1 A Comparison of Iowa Flash Flood Events and Eight Common Features of Excessive Rainfall for 2006-2011 BRITTANY A. KONRADI 1 Mentors: Melinda Beerends 2, Dr. Kristie Franz 1 Department of Geological and Atmospheric Sciences Iowa State University, Ames, Iowa 1 National Weather Service Des Moines, IA 2 ABSTRACT This study examines Iowa flash flood events from 2006 to 2011 and includes case studies of six non-winter events that were either well or poorly predicted by the National Weather Service Forecast Office in Des Moines, Iowa. Data regarding environmental and antecedent variables from these case studies is compared to flash flood criteria from Maddox et al. (1979). Four out of the six case studies agreed with Maddox et al. (1979) criteria and synoptic set-up. The common parameters that differed amongst flash flood and nonflood events were moisture and shear. 1. Introduction A flood is an important weather-related event that involves numerous environmental and antecedent conditions, unlike other meteorological events. Floods are the secondmost deadly weather events in the United States with an average of 100 flood fatalities and two billion dollars damage annually (Ashley and Ashley 2008). Typically the number of weather-related fatalities decreases over time due to technological advancements. For example, the tornado warning system has advanced over time due to improvements in radar (Ashley 2007). Its improvements have led to increased lead time and decreased fatalities. Unfortunately, the amount of flood fatalities per year has not decreased with time (Ashley and Ashley 2008). Two common causes of fatalities and damage are public misunderstandings and poor forecasts (Ashley and Ashley 2008). Public misunderstandings often result from not understanding the severity of a flood event until it occurs, which can result in dangerous and avoidable situations (Morss 2010). Roebber and Eise (2001) state that emergency management officials are not always aware of the uncertainty in flood forecasting. A forecaster may predict a certain flood crest, but flood forecasts are often made before the flood s causative event occurs. Communication amongst forecasters, emergency management, and the public is crucial to decreasing damage and fatalities (Roebber and Eise 2001). While public misunderstandings may improve over time with better communication, current numerical models, real-time data, and forecast methodology are important for improving the information that is given to the public. Current weather data is improving, but it is not yet ideal for flash flood forecasts. Numerical models use large spatial and temporal scales that are not ideal for mesoscale events like flash floods. However, models can forecast other environmental variables like soil moisture and temperature with useful accuracy (Doswell et al. 1996).
2 There are several flood types (river, coastal, flash flood, etc.) to consider in relation to weather forecasting. This study analyzes convective flash flood events from 2006 to 2011 in hopes of improving flash flood forecasts in Iowa. A flash flood is a type of flood that occurs within six hours of a causative event (WFO DMX Station Duty manual 2011). Flash floods can begin from a variety of situations, such as intense rainfall, dam failure, levee failure, ice jamming, etc. (WFO DMX Station Duty manual 2011). Forecasters can more easily predict the occurrence of precipitation, but predicting the location and amount of precipitation is difficult (Doswell et al. 1996, Junker et al. 1999). Ashley and Ashley (2008) find that flash floods are the top flood type causing flood-related fatalities and suggest that further research be done to specifically examine flash floods. Life-threatening flash floods are not common events, and knowledge of the antecedent variables contributing to flood events could prevent fatalities and damages (Doswell et al. 1996). Many studies propose the examination of relationships between flash floods and hydrological, surface, and atmospheric conditions to improve scientific understanding and forecasting of flash floods (Maddox 1996, Junker et al. 1999, Jessup and DeGaetano 2008, Ashley and Ashley 2008). Maddox, Chappell, and Hoxit were among the first meteorologists to attempt a list of common conditions that result in flash flood events. These features and classifications provided a foundation for future flash flood event research and will be compared to Iowa flash flood events in this study. Further studies have also examined common atmospheric features related to flash flood events. Funk (1991) suggests that forecasters use precise low-level moisture and available energy, jet-stream