+), maximum current, precipitation intensity, amount, hail occurrence, size, wind speed, tornado occurrence, damages.

2 The purpose of this study was to link storm occurrence and their severity observed at the ground with features observed by satellites for further storm detection and its severity estimation. Fig. 1. Manifestation of storm severity left: results of tornado on (fot. IMWM), right: lightnings (fot. R. Klejnowski) SHORT DESCRIPTION OF ANALYSED SATELLITE AND GROUND OBSERVATIONS. Most suitable for storm monitoring are those satellite products which can be for used 24 hours, not related to Sun presence. Use of IR channels is in such case obligatory. Typical storm related satellite products for 24 h storm monitoring are: IR 10.8 µm cloud top temperature and height, WV-IR temperature difference (called frequently Overshooting Tops Product), Cloud phase use of 3.9 µm channel RGB colour composites, Combined products using several features (expert systems). From the second hand available storm related ground observations are: From Synop observations: wind, rain (6 hourly), actual weather, past weather: Lightning detection systems: Lightning: type, position, current Automatic weather stations: wind, rain (10 min), Radars: Cloud droplets phase, hail detection, Cloud height, Radial wind based on Doppler measurements. In this were used two satellite products, very popular for 24h storm detection and monitoring: clod top temperature observed in IR 10.8 µm channel and observed temperature difference between WV 6.2 µm and IR 10.8 µm channels. As a ground reference, indicating, that we have storm, and characterising storm severity were used: lightnings and Synop observations. Only cloud-to-ground (CG) discharges from Polish PERUN system (SAFIR) were selected, due to several problems with cloud-to-cloud (CC) lightnings. The last ones are frequently observed out of clouds (disturbances from

3 military aircrafts systems) and also have significant directional behaviour radial to ground stations. To avoid additional errors CC lightnings were nor taken into account. Hourly Synop observation, with synoptic code WW (Present Weather) were used to indicate storm occurrence, hail occurrence, storm severity. COMPARISON OF STORM CELL FEATURES AND DETECTED LIGHTNINGS. Comparison between cloud features derived from satellite observations and lightnings detected by ground system PERUN was performed for the whole 2010 storm season: One way approach was analysed: if we have lightnings (storm exist) - what we can read from satellite data. Opposite relation was still not analysed: if we have clouds with selected features (IR and WV-IR temperatures) - does it mean, that we have storm? From lightning data were analysed: number of lightnings, type (CG+, CG-), current [ka]. To avoid potential problems with parallax effect and localisation precision of PERUN system, satellite data from the area surrounding discharge were taken into account. The box with size of 7x7 SEVIRI satellite pixels were used for analysis. Such box centred over the lightning position lead to analysis of cloud features within approximately 20 km radius (on the area of Poland). The minimum IR 10.8 temperature and maximum WV-IR temperature from such box were used as an satellite indicators of cloud top features. The results from 2010 storm season are presented below. The number of lightnings detected for each value of IR 10.8 Cloud Top Temperature. Fig. 2. Number of lightnings, originating from clouds with presented top temperature. It is well seen, that most of the lightnings are associated with cold clouds, approximately 90% of them are connected with clouds having temperature between -48 and -72 deg. C. The coldest observed cloud, which produced lightning had -72 deg. C. Much more frequent we can observe negative discharges then positive ones. Only about 9% of cloud-to-ground lightnings had positive current. For satellite products WV-IR, we observe opposite behaviour, majority of lightnings is associated with WV-IR values close to 0 deg, specially positive discharges are most frequent when WV-IR temperature difference is close or above zero.

4 Analysis of maximum current of CG lightnings with relation to cloud top properties visible by METEOSAT SEVIRI instrument is presented on Fig.4. can be observed, that maximal currents are connected with cold clouds. Less evident relation can be found on graph presenting lightnings maximum current in relation to WV-IR temperature difference. Fig. 3. Number of lightnings, originating from clouds with presented WV-IR temperature difference. Fig.4. Maximum current of CG- and CG+ lightnings in comparison to Cloud Top Temperature and WV- IR temp. Difference. Such a behaviour of cloud electricity is not continuous during the whole storm season. At the beginning of the season (April) and at the end (September) storm clouds are less developed, minimal cloud top temperature found for those months is around -60 deg. C. Lightnings are more regularly distributed over all cloud temperatures, specially for WV-IR graph. When middle part of storm season was analysed, we can observe sharp maximum, both for IR and WV-IR cloud top properties.

