The Effect of Urban Influences on Storms and Storm Relative Motion. in two Midwestern Cities. Prepared for

Transcription

1 The Effect of Urban Influences on Storms and Storm Relative Motion in two Midwestern Cities Prepared for Dr. Mike Chen and the Senior Thesis Award Committee Iowa State University of Science and Technology s Department of Geological and Atmospheric Sciences Agronomy Hall Ames, IA Prepared by Thomas Oliver Maaske Meteorology 499 Iowa State University Ames, IA December 6, 2013

2 The Effect of Urban Influences on Storms and Storm Relative Motion in two Midwestern Cities THOMAS O. MAASKE DR. TSING-CHANG (MIKE) CHEN Abstract Little to no research has been conducted on how the tracks of storms are altered as they pass through an urbanized area. Although many Urban Heat Island (UHI) studies have been done in the past, most of the research focuses on temperatures in the city and precipitation downwind of the city. This study focuses on finding the UHI s affect on storm tracks as storms move over an urban area. This is accomplished by establishing that there are UHI effects in Omaha, NE and Des Moines, IA by analyzing surface temperature with Integrated Surface Data (ISD) data and 3-hr rainfall data through Tropical Rainfall Measuring Mission (TRMM). Then radar and skew-t data was analyzed as the storms pass over the cities. Through analysis of the collected data by comparing urban stations to rural stations, and analyzing storm tracks as storms pass over a city, this study was able to find a good UHI indication in Des Moines, while a much weaker UHI signal exists in Omaha. Moreover, after analyzing eight cases for each city over the last three years this study found strong evidence to support the question do UHI s alter storms as they pass over cities? 1. Introduction In the past few decades, research of cities and the intensity of their heat island effect, urban heat island (UHI), have increased as we know more about the effects of over-development leading to unexpected and unwanted changes in our atmosphere. The area of interest discussed in this paper is not only the effect these urban areas have on the temperature, but more importantly the way an urban area can alter mesoscale storms (storms roughly 5 km to 500 km in size) through the UHI effect. Research on UHI intensity affecting the track of a storm can be crucial for adequately warning people who could be in danger of a storm heading in their direction. Hail, strong winds and flash flooding are major concerns for forecasters and the general public. As urban heating alters the storms it is crucial to know what affect a city has on an impeding storm. The goal of this research is to show how our human activity alters the dynamics of the atmosphere. The more we change things and take away green areas, the more heat will be generated near the surface, leading to more issues in the atmosphere above the city. The specific issue to be addressed is if there is an urban heat gradient large enough around two urban areas (Omaha, NE and Des Moines, IA), and if the cities temperatures cause enough lift to overcome a capped atmosphere, then the resulting storms, storm intensification and storm relative motion will be altered by the UHI, or that the opposite occurs for cities with a population smaller than one million people as suggested by Changnon (2001). This leads to the basis of this study and a question that needs to be answered: do UHI s alter the storm tracks while storms pass over an urban area? 2. Literature review Although UHIs have been heavily researched in the past 30 years (Bornstein et al. 2000) the research has been focused on precipitation and temperatures or as Ashley et al. (2012) calls them, the secondary Phenomena. Due to their effects, UHI s are linked to