characteristics, and other conditions. Doswell et al. (1996) explore several general physical atmospheric relationships and recommend that forecasters be aware of sustained high rainfall rates of one inch/hour or greater, if high moisture values are present, because high moisture values could prevent entrainment. They also conclude that forecasters should also recognize slow system movement when considering flash flood potential. This study compares the conclusive criteria from Maddox et al. (1979) to flash floods occurring in Iowa. From 2006 to 2011, years varied from having many floods to having very few. This seems to be a representative range of time in which to compare events and analyze where forecast improvements could be made. This study hypothesizes that when environmental and antecedent conditions meet the criteria of Maddox et al. (1979), a flash flood event will occur in Iowa. Flood forecasting continues to improve from Maddox et al. (1979); however, their study still stands as a cornerstone for forecasters to build upon as forecasters explore the ways in which hydrological, surface, and atmospheric conditions affect flash flood events. Flood forecasting is not perfect, particularly when the public does not understand the uncertainty involved with it. However, scientists have not thoroughly examined all of the related variables regarding high precipitation events because there are many variables to consider. Additionally, it is difficult for them to come up with a set of criteria to fit all floods. Once this knowledge increases, flood forecasts will improve as well. 2. Data and methodology a. Case selection Case selection began with a study of National Weather Service (NWS) flash flood watches, warnings, and local storm reports compiled from the Iowa Environmental Mesonet (IEM). The verification study
Number of Watches 3 compared NWS Forecast Office in Des Moines, Iowa (NWS DMX) warnings and local storm reports over the NWS DMX county warning area (CWA) to watch issuances to determine the forecasts accuracy. Because watches only verify as accurate if a local storm report of flash flooding was received, it is important to note that there may have been other types of floods that occurred during an event but are not covered by this study. It should also be noted that there is error in using only local storm reports to verify an event because flash flood events often occur in rural areas of Iowa, and not all watches or warnings can be properly verified. When considering flash flood events, this study excludes winter flash flood events caused by ice jamming because these events are not the focus of the study. There were also not many winter flash flood events during the period (Figure 1). Cases were also excluded when they occurred during wet periods because antecedent soil moisture and precipitation were more likely to be the cause of the flash flood event than the atmospheric conditions. Cases were ultimately selected so an equal amount of each type would be represented. Two events of each of the following types were selected: 1. Watch and warning issued and flash flood was reported. 2. Watch issued and no flash flood was reported. 3. No watch issued and a flash flood was reported. 40 30 20 10 0 Winter Events and Watches per Year Excluded Winter Events 2006 2007 2008 2009 2010 2011 Year Figure 1. Number of winter flash flood events compared to number of flash flood watches per year during this study s period. Despite the fact that some cases did not have a flash flood reported, a weather event may have been predicted that led forecasters to issue a flash flood watch and/or warning. The events chosen for this study occurred on 14 October 2007, 25 April 2008, 10 May 2008, 7 July 2010, 9 August 2010, and 25 May 2011, and will be hereby referred to as case numbers 1 through 6, respectively (Table 1). Table 1. Description of cases analyzed in this study. Case Start (UTC) End (UTC) Flood Event Watch 1 10/14/2007 10/15/2007 Yes Yes 21:00 8:48 2 4/25/2008 4/25/2008 Yes Yes 2:00 16:53 3 5/11/2008 5/11/2008 No Yes 0:00 8:57 4 7/7/2010 7/7/2010 Yes No 8:00 18:00 5 8/9/2010 8/10/2010 Yes No 3:00 15:00 6 5/25/2011 8:00 5/26/2011 2:20 No Yes