5 Fig. 5. Seasonal differences - left: April and September, right: May, June, July, August COMPARISON OF STORM CELL FEATURES AND OBSERVATIONS AT SYNOPTIC POSTS. Satellite products presenting derived cloud features, generated each 15 minutes from METEOSAT satellite were compared to Synop observations. During whole 2010 storm season approx Synop reports from 76 Polish stations (including airport reports) were used for this study. Satellite product from time slots xx:45 were used, as closest to Synop observation time. Synoptic codes WW Present Weather related to storm occurrence were used in analysis: Non-Precipitation Events Lightning Visible, No Thunder Heard Thunderstorm But No Precipitation Falling At Station Squalls Within Sight But No Precipitation Falling At Station No Cases In Funnel Clouds Within Sight - No Cases In 2010 Precipitation Within Past Hour But Not At Observation Time Hail Showers Thunderstorms Showers light hail showers moderate to heavy hail showers Thunderstorms Thunderstorm In Past Hour, Currently Only Light Rain Thunderstorm In Past Hour, Currently Only Moderate To Heavy Rain Thunderstorm In Past Hour, Currently Only Light Snow Or Rain/Snow Mix Thunderstorm In Past Hour, Currently Only Moderate To Heavy Snow Or Rain/Snow Mix Light To Moderate Thunderstorm Light To Moderate Thunderstorm With Hail Heavy Thunderstorm Heavy Thunderstorm With Duststorm Heavy Thunderstorm With Hail Relation between Synop Present Weather and both satellite derived IR 10.8 cloud top temperature and WV-IR temp. difference were investigated. Box 7x7 SEVIRI satellite pixels centred over each

6 Synop station was used for analysis. Which is representation of approx 20 km horizon of storm observations at the station (which may be not truth in the mountains). At the first analogically to the study on lightnings, were counted reported Synop storm codes for each value of temperature (IR in 2 deg. steps WV-IR in 1 deg. Steps) Fig. 6. Can be observed distinct maximum of reported storms around cold cloud tops and around WV-IR close to 0 deg. C. Hypothesis, that those two features can be used for storm detection is arousing. Fig. 6. Number of reported Synop storm codes for each temperature value in 2010 storm season in Poland. Problem is becoming more difficult, when we analyse opposite relation and put on the graph also Synop non-storm cases. All synoptic WW codes were analysed, excluding only code, where no indication of current weather is available. Fig. 7. Number of Synop storm/non-storm reports for each value of IR 10.8 cloud top temperature. Can be observed, that only for very cold clouds and positive WV-IR temperature values number of storm cases is higher than non-storm ones. Those two features were used as indicator of storm. In the Table 1 are presented results in form of the contingency table. On the left was used criteria, that storm cloud ought to have IR temperature below -48 deg. C and WV-IR temp. difference above -3 deg. C.

7 Fig. 8. Number of Synop storm/non-storm reports for each value of WV-IR temperature difference. Total = POD = 0.64 FAR = 0.79 POFD = 0.10 Accuracy = 0.89 CSI = 0.19 Total = POD = 0.40 FAR = 0.63 POFD = 0.03 Accuracy = 0.95 CSI = 0.24 Table 1-2. Contingency table with different criteria for storm features retrieved from satellite data. Due to the high False Alarm Rate value, to reduce it, more sharp conditions were used on the right side of Table 1 cloud top temperature <=-53 deg. C and WV-IR >=0 deg. C. FAR was slightly reduced, but also POD went down. Using only presented two cloud features is not possible to reduce FAR. Additional method is required. CONCLUSIONS. 1. If we have lightnings, we can be sure, that most of them (90%) are produced by very cold cloudes (-48 to -72 deg C on the area of Poland) and having WV-IR temperature difference close or above 0 deg C.

8 2. Majority of storms reported by Synop observations are connected with clouds having presented above features. But: 3. When we observe from space clouds having such a features, we cannot be sure that storms are present (according to Synop records). 4. We still need additional parameters! From space? So: 5. We do not observe the same from space and on the ground. 6. More investigations are needed: comparison to Synop cloud observations, severe non-storm weather, instantaneous precipitation from AWS, wind speed. 7. Reduction of FAR may be performed with use of additional information, radar products are the most promising solution. This study will be continued. Determined convective cloud parameters were investigated for further use in automatic expert system, under preparation at IMWM in frame of project: Influence of climate change to environment, economy and society, co-financed by European Regional Development Fund. REFERENCES Bauer-Bessmer B. (1995), Remote Sensing of Severe Hail Storms, Diss.ETH No , Swiss Federal Institute of Technology Zürich Doswell, C. A., III, (2001): Severe convective storms An overview. Severe Convective Storms, Meteor. Monogr., No. 5, Amer. Meteor. Soc., Jacobson R.A., 2003, Relationship of intracloud lightning radiofrequency power to lightning storm height, as observed by the FORTE satellite, Journal of Geophysical Research, Vol. 108, No. D7, Pajek M., Iwanski R., König M., Struzik P., (2008) Extreme Convective Cases - The Use of Satellite Products for Storm Nowcasting and Monitoring, Proc EUMETSAT Meteorological Satellite Conference, Roberts R.D., Burgess D., Meister M., (2005), Developing Tools for Nowcasting Storm Severity, Weather and Forecasting, Vol. 21, pp Ushio, T., S. J. Heckman, D. J. Boccippio, H. J. Christian, and Z.-I. Kawasaki, (2001) A survey of thunderstorm flash rates compared to cloud top height using TRMM satellite data, J. Geophys. Res., 106, pp. 24,089 24,095. Williams, E. R., (2001) The electrification of severe storms, in Severe Convective Storms, edited by C. A. I. Doswell, chap. 13, pp , Am. Meteorol. Soc., Boston, Mass. Zinner T., Betz H.D., (2009), Validation of METEOSAT Storm Detection and Nowcasting Based on Lightning Network Data, Proc EUMETSAT Meteorological Satellite Conference,