Using Geographic Information Systems to Quantify the Occurrence of Severe Weather Phenomena Jeffrey...
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Using Geographic Information Systems to Quantify the Occurrence of Severe Weather Phenomena Jeffrey B. Basara and James E. Hocker Oklahoma Climatological Survey, University of Oklahoma, Norman, Oklahoma 1. Introduction Severe thunderstorms are an important and relatively common component to the annual weather across the state of Oklahoma. Such weather brings hazardous features such as large hail, damaging winds, and tornadoes, while also providing beneficial precipitation vital to the state’s agricultural and hydrological needs. Recent studies have combined WSR-88D radar observations and geographic information systems (GIS) applications to gain an increased understanding of the spatial and temporal distribution of severe weather in Oklahoma. The application of GIS to operational meteorology (Waters et al., 2005; Bunting et al., 2005) as well as meteorological research (Yuan et al., 2002; McIntosh and Yuan, 2005) has increased significantly in recent years establishing the technology as a new platform for meteorological and climatological analysis. This demonstration study was conceived to combine the use of NEXRAD radar data archives with GIS technologies to visualize and analyze the spatial patterns of multi-year storm occurrences. The results have revealed new insights into the frequency, duration, track length, and motion of squall lines and supercells over a 10-year period. In addition, a separate 3-year pilot study has also demonstrated the unique attributes of utilizing GIS to estimate hail occurrence. 2. Ten-Year Oklahoma Supercell and Squall Line Climatology a. Events Event days for the study were selected using a set of storm report criteria across the domain shown in Figure 1.Significant severe weather events were defined as any single convective day (1200–1159 UTC) when: (1) the total combined severe storm reports (hail and wind) was greater than or equal to 20 or (2) any tornado was reported in Oklahoma. A total of 332 separate severe weather event days were identified between 1994 and 2003 and all were analyzed for the occurrence of squall lines. b. Methodology NEXRAD Level-II and Level-III radar data were acquired from the National Climatic Data Center (NCDC). Level-II data was used as a first choice for the cases while Level-III was acquired as a supplement or replacement for any missing Level-II data. Two main software packages were used to analyze radar data for the 12 year climatology. For Level-II data a program entitled GRLevel2 was used to both view and track supercells and squalls lines. Level-III data was viewed and analyzed via NCDC’s online Java NEXRAD viewer. 3. Three-Year Southern Plains Hail Climatology With recent technological advances, such as radar-based hail detection algorithms and geographic information systems (GIS) applications, alternate methods for quantifying hail occurrence are available. Three years of hail occurrence were investigated in this study, from 2001 through 2003, across the domain which included portions of eight states (Arkansas, Colorado, Kansas, Louisiana, Missouri, New Mexico, Oklahoma, and Texas). To quantify hail occurrence across the plains, GIS and radar data were utilized to increase the understanding of the spatial and temporal variability of severe hail. The Weather Decisions Technologies (WDT) Hailswath algorithm was used to create swaths for all storms capable of producing severe hail. This method reduced the human impact, and potential human bias, on the analysis. While the method chosen was not a perfect solution, it served as a demonstration study for alternate analyses of hail quantification. To determine a list of potential hail days, Storm Data was used as a first guess. Of the 1095 days in the 3-year period, 535 potential hail days were identified (an impressive 48.9 percent of the total days), though the number of hail days from the initial search was larger than the final number of cases in the analysis. Additional steps in the data processing narrowed the list of hail days by determining dates without hail in the study domain The methodology used in this study to create hail swaths is detailed with many involved steps. To help clarify each step, Figure 7 provides a graphical illustration of the methodology. A key hypothesis was confirmed by the analyses depicted in Figure 8; the methodology utilized allows for the calculation of hail potential. Determining an exact quantity of severe hail storms at a given location is extremely difficult. However, this study revealed the potential for severe hail in and around a given location by integrating radar observations and GIS techniques. 