4 b. Atmospheric data The environmental data used in this study is taken from the Iowa Environmental Mesonet (IEM), Storm Prediction Center (SPC) archive, National Climatic Data Center (NCDC) StormData, Wunderground online archive, University of Wyoming archived sounding data, and archived cases from the NWS DMX. IEM data included issuance information, NEXRAD images, and Midwest mesonet station plots. The issuance dataset consisted of all flash flood watches, warnings, and local storm reports for events from January 1, 2006 to November 1, 2011. The mesonet data consisted of hourly images of surface data and radar for three-hour periods right before, during, and after the event occurred. SPC and Wunderground archived data included ranges of the following parameters across the NWS DMX CWA: surface dew point (T d ), 850 hpa heights, precipitable water (Pwat), moisture transport, 0-1km shear, 0-6km shear, and effective shear. The NCDC StormData archive provided an event summary from each event s episode narrative. University of Wyoming archived sounding website provided archived sounding data for Case 3. Any additional data came from archived AWIPS (Advanced Weather Interactive Processing System) cases from the NWS DMX, which allowed visual representation of parameters necessary for comparison with Maddox et al. (1979) conditions and criteria. Soil moisture data presented a challenge during this study because soil moisture data is not available for the entire NWS DMX CWA on a temporal or spatial scale appropriate for comparison to atmospheric conditions and flash flood events. Data from the recent Soil Moisture and Ocean Salinity (SMOS) satellite is only available from 2009 to present, revisits sites only every three days, and has too large of grid spacing for this study (European Space Agency 2009). While climatological monthly data is available from the United States Soil Moisture Monitoring program, this is too large of a temporal scale to be useful in flash flood analysis, unless abnormal precipitation occurs during long periods of time. Despite the lack of soil moisture data, it is important to consider the antecedent soil moisture and its relationship to flash flood occurrences. Therefore, this study uses the normal monthly and annual precipitation values and compares them to the monthly and annual precipitation values associated with the six case dates. This study also includes storm precipitation total values from AWIPS and the NWS climatological archive. c. Case comparison to criteria The six cases that this study focuses on were compared to the conditions and criteria in Maddox et al. (1979). Their study provides a list of eight common atmospheric features that produce flash flood events. Their list of eight features is as follows: 1. Most flash floods are associated with convective storms. 2. Storms occur where surface dew points are high compared to climatological average. 3. Relatively high moisture contents are present through a deep tropospheric layer. 4. Weak to moderate vertical wind shear is present through the cloud depth. 5. Convective storms and/or cells move repeatedly over the same area. 6. A weak, mid-tropospheric meso-α scale trough helps to trigger and focus the storms. 7. The storm position is very near a midtropospheric, large-scale ridge position. 8. Storm occurs during the nighttime hours. The above criteria that can be measured quantitatively were compared to the six focus cases in this study based on the thresholds in Tables 2 and 3. Thresholds are taken from climatological data provided by the IEM, the
5 Wunderground archive, and the SPC definitions of strong shear. Table 2. Verification thresholds of weak to moderate shear for comparison to wind shear data. Criteria Threshold 0-1 km shear < 12 kts 0-6 km shear < 35 kts Effective shear < 25 kts Table 3. Verification thresholds for comparison to T d and Pwat data. Case T d Climate Avg ( F) Pwat Climate Avg (in.) 14 Oct 2007 42.6 0.53 25 Apr 2008 41.5 0.75 10 May 2008 46.1 0.93 7 Jul 2010 64.3 1.22 9 Aug 2010 64.2 1.1 25 May 2011 52.0 1.06 These thresholds are based on climatological averages for Des Moines, which is approximately the center of the NWS DMX CWA. There were no climatological averages of precipitable water values for NWS DMX, so an average of precipitable water data was taken between values from the National Weather Service offices in Davenport, IA and Omaha, NE. If the climatological average for precipitable water was less than the maximum and minimum values for the location or this average was greater than the minimum value for most of the time period, the value was considered to be greater than the climatological average and met the criteria. Because Maddox et al. (1979) criteria are quantitative and qualitative, most criteria need a qualitative analysis as well. This study defines convective storms as cells that produce lightning strikes for a reasonable duration (at least half an hour). It shows their motion and reflectivity using NEXRAD images from the IEM. Relatively high moisture content can be seen through precipitable water, but it can also be seen through high θ e values