Warm season convective wind CLIMATOLOGY for the ccafs/ksc area Katie Laro Plymouth State University, Plymouth, New Hampshire E-mail: kllaro1@plymouth.edu Background Information Distribution of Events Diurnal Variations Radar Study Results The warm-season convective wind climatology for Cape Canaveral Air Force Station (CCAFS)/Kennedy Space Center (KSC) has been recently updated and extended to cover 15-years to include the 2008 and 2009. The original climatology was produced by Sanger(1999) which started the study with the years 1995-1998 to only include warning level microburst events. Loconto (2006) continued this study and greatly fine tuned the methodology by looking at various convective wind predictors from 1993-2003. Cummings et al. (2007) added the years 2004-2005 to included all microburst events, not just the warning level events. This study was later enhanced by Dinon et al. (2008), who analyzed radar data to study boundary interactions, cell type, cell strength, group movement, and cell movement in relation to the location of max peak wind for warning-level events. Ander et al. (2009) added data for years 2006 and 2007 and expanded the radar climatology to include all non-warning level periods. This project again increased the span of the entire climatology by another two years.. The wind data for this study comes from 36 weather towers on and around CCAFS/KSC area. Since they record the winds every five minutes, they are used to identify peak wind gusts and classify an event as either warning level, with peak winds being ≥ 35kts, or non-warning level where peak winds are < 35kts. High resolution radar data come from the National Weather Service radar site, located in Melbourne, FL. More information can be found at: http://vortex.plymouth.edu/conv_winds/ The first task was to identify convective periods from surface and radar observations . Those periods are defined as beginning on the top of the hour when convection in the area first occurs, and ending at the top of the hour after the last evidence of convection dissipates. Then the period needs to be followed by a break in convective activity for a time of 6 hours or more (Cummings et al. 2007). Programs were developed that extract and analyze the peak wind tower data for all of the convective periods. The programs can stratify the wind speeds vs.: hour, height, direction, tower number., etc. and determine the peak wind speed and time for each convective period. The stratified data are then made web accessible (see Figures 2 and 3). Figure 8 shows the hours with the greatest number of observations are in the afternoon, which is likely caused by daytime heating. Figure 8. Figure 9 demonstrates that strong winds can occur at any time of the day and that there’s a minimal correlation between the number of events (noted in bars) for a particular hour and associated wind speed. Figure 13. Figure 9. Elevation Variations Figure 2. Web page to access the stratified wind data. Figure 3. Example of peak speeds data. Figure 14. Flow Regimes, Monthly, and Yearly Variations Flow regimes directly relate to the intensity and occurrence of convective events. Lambert (2007) classified the eight flow regimes by the position of the subtropical ridge axis relative to Florida. Figure 10. Figure 11. The purpose of normalizing the data was to correct for the varying number of sensors by height. The non-warning and warning level-normalized elevations are very alike. Both peaks of events occurred at 295 feet. Their minimums which, were also the same, were at 12 feet. CCAFS/KSC Wind Tower Network Figure 15. Figure 13 shows the greatest percentage of convective periods for both warning and non-warning levels are pop up storms, which are most commonly initiated by daytime heating. In Figure 14, moderate is the most common strength for both warning and non-warning storms. The most common cell structure for warning level events is linear, where the most common for non-warning is cluster. This means that there’s a significant association with linear structured cells and high winds, and with cluster shaped cells and weaker winds. As shown in Figure 15. Radar Climatology Classifications Figure 4. Figure 5. Dinon et al. (2008) created a method of classifying the convective periods into six categories using NEXRAD radar for KMLB or KTBW if Melbourne wasn’t available . Figure 12 shows three of the six categories. The other three are group movement, individual cell movement, and location of the storm. Cell Initiation Cell Structure Cell Strength SBF and OFB Linear Weak/Broken SBF only Individual Cell Moderate OFB only Cluster Strong No SBF or OFB Figure 4 shows July having the maximum, and May having the minimum frequency of convective events. The flow regimes in Figure 6 help to explain why. The majority flow regimes for May were NW and NE, with SW-2 being the most dominant for July. References Lericos, T. P., H. E. Fuelburg, A. I. Watson, and R. I. Holle, 2002: Warm season lightning distributions over the Florida Peninsula as related to synoptic patterns. Weather and Forecasting, 17, 83-98. Figure 6. Figure 7 shows the results for 2006 and 2009, which were the years with minimum and maximum number of convective events, respectively as shown in Figure 5. In this figure, the convective flow regimes show that SW-1 and SW-2 were leading factors. Where non-convective had more varied flow regimes. Figure 12. Loconto, A. N., 2006: Improvements of warm-season convective wind fore- casts at the Kennedy Space Center and Cape Canaveral Air Force Station. M.S. Thesis, Dept. of Chemical, Earth, Atmospheric and Physical Sciences, Plymouth State University, Plymouth, NH.. Dinon, H. A., M. J. Morin, J. P. Koermer, and W. P. Roeder, 2008. Convective winds at the Florida spaceport: year-3 of Plymouth State research, 13th Conf. on Aviation, Range, and Aerospace Meteorology, 21-24 Jan 2008, New Orleans, LA. Figure 1. KSC/CCAFS weather tower network used to collect wind data for the study. The 9 towers in white had sensors that either didn’t have peak wind observations 70% of the study or their monthly availability dropped below 65%, both of which are threshold requirements. So they were thrown out of the study. Cell initialization is determined by the types of boundaries that start the convection. Types of initializations include: sea breeze front, outflow boundaries, both, or neither. Cell structure is simply the shape of the storm that’s producing the peak winds. Cell strength is based on the decibels of the reflectivity on the radar. If the decibels are less than 45, the storm is classified as weak, 45-55 is moderate, and greater than 55 is strong. Figure 7.