3 many implications. First, economic implications, through heat caused by the consumption of fuel in the cars of the city, to the heat caused by the air conditioners being used in the summer (Grimmond et al. 2010). Second, heat leads to many health risks such as dehydration, heat exhaustion, and heatstroke cases every year (Goggins et al. 2012). UHIs still have the potential to go beyond these bounds and alter the air above and thus alter the cloud condensation nuclei (CCN) concentrations in the atmosphere as discussed in Shem and Shepherd (2009) s conclusions. Huff and Changnon (1973) researched UHIs over eight metropolitan areas and found that severe weather is a threat for metropolitan areas due to an increase in precipitation. This increase in precipitation shows that convection must be occurring (Ashley et al. 2012). Huff and Changnon (1973) also found that UHIs caused this increase in precipitation in summer. The same was also found by (Imhoff et. al. 2010; Shem and Shepherd 2009; Bornstein et al. 2000; and Ashley et al. 2012). In fact, Imhoff et. al. (2010) found that for all metropolitan areas in the U.S. the UHI is the greatest in the summer time and the severity of UHIs are also influenced by the type of climate the city is in. Changnon researched UHIs again in 1979 and found that the UHI of St. Louis formed precipitation downwind of the city. With this data and previous research, including Huff and Changnon (1973) and Changnon (1979) concluded that the city of St. Louis caused this rainfall increase. In order to have a better understanding of temperature and precipitation in urban areas, convection must be discussed. In these cases, the findings assume that the UHI causes the initiation, but they do not focus on the cause in each case which is, in most cases, going to be convection. Shem and Shepherd (2009) had major findings in modeling the effects of UHI on precipitation in and around Atlanta, GA. One of their biggest discoveries was an increase in rainfall around an urban area and an understanding of why initiation and intensification occurs around a UHI. The greatest impact from this paper is the possible urban-rural pressure gradient discussed by Shem and Shepherd (2009) that is caused by differential heating between urban and rural areas and vertical mixing during the day. This gives an explanation of why this paper s hypothesis may be true. Much radar study has been done including the Metropolitan Meteorological Experiment (METROMEX) project carried out in St. Louis, MO in the 1970 s (Ackerman et al. 1978) and more recently by (Niyogi et al. 2011) in Indianapolis, IN where they look at the downwind effects versus the upwind effects in and around urban areas. Little to no research has been conducted on how the tracks of storms are altered as they pass through an urbanized area. Research in the METROMEX project (Ackerman et al. 1978) and storm development in Major U.S, cities such as Chicago, IL and New York, NY (Changnon 2001) helped to better develop this paper s hypothesis. There are also sources such as Niyogi et al. (2011), Changnon (1979), Huff and Changnon (1973), Imhoff et. al. (2010), Niyogi et al. (2011), Shem and Shepherd (2009), and Bornstein et al. (2000), that all help to develop the methods, hypothesis, and have helped with the overall development of this research by identifying key results such as downwind rain intensifications and ways to look at this research. 3. Experimental methods and limitations a. Methods This study was performed by initially taking integrated station data (ISD) from the National Climatic Data Center (NCDC). The ISD data set undergoes quality control, which allows for more accurate data analysis. The ISD data was used to identify the intensity of the heat island in both cities (Omaha, NE; Des Moines, IA). Using a FORTRAN code, the ISD data was gathered and then plotted using the GrADS plotting program. The data was plotted on a horizontal field around the two cities (Figures 3, 4, & 5). This allowed for a clearer image of temperature gradients around these cities through contours and shading. In plotting 3-hr TRMM satellite data through GrADS to depict rainfall amounts downwind of cities to solidify the assumption that the two urban areas in this study do in fact have UHI effects and they do alter rain downwind of cities.

4 This leaves an area above the radar that expands with height called the cone of silence which does not allow data to be collected at higher layers above the radar. This is shown in Figure 7 with the slope of blue reflectivity in the background. 4. Results Figure 1: Plot of the station locations used in the study. Archived radar data from the NCDC, visualized with Gibson Ridge Radar Software, was also used to identify any change in storm initiation, storm motion, and/or intensification as the storms passed over a metropolitan area by analyzing a storms reflectivity as it passed over the cities (Ashley et al. 2012; Niyogi et al. 2011; Ackerman et al.1978). Radiosondes were also gathered to look at the vertical structure of the atmosphere during each event. After this data was gathered and analyzed, plots were made comparing temperatures of the control site(s) for both metro areas to determine the UHI effects around the two cities during storm cases from different years. b. Limitations Surface stations are not always located in the center of urban areas and are less dense in rural areas. This shows that the values we get will not express the true UHI effect for each metropolitan area. Also, radiosondes are not densely gridded and may not capture a true representation of the vertical structure of the atmosphere for all surrounding points and all hours between soundings. Due to this limitation, model soundings will be used as well. Next, radar reflectivity can be skewed in various ways because it is a beam of radiation being emitted and reflected back to the source. Sources of error include ducting, bright banding, ground clutter, and many more. A computer then quantifies radar data on a grid so the accuracy is as good as the resolution cells the computer makes. This estimation improves as a hydrometer gets closer to the radar, thus the reasoning for using close range radar for this paper. Finally, radar beams have only a select range of tilts. Preliminary results showed that Omaha, NE and Des Moines, IA both had high precipitation downwind of the city and shown in Figures 2 & 3. These results show that UHI effects are playing a role in storm alteration (Ackerman et al. 1978; Ashley et al. 2012; Huff et.al 1973). Figure 2: High 3-hr precipitation TRMM satellite values downwind from Omaha, Nebraska. Figure 3: Wind stream lines showing the downwind push of the precipitation in Figure 2. The UHI temperature signatures were much easier to plot in Des Moines, IA versus Omaha, NE shown below in Figures 4 & 5. It is assumed that the