and moisture transport vectors. Precipitable water, θ e, and moisture transport vectors are taken from the SPC archived data. Weak to moderate vertical wind shear are quantified based on definitions of strong shear from the SPC. Shear can also be seen from magnitude changes with height when plotted from radiosonde data close to when a flash flood event occurs or is expected to occur. Therefore wind shear should meet criteria for magnitude in 0-1 km shear, 0-6 km shear, effective shear (Table 2), and (Figure 2) as given by Maddox et al. (1979). Figure 2. Maddox et al. (1979) ideal wind profile for comparison with radiosonde data for shear criteria. This study defines moving repeatedly over the same area to mean multiple convective cells or storms back building, developing, or moving slowly or over the same area. Radar and infrared satellite images from the periods will be used to show this. Particular emphasis is placed on storms/cells that are located over an area where a local storm report occurs. Additionally, this study defines a nighttime case as one that has at least half of its watch from 3Z to 12Z. Typically from March to October, it is between dusk and dawn from 3Z to 12Z in Iowa. If there was no flash flood watch issued for the event, the event is considered to have occurred from approximately its first flash flood report to its last flash flood report. Criteria relating to a
Watches 6 meso-α scale trough and a mid-tropospheric, large-scale ridge position are best defined visually (Figure 3). An overlay of each case s conditions was created using AWIPS and SPC data and compared to Figure 3. their data (Figure 3). This distribution implies that flash floods are most likely during the convective season (typically April to September in Iowa). Flash floods that are a direct result of atmospheric conditions are typically a result of convective weather. All six cases in this study were convective and produced precipitation. However, not all of the cases produced precipitation in the amounts and locations needed to create flash flood events. Iowa flash flood watch issuances from 2006 to 2011 (Figure 4) agree with the Maddox et al. (1979) distribution (Figure 5). This agreement indicates that NWS DMX forecasters found potential flood events were possible with a similar annual frequency. 30 Total Flash Flood Watches Issued per Month 2006-2011 25 20 15 10 5 0 J F M A M J J A S O N D Month Figure 4. Iowa flash flood annual distribution during this study s period. Figure 3. Maddox et al. (1979) ideal large scale set-up at 500 hpa, 850 hpa, and surface. 3. Results a. Convection Maddox et al. (1979) conclude that most flash floods are associated with convective storms. They give an average annual distribution of all flash flood types based on
7 Case 1 backbuilds (Figure 7), and cases 1, 2, 4, 5, and 6 have cells/storms that clearly strengthen. All cases have cells/storms that move very slowly over the same area (10-30 mph), and cases 5 and 6 have cells/storms that stay over the same location for an extended period of time (see Appendix Figures A1 through A5). Figure 5. Annual flood distribution from Maddox et al. (1979). b. Timing and Motion Maddox et al. (1979) determine that most flash flood events occur during nighttime hours. Cases 1, 2, 3, and 5 meet the criteria for a nighttime event (Figure 6). Nighttime events relate to heavy precipitation development because the low-level jet provides additional forcing at night. Figure 6. Shaded areas indicate duration of each event, while red boxes indicate nighttime criteria. Maddox et al. (1979) also find that flash floods are most likely when convective storms or cells move over the same area. Convective systems that move repeatedly over the same area or remain over an area for a long time often result in heavy precipitation over one area. All six cases meet the criteria for a storm or cell moving over the same area. Figure 7. Case 1 system shown by NEXRAD. The system moves slowly northeastward and builds from the south. Black arrow and box indicate overall storm motion. c. Shear This study consults 0-1 km, 0-6 km, and bulk effective shear to determine whether weak to moderate shear occurs. Weak to moderate shear, particularly 0-6 km shear, results in slow storm motion and therefore increases the chances of heavy precipitation over one area. Zero values in shear cases plotted in this study indicate values at least 5 kts less than the criteria. The SPC shear data archive does not plot these values. For the purposes of this study, cases with a shear value of zero can be classified as meeting the study s criteria. Cases 4 and 5 meet 0-6 km shear criteria (Figure 8).