4. For Further Reading Basara, J. B., D. R. Cheresnick, D. Mitchell, and B. G. Illston, 2007: An analysis of Severe Hail Swaths in the Southern Plains of the United States. Trans. in GIS, 11, 531-554. Hocker, J. E., and J. B. Basara, 2007: A ten year spatial climatology of squall line storms across Oklahoma. Intl. J. of Climo., DOI: 10.1002/joc. 1579. Hocker, J. E., and J. B. Basara, 2008: A geographic information systems based analysis of supercells across Oklahoma from 1994 – 2003. J. Appl. Meteor., in press. 5. References Bluestein, H. B., and M. H. Jain, 1985: Formation of mesoscale lines of precipitation: Severe squall lines in Oklahoma during the spring. Journal of the Atmospheric Sciences, 42, 1711–1732. Bunting, B. L., L. Bucklew, P. Kirkwood, S. Rae., 2005: The graphical severe weather warning initiative at the fort worth national weather service. Proceedings of the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, 8–14 January 2005, American Meteorological Society: San Diego, CA, Boston, MA, unpaginated CD-ROM. Klimowski, B. A., M. J. Bunkers, M. R. Hjelmfelt, and J. N. Covert, 2003. Severe convective windstorms over the northern high Plains of the United States. Weather and Forecasting, 18, 502–519. McIntosh, J., and M. Yuan, 2005: Assessing similarity of geographic processes and events. Transactions in GIS, 9, 223–245. Waters, K. R., J. R. Coyne, P. L. Wolf, J. T. Schaefer, J. M. Looney, S. Naglic, B. W. MacAloney II, M. A. Tew, J. Lorens, R. J. Okulski, and N. O. Schwein, 2005: Polygon weather warnings–a new approach for the National Weather Service. Proceedings of the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, c. Results A total of 943 supercells and 477 squall lines were identified across Oklahoma from 1994 to 2003. GIS analyses revealed the relative spatial frequencies of each storm type statewide as well as mean storm initiation locations and storm tracks. Total and monthly supercell results are shown below in Figures 3 and 4. Similar results for squall lines are illustrated in Figures 5 and 6. Several criteria were developed to identify supercell storms and squall lines for the climatology. Supercells were required to: • Contain a mesocyclone with an azimuthal velocity differential greater than 7.7 m/s (15 knots) at base level, and • Persist for 30 minutes or greater. Initiation was based on the first occurrence of a 40 dBz echo and termination was based on loss of all supercell characteristics. Supercells were tracked following the region within the forward flank just north of the storm inflow. The intent of the criteria was to capture the full spectrum of supercell types as opposed to capturing only the most severe, classic-type storms that are studied most frequently. Figure 1. KTLX base reflectivity at 00:07:25 UTC on 4 May 1999 overlaid with supercell storm tracking features. Consistent with the efforts of Bluestein and Jain (1985) and Klimowski et al. (2003), squall lines were determined based on the following criteria: • Length of 50 km or greater, • Length to width ratio of at least 5:1, and • Persist for 30 minutes or more. Initiation was taken to be the first time at which all the criteria were met and termination was the time at which any of the criteria failed. Squall lines were tracked using the central feature of the line as well as the two end points. Figure 2 shows an example of squall line tracking. Figure 2. KTLX base reflectivity at 03:53:54 UTC on 28 May 2007 overlaid with squall line storm tracking features. Supercell Results Supercell Results Squall Line Results Squall Line Results April Figure 3. Spatial frequency of all supercells during 1994-2003. May June July August September October Figure 5. Spatial frequency of all squall lines during 1994-2003. Figure 4 (above). Monthly supercell frequencies and track histograms. Figure 6 (above). Monthly squall line frequencies and track histograms. Figure 8. A graphical representation of the hail study methodology Figure 8. Analyzed severe hail occurrence for the period spanning 2001-2003
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Transcript of Using Geographic Information Systems to Quantify the Occurrence of Severe Weather Phenomena Jeffrey...