5 locations of the three Omaha, NE metro area stations (Figure 6) reporting the temperature data are on or near the Missouri river or located along the edges of Omaha, NE metro area. This results in less of impact of UHI (Figures 5 & 6) while the Des Moines, IA reporting station is in a much more urban setting. Figure 6: Plot showing the urban locations of the Omaha, NE stations (orange hexagons) used for the GrADS program in this study. The red box indicates the Omaha urban stations, and how they are generally located in non urban areas or along the edges of the city (Omaha Metro boundaries are outlined in blue). Figure 4: Smoothed temperature plot with wind streamlines of the state of Iowa with evidence of UHI for the Des Moines stations due to the fact that they are the only stations in the 25 C contoured region. Another significant finding was the movement of and tracking of storms. Initially we thought that local storm reports would be useful in picking out dates to analyze, but it was found that some storms driven by synoptic scale fronts (especially cold fronts) were so powerful they just lifted the UHI s warm and dry air inversion layer away like it was nothing. This is believed to be what is happening in (Figure 7) a case in Des Moines, IA where the frontal boundary pushes under the inversion layer and lifts it over a precipitation core resulting in a weaker reflectivity values aloft, as well as pockets of zero DBZ values further in the storm as the storm mixes the inversion layer in the surrounding storm (Figure 7). Figure 5: Surface temperature plot with wind streamlines of western Iowa and eastern Nebraska showing a temperature bulge around the Omaha metro area.

6 Storm motion Figure 7: GR2Analyst 3D plot looking from the south-south east (depicted by yellow arrows) at a strong thunderstorm passing through the Des Moines metropolitan area (boxed in red) with only the low DBZ values shown to enable the view of what seems to be the inversion layer being lifted above the gust front as depicted by the red arrow and the orange arrows are pointing out pockets of no reflectivity aloft depicting an inversion layer being mixed into the thunderstorm. The forcing was weaker in an Omaha metro case (Figure 8). This case shows the precipitation reflectivity seems to initially want to go over the top and around of this inversion layer, making a bubble of zero DBZ values near the surface over the Omaha metro area. Figure 9: May 19, 2013 a storm over Omaha split as it was passing over the urban area. Left image is 20 min prior to right image. The image on the right shows that the left cell is weakening and the right cell is strengthening. 5. Analysis Statistical analysis of urban temperatures was performed compared to controls (Ames, IA & Knoxville, IA for Des Moines, IA and Fremont, NE for Omaha, NE). Sites north and south of Des Moines were chosen to see how far this inversion layer may be reaching. With no results to support this finding, the controls were still useful in identifying a heat signature even on rainy days which is believed to mute the effects of the UHI thus possibly showing the actual strength of the UHI in Des Moines. The plots showing these statistical analyses are shown in Figures 10, 11, & 12) Storm motion Figure 8: GR2Analyst 3D plot looking from the south-south west (shown by the yellow arrows) at a thunderstorm passing through the Omaha metropolitan area (boxed in red) with only the low DBZ values shown to enable the view of what seems to be the inversion layer at the surface being completely covered by the high precipitation reflectivity above it suggesting that Omaha does have a UHI effect although it may not be plotted on a temperature map, and that it s UHI is altering precipitation over the city. Finally, some evidence was found to suppoert the hypothesis with storm tracks being altered shown below in Figure 9. Figure 10: Plot of hourly temperatures of a rainy day case showing Des Moines (green) for most time stamps warmer than Ames (blue)