0-1 km shear (kts) 0-1 km shear (kts) 0-6 km shear (kts) 8 Figure 8. 0-6 km shear must be less than 35 kts to meet Maddox et al. (1979) criteria. Cases 4 and 5 meet 0-1 km shear criteria (Figure 9). 30 25 20 15 10 5 0 60 50 40 30 20 10 0 0-6 km Shear vs. Criteria 0-6 km shear Criteria 0 1 2 3 4 5 6 Case Figure 9. 0-1 km shear must be less than 12 kts to meet Maddox et al. (1979) criteria. Cases 3, 4, and 5 meet 0-1 km shear criteria (Figure 10). 30 25 20 15 10 5 0 0-1 km Shear vs. Criteria 0-1 km shear Criteria 0 1 2 3 4 5 6 Case 0-1 km Shear vs. Criteria 0-1 km shear Criteria 0 1 2 3 4 5 6 Case Figure 10. Effective shear must be less than 25 kts to meet Maddox et al. (1979) criteria. When using radiosonde data in comparison with Figure 2, cases in which winds veer at the surface, are generally unidirectional beyond the surface, increase linearly with height, and are not strong for the time of year will be considered to meet criteria. Winds veering or backing at the surface keeps the updraft and downdraft separate within a cell and assists storm development. Unidirectional winds help a system maintain its structure, and winds that are not too strong allow a system to maintain its position long enough for heavy precipitation to fall. Cases 1, 2, 4, and 5 (see Appendix Figures A6 through A10) are similar to Figure 2 and meet the shear criteria (Figure 11). Figure 11. Case 1 radiosonde data. Winds veer near the surface, are generally unidirectional beyond the surface, and increase with height similarly to Figure 2. Based on all four shear comparisons, Cases 1, 2, 4, and 5 meet Maddox et al. (1979) shear criteria. d. Moisture Maddox et al. (1979) determine that deep moisture throughout the atmosphere is common with flash floods. When more
Precipitable Water (in) Dew Point ( F) 9 moisture is available for a system, it has the ability to produce heavier precipitation. This study examines precipitable water, surface dew point temperature, and moisture advection to show the overall moisture. Cases 1, 2, 4, 5, and 6 have above average precipitable water amounts throughout the duration of each event (Figure 12). 3 2.5 2 1.5 1 0.5 0 Precipitable Water vs. Climatological Average Min Max Clim. Avg 0 1 2 3 4 5 6 Case Figure 12. Precipitable water values for each case during the case date. Red boxes indicate the maximum value for that case date. Blue diamonds indicate the minimum value for that case date. Green triangles indicate the climatological average value for that case date. Cases 1, 2, 4, 5, and 6 meet the Maddox et al. (1979) criteria for having high dew point temperatures (Figure 13). 90 80 70 60 50 40 30 20 10 0 Dew Point vs. Climatological Average Avg Max Clim. Avg 0 1 2 3 4 5 6 Case Number Figure 13. Dew point values for each case during the case date. Red boxes indicate the maximum value for that case date. Blue diamonds indicate the 24-hour average value for that case date. Green triangles indicate the climatological average value for that case date. Cases 2, 4, and 5 have moderate to strong moisture transport and θ e into Iowa (Table 4 and Appendix Figures A11 through A16). Table 4. Strength of moisture advection during each case. Strong values meet criteria for high moisture content within the deep tropospheric layer. Case Number θ e Transport Strength at 850 hpa into Iowa 1 Strong 2 Strong 3 Moderate 4 Strong 5 Strong 6 Moderate Based on the moisture criteria, cases 1, 2, 4, and 5 have above normal moisture over a deep layer of the atmosphere. e. Meso-α scale trough and large-scale ridge Maddox et al. (1979) determine that most flash flood events occur near a weak, meso-α scale trough. Cases 1 (Figure 14) and 2
10 (Appendix Figure A17) occur while there is a shortwave trough (or low pressure system) and available energy from a local vorticity maximum, and they agree with Maddox et al. (1979). Case 3 is affected by a shortwave trough (Appendix Figure A18). Cases 4 (Appendix Figure A19) and 5 (Appendix Figure A20) set-up along a line of locally high vorticity, but they are not near a local meso-α scale trough. Case 6 has a set-up with a mature low pressure system, which has wrapped around vorticity (Appendix Figure A21). Maddox et al. (1979) also determine that most flash flood events occur near midtropospheric, large-scale ridge. Case 1 occurs on the west side of a 500 hpa ridge (Figure 14). This ridge extends back toward the flood report locations and continues to dig deeper before it moves out of the region. Case 2 is mostly in a trough with a main ridge in the eastern U.S. (Appendix Figure A17). Case 3 is mainly affected by a 500 hpa trough, despite the 500 hpa ridge on the east coast (Appendix Figure A18). Case 4 is wedged between a 500 hpa trough and ridge, but it is arguably more influenced by the ridge (Appendix Figure A19). Case 5 is under a 500hPa ridge (Appendix Figure A20). Case 6 is under a closed, 500 hpa low pressure system, which is the primary feature affecting it (Appendix Figure A21). f. Other large scale features The set-up for each case was also compared to Figure 3 at 500 hpa, 850 hpa, and the surface through data from AWIPS and the SPC online archive. Case 1 has the right entrance region of a jet streak over Iowa. The jet streak and 500 hpa heights match the 500 hpa of Figure 3, though Case 1 is not a mature low pressure system (Figure 14). The maximum moisture axis follows the flow into Iowa at 850 hpa (Figure 14). The moisture axis at the surface also follows the front, despite the fact that the surface low is not in the same position as in Figure 3 (Figure 14). Overall, Case 1 meets the criteria with upward motion and moisture present.
