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Olivia Kellner Ph.D. Candidate, Purdue University Climate Specialist, Indiana State Climate Office Photos: Doyle McIntosh 2014 Indiana GIS ConferenceMay.

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Presentation on theme: "Olivia Kellner Ph.D. Candidate, Purdue University Climate Specialist, Indiana State Climate Office Photos: Doyle McIntosh 2014 Indiana GIS ConferenceMay."— Presentation transcript:

1 Olivia Kellner Ph.D. Candidate, Purdue University Climate Specialist, Indiana State Climate Office Photos: Doyle McIntosh 2014 Indiana GIS ConferenceMay 8, 2014

2 Founding science and hypothesis Data Climatology Methods Findings Geospatial Analysis Methods Maps Findings Conclusions http://www.angelfire.com/theforce/storm_chasingf5/Historical%2 0and%20Major%20Tornado%20Outbreaks%20the%20one.htm http://www.srh.noaa.gov/ohx/?n=april319 74_40thanniversary http://www.crh.noaa.gov/ilx/event s/may302004/040530_rpts.gif Kellner, O. and D. Niyogi, 2013, Land-surface Heterogeneity Signature in Tornado Climatology? An Illustrative Analysis over Indiana 1950-2012, Earth Interactions, e-view, doi: http://dx.doi.org/10/1175/2013EI000548.1. Presentation Outline:

3 Founding science:  Land-surface heterogeneity: where the land cover or land use is not uniform across an area  Leads to a heterogeneous boundary layer in terms of temperature, dew points, vertical velocities, and winds Mahmood et al., 2011 Fig. 5. Inner domain average modeled (a) relative humidity, (b) dew point temperature, (c) ground temperature, (d) two-meter temperature, and (e) planetary boundary layer height for control, bare soil, grassland, and forest. Mahfouf et al., 1987  Can these surface discontinuities modify the boundary layer enough to impact storm dynamics and evolution?

4 From Brown and Arnold, 1998: Figure 6. Spatial distribution for all convective cloud masses(dots, both initial and vertically enhanced) for 34 weak synoptic flow days, July–August, 1986–1991, in the aggregate. From Changnon et al., 1991 Journal of Applied Meteorology

5 From Brown and McCann, 2004

6 Indiana’s land surface, rich with physiographic boundaries, land-surface heterogeneity, topography, and distinct, isolated urban regions may influence the evolution of convective weather (specifically tornado touchdown locations). http://media.wfyi.org/NaturalHeritage/learn/regions.htmlhttps://ou-gisapplications.wikispaces.com/Indiana+Land+Usehttp://pubs.usgs.gov/of/2004/1451/rupp/

7 Climatology Storm Prediction Center (SPC) Storm reports, available in their Severe Weather Database Files Inclusive of Date Time Touchdown in lat/long County F-scale Injuries Fatalities SPC SVRGIS webpage: http://www.spc.noaa.gov/gis/svr gis/ Tornado touchdown points States Cities Counties Population Density (2010 raster file, density per square kilometer) Land cover: U.S.G.S Enhanced Historical Land-use and Land- cover Data sets DEM: Ball State University Geospatial Data

8 Implementation of.csv files of storm data into Excel Sort data by: Date Time F-scale Compute tornado days and climatological data by parameters investigated Month Year F-scale Weak (F0-F1) and Strong (F2-F5) Increase/decrease in annual tornado days Also investigated antecedent rainfall at 1, 3, and 6 month periods and ENSO phase to annual number of tornado days

9 Most active time of day weak tornadoes: 4-7pm LST; strong tornadoes: 2-4pm and 5-8pm LST; all tornadoes 4-8pm LST Majority of Indiana’s tornadoes are weak tornadoes (50%) 30-year moving averages show no increase or decrease in annual tornado days 30-year moving averages by climate division show an increase in annual tornado days in southern most climate divisions from 1 day a year to 3 days a year ENSO: rate at which ENSO changes phase appears to relate to more active seasons in Indiana Weak relationship between 6- month antecedent drought conditions and number of tornado days This shift is a result of the windshear environment more common with strong tornadoes

10 Dr. T. T. Fujita, University of Chicago

11 Spatial analyst tools: Kernel density Map algebra Slope calculator Conversion tools Analysis tools: Buffer “Select features within”

12 Changes in elevation Change in slope of 5 degrees or more over a distance of ~100 meters Change in land cover 6 classes Forest Urban Agriculture Barren Wetlands/water bodies Range land Urban areas City centroids Urban area shapefiles Population density People per square kilometer

13 http://jasonahsenmacher.wordpress.com/category/terrain/ http://pubs.usgs.gov/of/2004/1451/rupp/ Is this happening here in Indiana?

14 ~1 mile ~9 miles Tornado “rings” ? ~Noted by Fujita in other cities such as Chicago in early 1970s

15

16 Percentage of Total Tornadoes 1950-2012 (1285 total) within 1-4 km of Different 2010 Population Density Classes (People/km 2 ) ClassClass Range:1 km2 km3 km4 km Class 2238-84739516067 Class 3848-1,77924303541 Class 41,780-3,30910131619 Class 53,310-6,4971234 Class 66,498-13,8790001 Correlation: -0.79 -0.79 -0.80 -0.80 An indirect relationship: higher percentage of tornado touchdown points in land area with lower populations However, the spatial distribution close to major cities towns suggest a population bias…

17  Spatially different patterns -> La Niña more concentrated touchdown locations  In terms of climatology, no year has a greater risk for more tornadoes  Transition between phases appears to contribute to active and less active tornado years  Spatially different patterns -> La Niña more concentrated touchdown locations  In terms of climatology, no year has a greater risk for more tornadoes  Transition between phases appears to contribute to active and less active tornado years

18 Meteorology & climatology are very cartographically intensive sciences (forecasters constantly look at & analyze maps)! Sadly, a gap between those that know meteorology & the benefits of geospatial analysis is present Indiana tornado days have not increased or decreased through time Note that tornado days are not the same as tornadoes! Any given day can have 1 – 20+ tornadoes Several land surface relationships may be occurring topography physiographic regions land use : 42 % & 64% touched down within 1 km of forest & urban land areas, respectively All tornadoes: 43% & 61% touched down within 1 km of forest and urban, respectively Supports land-surface heterogeneity hypotheses: Boundaries of temperature, dewpoints, CAPE, vertical velocities, & surface roughness when transitioning from one land use to another

19 Thank you! - Questions?!?! Special thanks to Dr. David L. Arnold & Tim Samaras for inspiration and devotion to novel, challenging research seeking to unravel the unsolved mysteries of severe weather & tornadoes NWS Indianapolis for continued support Dev Niyogi & the Indiana State Climate Office Email: okellner@purdue.edu


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