Northern Hemispheric Flood Fingerprints Katie Walls The Pennsylvania State University December 16, 2008

Motivation Flooding causes billions of dollars in damage every year across the Northern Hemisphere The synoptic patterns involved share common patterns, or fingerprints The configuration of the anomalies in relation to the flooding event Root et al. (2007) found repeatable U.S. mid-Atlantic flood fingerprints

Hypothesis There are common fingerprints for the mid-latitudes (20° to 60°) of the Northern Hemisphere Four different atmospheric variables involved in identification Sea Level Pressure SLP Precipitable Water PWAT 850 hPa U-wind 700 hPa V-wind

Hypothesis Cont. Six fingerprints identified using rotated Empirical Orthogonal Functions (EOFs) Each rotated EOF represents one synoptic pattern and consists of four atmospheric variables

Case Selection Over 300 flooding events from three sources National Climate Data Center's event database CMORPH Encyclopedia Britannica disaster articles from 1979 to 1999 Surface rainfall totals unavailable outside of the U.S. – need an objective method to assess rainfall Japanese 25-year Reanalysis (JRA25) data Validated via comparison of JRA25 data with North American COOP reports

Flood Event Locations 200 Events taken from North America, Europe, and Asia where at least 2 in. (~50mm) of rain fell in an 18-24 hr. period

Standardized Anomalies Four atm. variables extracted from NCEP-NCAR Global Reanalysis dataset (17 pressure levels on 2.5º by 2.5º grids) for each event Standardized anomalies SA calculated for each field on a 9 by 9 grid (22.5º by 22.5º) surrounding flood event L Sea Level Pressure

Mitigate effects of seasonal variation At each grid point: A is the atmospheric variable value µ is the mean of the 17-day average centered on the flood date σ is the value of one standard deviation based on a 30-year climatology. Next, calculate the eigenvectors of the SA fields

Rotated EOFs Basically reduce a data set to a smaller data set that contains linear combinations of the original data Reveal synoptic patterns by displaying the most variation amongst all cases - fingerprints Six-factor oblique rotation reveals most meaningful meteorological synoptic patterns Six distinct fingerprints represent 61% of the variance of floods across the Northern Hemisphere Flooding events are described by a combination of multiple EOF rotations

Summary Flood events are categorized using obliquely rotated EOF analysis, based on standardized anomalies Oblique rotation reveals 6 fingerprints that explain 61% of the variance amongst 200 mid-latitude Northern Hemispheric floods Identification of such patterns can advance flood forecasting and prevent life and property loss in the future

Future Work Add more atmospheric fields to methodology Use standardized anomalies from ERA and JRA datasets Search for flood fingerprints in predicted model anomaly fields Apply methodology to other weather hazards

Acknowledgements Paul Knight Nels Shirer George Young Sue Ellen Haupt Rich Grumm Sonya Miller The Pennsylvania State Climatology Office COOP University of Reading-World Weather News Those who have supported me throughout my graduate experience