11 Figure 14. Clockwise from the upper left: 300 hpa winds (with a jet streak north of Iowa), 500 hpa heights and vorticity (vorticity maximums and minimums over Iowa), surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 00 Z 15 October 2007. Case 2 is in the right entrance and left exit regions of two jet streaks. The jet streak and 500 hpa heights match the 500 hpa of Figure 3, though Case 2 is not a mature low pressure system (Figure A17). The maximum moisture axis follows the flow into southwest Iowa at 850 hpa (Figure A17). The moisture axis at the surface also follows the front, despite the fact that the surface low is not in the same position as in Figure 3 (Figure A17). Overall, Case 2 meets the criteria similarly to Case 1. Case 3 has left exit region of a jet streak over southeast Iowa. The jet streak is deepening the 500 hpa trough (Figure A18), and the 500 hpa pattern does not match Figure 3. The moisture axis does not follow the flow into southwest Iowa at 850 hpa (Figure A18). The moisture axis at the surface follow between the warm and cold fronts, but the surface low is not over the area covered by Case 3 in Iowa (Figure A17). Overall, Case 3 does not meet the criteria because forcing in the pattern of Figure 3 does not occur in the Case 3 focus area. The Case 4 location is affected by the right entrance region of a large jet streak, which moves off to the northwest (Figure A19). It is then affected by the left exit region of a small, weaker jet streak (Figure A19). At 850 hpa, the moisture axis follows the flow northward into Iowa (Figure A19). At the surface, the strong moisture is positioned between the fronts. Overall, Case 4 meets the criteria because the set-up supplies moisture and a later small vorticity maximum. Case 5 jet streaks are too far north to affect Iowa (Figure A20). However, a line of positive vorticity extends northwest to southeast through Iowa later in time to provide energy. There is strong moisture at 850 hpa and at the surface; however, the surface fronts do not match Figure 3 (Figure A20). Overall, Case 5 does not meet the criteria because while strong moisture is present, the set-up is not similar enough to Figure 3. Case 6 jet streaks do not affect Iowa (Figure A21). At 500 hpa, the mature low pressure system wraps around positive vorticity and moisture at 850 hpa into Iowa (Figure A21). At the surface, the strongest moisture is between the fronts, but the front types do not match Figure 3 (Figure A21). Similarly to Case 5, Case 6 does not match the criteria from Figure 3. While strong moisture is present, the overall set-up does not match Figure 3.
Case 12 Overall, Cases 1, 2, and 4 generally follow atmospheric features as proposed by Maddox et al. (1979) (Figure 3). g. Antecedent soil conditions The antecedent soil moisture is measured by antecedent rainfall compared to the climatological normal in this study. The climatological monthly normal is calculated from the first day of the month through the case date and is based on data from 1971 to 2000. The climatological annual normal is calculated from January 1 st of that year through the case date and is also based on data from 1971 to 2000. Precipitation above normal can increase the chances of a flood occurring, particularly if the soil stays saturated. Results from this study show that cases 1, 2, 4, 5, and 6 received above normal precipitation for the month of their occurrence (Figure 15) (Table 5). Table 5. Locations had often received above normal precipitation from the first of that event s month to the event. Case Monthly Precip. by case date (in.) Normal Precip. for month (in.) 1 4.49 1.27 2 5.78 2.93 3 0.68 1.43 4 1.20 0.98 5 7.67 1.33 6 5.35 3.37 6 5 4 3 2 1 Monthly Percentage of Normal Precipitation 0% 200% 400% 600% Percent of Normal Figure 15. Cases above 100% of normal had received above normal precipitation from the first of the month to when the event from the case occurred. Above normal precipitation increases the chances of floods to occur. In addition, all six cases had above normal annual precipitation before they occurred (Figure 16). Table 6. Locations had often received above normal precipitation from January 1 st of the event s year until the event. Case Annual Precip. by case date (in.) Normal Precip. for Year (in.) 1 37.53 31.01 2 10.29 7.36 3 11.01 9.44 4 29.02 17.81 5 40.93 22.49 6 14.32 11.38 Monthly % of normal