Using Geographic Information Systems to Quantify the Occurrence of Severe Weather Phenomena
Jeffrey B. Basara and James E. HockerOklahoma Climatological Survey, University of Oklahoma, Norman, Oklahoma
1. Introduction
Severe thunderstorms are an important and relatively common component to the annual weather across the state of Oklahoma. Such weather brings hazardous features such as large hail, damaging winds, and tornadoes, while also providing beneficial precipitation vital to the state’s agricultural and hydrological needs. Recent studies have combined WSR-88D radar observations and geographic information systems (GIS) applications to gain an increased understanding of the spatial and temporal distribution of severe weather in Oklahoma. The application of GIS to operational meteorology (Waters et al., 2005; Bunting et al., 2005) as well as meteorological research (Yuan et al., 2002; McIntosh and Yuan, 2005) has increased significantly in recent years establishing the technology as a new platform for meteorological and climatological analysis.
This demonstration study was conceived to combine the use of NEXRAD radar data archives with GIS technologies to visualize and analyze the spatial patterns of multi-year storm occurrences. The results have revealed new insights into the frequency, duration, track length, and motion of squall lines and supercells over a 10-year period. In addition, a separate 3-year pilot study has also demonstrated the unique attributes of utilizing GIS to estimate hail occurrence.
2. Ten-Year Oklahoma Supercell and Squall Line Climatology
a. Events
Event days for the study were selected using a set of storm report criteria across the domain shown in Figure 1.Significant severe weather events were defined as any single convective day (1200–1159 UTC) when:
(1) the total combined severe storm reports (hail and wind) was greater than or equal to 20 or
(2) any tornado was reported in Oklahoma.
A total of 332 separate severe weather event days were identified between 1994 and 2003 and all were analyzed for the occurrence of squall lines.
b. Methodology
NEXRAD Level-II and Level-III radar data were acquired from the National Climatic Data Center (NCDC). Level-II data was used as a first choice for the cases while Level-III was acquired as a supplement or replacement for any missing Level-II data.
Two main software packages were used to analyze radar data for the 12 year climatology. For Level-II data a program entitled GRLevel2 was used to both view and track supercells and squalls lines. Level-III data was viewed and analyzed via NCDC’s online Java NEXRAD viewer.
3. Three-Year Southern Plains Hail Climatology
With recent technological advances, such as radar-based hail detection algorithms and geographic information systems (GIS) applications, alternate methods for quantifying hail occurrence are available. Three years of hail occurrence were investigated in this study, from 2001 through 2003, across the domain which included portions of eight states (Arkansas, Colorado, Kansas, Louisiana, Missouri, New Mexico, Oklahoma, and Texas). To quantify hail occurrence across the plains, GIS and radar data were utilized to increase the understanding of the spatial and temporal variability of severe hail. The Weather Decisions Technologies (WDT) Hailswath algorithm was used to create swaths for all storms capable of producing severe hail. This method reduced the human impact, and potential human bias, on the analysis. While the method chosen was not a perfect solution, it served as a demonstration study for alternate analyses of hail quantification. To determine a list of potential hail days, Storm Data was used as a first guess. Of the 1095 days in the 3-year period, 535 potential hail days were identified (an impressive 48.9 percent of the total days), though the number of hail days from the initial search was larger than the final number of cases in the analysis. Additional steps in the data processing narrowed the list of hail days by determining dates without hail in the study domain The methodology used in this study to create hail swaths is detailed with many involved steps. To help clarify each step, Figure 7 provides a graphical illustration of the methodology.
A key hypothesis was confirmed by the analyses depicted in Figure 8; the methodology utilized allows for the calculation of hail potential. Determining an exact quantity of severe hail storms at a given location is extremely difficult. However, this study revealed the potential for severe hail in and around a given location by integrating radar observations and GIS techniques.
4. For Further ReadingBasara, J. B., D. R. Cheresnick, D. Mitchell, and B. G. Illston, 2007: An analysis of Severe Hail Swaths in the Southern Plains of the United States. Trans. in GIS, 11, 531-554.