7 Days Days Figure 11: Plot of average daily temperatures of seven rainy days showing Des Moines (yellow) consistently warmer than Ames (red) with the standard deviations marked by the blue lines in each bar. Figure 13: Plot of average daily temperatures of seven rainy days showing Omaha (yellow) consistently warmer than Fremont (red), other than the fifth and sixth days. The standard deviations marked by the blue lines in each bar. After collecting the necessary radar data for the days that the inversion layer of the city could be detected by point sounding, it was confirmed that the Rapid Refresh/Rapid Update Cycle (RAP/RUC) model data showed a slight inversion at the surface for both cities (Figure 14). This supports but does not confirm the assumption that the UHI forms a slight inversion layer at the surface and is more likely to be what is being depicted in Figures 7 & 8. Days Figure 12: Plot of average daily temperatures of seven rainy days showing Des Moines (yellow) occasionally warmer than Knoxville (red) with the standard deviations marked by the blue lines in each bar. Similarly, Omaha and Fremont were plotted (Figure 13) side by side to show that Omaha is warmer than Fremont in all but one day suggesting that there is an UHI it just does not plot in GrADS as clearly as Des Moines (Figures 4 &5). Figure 14: RAP sounding on April 08, 2013 at the KOMA station in Omaha s Eppley Airfield, showing an inversion near the surface. After an analysis of the radar data for eight cases in each city between 2010 and 2013, four cases in Des Moines and three cases in Omaha showed a significant splitting of storm cells as they enter or are passing over the metro area (Figure 9), or merging of cells as they have gone past the cities (Figure 15). It is believed to be caused by the inversion layer near the surface (Figures 7, 8 & 14).

8 cases are as well (Figures 9 & 15) with other cases indicating there is an inversion layer around the city (Figures 7 & 8) for most of the cases. This study also found both cities, especially Des Moines, IA, to have strong indications of UHI effects through a horizontal display of temperature and downwind precipitation in GrADS. Through some basic statistical analysis of rain days when the UHI effect should be at its weakest, there were still indications of Des Moines, IA being warmer than both controls. While Omaha, NE was harder to find a UHI indication in the temperature fields, it still seems to have a significant effect on precipitation and storms both in and around the city. More research needs to be done on these and other Midwestern cities to see their UHIs creates an impact on storms and storm relative motion. It would also be interesting to see what, if any, effect UHIs have in larger cities such as Dallas, TX, Kansas City, MO, or Minneapolis, MN or if they have an effect on winter storm tracks. Based on this research UHIs seem to have a large impact not only to metropolitan areas, but also effect storm tracks and increase downwind precipitation indicating that it is a topic that will be studied for many years to come. REFERENCES Figure 15: May 12, storm cells merge on downwind side of Des Moines with the southern cell taking a track that runs almost parallel to the metro boundary line. 6. Conclusions Overall, this study found that both Omaha, NE and Des Moines, IA seem to have an influence on storm tracks and storm motion as they pass over the cities with half of the Des Moines cases in favor of the hypothesis and three out of the eight Omaha, NE Ackerman B., A. Changnon Jr., G. Dzurisin, D.L. Gatz, R. C. Grosh, S. D. Hilberg, F. A. Huff, J. W. Mansell, H. T. Ochs III, M. E. Peden, P. T. Schichedanz, R. G. Semonin, and J. L. Vogel, 1978: Summary of METROMEX, volume 2: causes of precipitation anomalies, IL St. Water Surv., 63, Ashley W. S., M. L. Bentley, and A. J. Stallins, 2012: Urban-induced thunderstorm modification in the Southeast United States (author abstract) (report), Clim. Change, 113(2), 481. Bornstein, R. and L. Qinglu, 2000: Urban heat islands and summertime convective thunderstorms in Atlanta: three case studies, Atmo. Envi., 34(3),

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