Case 13 Annual Percentage of Normal Precipitation 4 5-6 5 5-6 6 6-8 6 5 4 3 2 1 0% 50% 100% 150% 200% Percent of Normal Annual % of Normal Figure 16. Cases above 100% of normal had received above normal precipitation from January 1 st to when the event from the case occurred. Above normal precipitation increases the chances of floods to occur. After seeing that most cases had received above-normal rainfall prior to their occurrence, it is also important to note the amount of precipitation resulting from each case (Table 7). These precipitation values are the maximum values for each system. If the soil conditions were already very moist, storm total precipitation values similar to Table 7 could cause a flash flood. Table 7. Storm total precipitation maximum values, which were taken from AWIPS. Case 3 did not have data on AWIPS, so data from the NWS Climatology was used. Case Storm Total Precipitation Maximum (Radarindicated) (in.) 1 6-8 2 5-6 3 0.47 *taken from NWS Climatology and not radar-indicated 4. Conclusion This study examines flash flood watches, warnings, and events from 2006 to 2011 in the NWS DMX CWA. Six cases are chosen for in-depth analysis and are compared to eight criteria from Maddox et al. (1979). Analysis data regarding convection, motion, timing, shear, dew point, available moisture content, and antecedent soil moisture is taken from the IEM, SPC, NCDC StormData, Wunderground, and University of Wyoming online data archives, as well as the NWS AWIPS. This study originally hypothesized that when environmental and antecedent conditions meet the criteria of Maddox et al. (1979), a flash flood event would occur in Iowa. Only one case (Case 1) completely agreed with this hypothesis. Cases 1 and 2, in which watches were issued and flash floods occurred, agreed best with the Maddox et al. (1979) criteria (Table 8). Cases 4 and 5 mostly agreed with Maddox et al. (1979) criteria except for the synoptic set-up or timing (Table 8). Cases 3 and 6, which did not have flash floods occur, had low moisture and shear values and disagreed with the timing or set-up of Maddox et al. (1979) criteria (Table 8). During comparison of synoptic setup at all levels (Figure 3), only Cases 1, 2, and 4 generally followed the atmospheric features as Maddox et al. (1979) proposed. Unfortunately, there are several major limitations in this study. Most limitations are covered in the methods section, but they are important to note. Firstly, flash floods are difficult to verify in rural areas, particularly in relation to timing. Therefore, watches and warnings cannot be verified as accurate unless a local storm report is submitted. Secondly,
14 not all data from each source was available for all of the six cases. This may result in errors in the dataset, particularly in storm precipitation totals. Thirdly, many of the Maddox et al. (1979) criteria have multiple measurements available, and measurements often occur at scale too large to accurately represent a flash flood. While this study is inconclusive, future research can further examine moisture content and vertical shear to determine the magnitude of an effect that these variables have on flash floods. Additionally, there are many more cases within this study (2006 to 2011) to be examined that could be compared to Maddox et al. (1979) criteria or further criteria. Each case is unique to its location and antecedent events or conditions, which makes flash flood forecasts challenging. As the understanding of environmental conditions related to flash flood events grows, forecasts can improve. Table 8. Results of comparisons between Cases 1-6 and Maddox et al. (1979) criteria. An X indicates that the case agreed with Maddox et al. (1979) criteria. Case Flood Event Convective Dew Point Moisture Content Vertical shear Same Area SW Trough Ridge Night 1 Yes X X X X X X X X 2 Yes X X X X X X X 3 No X X X 4 Yes X X X X X X 5 Yes X X X X X X X 6 No X X X Acknowledgements. The author wishes to thank Melinda Beerends at NWS and Dr. Kristie Franz at Iowa State University for their significant insight and guidance throughout this study. REFERENCES Ashley, S. T. and W. S. Ashley, 2008: Flood Fatalities in the United States. J. Appl. Meteor. Climatol., 47, 805 818. Ashley, W. S., 2007: Spatial and Temporal Analysis of Tornado Fatalities in the United States: 1880 2005. Wea. Forecasting, 22, 1214 1228. Doswell, C. A., H. E. Brooks, and R. A. Maddox, 1996: Flash Flood Forecasting: An Ingredients-Based Methodology. Wea. Forecasting, 11, 560 581. European Space Agency, cited 2009: SMOS Scientific Objectives. [Available online at http://www.esa.int/esalp/esas7c2vmoc_l Psmos_0.html.] Funk, Theodore W., 1991: Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event. Wea. Forecasting, 6, 548 564. Junker, N. W., R. S. Schneider, and S. L. Fauver, 1999: A Study of Heavy Rainfall Events during the Great Midwest Flood of 1993. Wea. Forecasting, 14, 701 712. Maddox, R. A., C. F. Chappell, and L. R. Hoxit, 1979: Synoptic and Meso-α Scale Aspects of Flash Flood Events 1. Bull. Amer. Meteor. Soc., 60, 115 123. Morss, Rebecca E., 2010: Interactions among Flood Predictions, Decisions, and Outcomes: Synthesis of Three Cases. Natural Hazards Review, 11, 3, 83. WFO DMX Station Duty Manual, Vol. 1, Section 5.2, 2011.