Hocker, J. E., and J. B. Basara, 2007: A ten year spatial climatology of squall line storms across Oklahoma. Intl. J. of Climo., DOI: 10.1002/joc. 1579.
Hocker, J. E., and J. B. Basara, 2008: A geographic information systems based analysis of supercells across Oklahoma from 1994 – 2003. J. Appl. Meteor., in press.
5. References
Bluestein, H. B., and M. H. Jain, 1985: Formation of mesoscale lines of precipitation: Severe squall lines in Oklahoma during the spring. Journal of the Atmospheric Sciences, 42, 1711–1732.
Bunting, B. L., L. Bucklew, P. Kirkwood, S. Rae., 2005: The graphical severe weather warning initiative at the fort worth national weather service. Proceedings of the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, 8–14 January 2005, American Meteorological Society: San Diego, CA, Boston, MA, unpaginated CD-ROM.
Klimowski, B. A., M. J. Bunkers, M. R. Hjelmfelt, and J. N. Covert, 2003. Severe convective windstorms over the northern high Plains of the United States. Weather and Forecasting, 18, 502–519.
McIntosh, J., and M. Yuan, 2005: Assessing similarity of geographic processes and events. Transactions in GIS, 9, 223–245.
Waters, K. R., J. R. Coyne, P. L. Wolf, J. T. Schaefer, J. M. Looney, S. Naglic, B. W. MacAloney II, M. A. Tew, J. Lorens, R. J. Okulski, and N. O. Schwein, 2005: Polygon weather warnings–a new approach for the National Weather Service. Proceedings of the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, 8–14 January 2005, American Meteorological Society: San Diego, CA; Boston, MA, unpaginated CD-ROM.
Yuan, M., M. Dickens-Micozzi, and M. A. Magsig, 2002: Analysis of tornado damage tracks from the 3 May tornado outbreak using multispectral satellite imagery. Weather and Forecasting, 17, 382–398.
c. Results
A total of 943 supercells and 477 squall lines were identified across Oklahoma from 1994 to 2003. GIS analyses revealed the relative spatial frequencies of each storm type statewide as well as mean storm initiation locations and storm tracks. Total and monthly supercell results are shown below in Figures 3 and 4. Similar results for squall lines are illustrated in Figures 5 and 6.
Several criteria were developed to identify supercell storms and squall lines for the climatology. Supercells were required to:
• Contain a mesocyclone with an azimuthal velocity differential greater than 7.7 m/s (15 knots) at base level, and• Persist for 30 minutes or greater.
Initiation was based on the first occurrence of a 40 dBz echo and termination was based on loss of all supercell characteristics. Supercells were tracked following the region within the forward flank just north of the storm inflow. The intent of the criteria was to capture the full spectrum of supercell types as opposed to capturing only the most severe, classic-type storms that are studied most frequently.
Figure 1. KTLX base reflectivity at 00:07:25 UTC on 4 May 1999 overlaid with supercell storm tracking features.
Consistent with the efforts of Bluestein and Jain (1985) and Klimowski et al. (2003), squall lines were determined based on the following criteria:
• Length of 50 km or greater,• Length to width ratio of at least 5:1, and• Persist for 30 minutes or more.
Initiation was taken to be the first time at which all the criteria were met and termination was the time at which any of the criteria failed. Squall lines were tracked using the central feature of the line as well as the two end points. Figure 2 shows an example of squall line tracking.Figure 2. KTLX base reflectivity at 03:53:54 UTC on 28 May 2007
overlaid with squall line storm tracking features.
Supercell ResultsSupercell Results Squall Line ResultsSquall Line Results
April
Figure 3. Spatial frequency of all supercells during 1994-2003.
May
June
July
August
September
October
Figure 5. Spatial frequency of all squall lines during 1994-2003.
Figure 4 (above). Monthly supercell frequencies and track histograms. Figure 6 (above). Monthly squall line frequencies and track histograms.
Figure 8. A graphical representation of the hail study methodology
Figure 8. Analyzed severe hail occurrence for the period spanning 2001-2003