15 Roebber, P. J., and J. Eise, 2001: The 21 June 1997 Flood: Storm-Scale Simulations and Implications for Operational Forecasting. Wea. Forecasting, 16, 197 218
16 Appendix Figure A3. Case 4 system as shown on NEXRAD. The system moves slowly northeastward and strengthens. Figure A1. Case 2 system as shown on NEXRAD. The system moves slowly eastward. Figure A4. Case 5 system as shown on NEXRAD. The system moves eastward. Figure A2. Case 3 system as shown on NEXRAD. The\ system moves slowly east. Figure A5. Case 6 as shown on NEXRAD. The system has cyclonic rotation as it propogates eastward and brings heavy precipitation to the same area.
17 Figure A6. Case 2 radiosonde data. Winds veer near surface, increase with height, and are unidirectional beyond the surface (similarly to Figure 2). They are not strong for the time of year (April). Figure A8. Case 4 radiosonde data. Winds veer near the surface and are generally unidirectional. Winds increase fairly linearly with height and are not strong for the time of year (July). Figure A7. Case 3 radiosonde data. Winds veer near surface, increase with height, and are unidirectional beyond the surface (similarly to Figure 2). However, winds are strong at most levels (50 kts or greater), which makes the system fast-moving. Figure A9. Case 5 radiosonde data. Winds veer near the surface and are unidirectional at mid-levels. Wind magnitude varies with height and is weak.
18 Figure A10. Case 6 radiosonde data. Winds do not veer near the surface and are unidirectional only at mid-levels. Wind magnitude varies greatly. Figure A12. Case 2 has strong moisture advection into central Iowa at 06Z. Figure A13. Case 3 has its strongest moisture moving east of Iowa and Missouri at 03Z. Figure A11. Case 1 has strong moisture advection into southwest Iowa at 06Z.
19 Figure A14. Case 4 has its strongest moisture advection into Iowa occurring at 09Z, into eastern Iowa. Figure A15. Case 5 has very strong moisture advection eastward across Iowa at 09Z. Figure A16. Case 6 has its strongest moisture advection into Iowa at 00Z, but the strongest moisture advection for the system is directed east of Iowa.
20 Figure A17. Clockwise from the upper left: 300 hpa winds (with a jet streak southwest of Iowa), 500 hpa heights and vorticity (vorticity maximums over Iowa), surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 06 Z 25 April 2008 (Case 2). Figure A18. Clockwise from the upper left: 300 hpa winds (with a jet streak south of Iowa), 500 hpa heights and winds, surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 06 Z 11 May 2008 (Case 3).
21 Figure A19. Clockwise from the upper left: 300 hpa winds (with a jet streak northwest of Iowa), 500 hpa heights and vorticity, surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 12 Z 7 July 2010 (Case 4).
22 Figure A20. Clockwise from the upper left: 300 hpa winds (with a jet streak northwest of Iowa), 500 hpa heights and vorticity, surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 06 Z 8 Aug 2010 (Case 5).
23 Figure A21. Clockwise from the upper left: 300 hpa winds (with a small jet streak in southern Iowa), 500 hpa heights and vorticity, surface pressure, surface fronts, and surface dew points (shaded), and 850 hpa heights and dew points (shaded). Data is from 12 Z 25 March 2011 (Case 6).