Evan Webb NOAA/National Weather Service Forecast Office Grand Rapids, MI USING GIS TO ENHANCE IMPACT-BASED WEATHER WARNINGS

OUTLINE Objectives Starting Point: Winter NWS Grand Rapids Impact Graphic Winter Storm Impact Index (WSII) – NWS Burlington, VT Role of GIS Further Development

OBJECTIVES Implement 5 color risk-based alert system to provide intuitive, consistent long-fused weather hazard information Leverage Geographic Information Systems (GIS) to integrate NWS gridded forecasts with other data sets to assess community hazard exposure and potential impacts Other Data Sets? Land Use Population Density Infrastructure (Hospitals, Interstates, Schools, etc.) Climatology Provide more objective, scientifically-based starting point for potential weather impacts

Winter Prototype First populated with snowfall forecast Hand-edited Subjective IMPACT GRAPHIC – WFO GRAND RAPIDS Immediate – Life Saving Action Extremely Life Threatening Everything Will be Shut Down Possibly for Days or Weeks Be Prepared – Major Actions Expect Dangerous Conditions Expect Major Disruption of Normal Activities Be Aware – Minor Actions Caution – Especially When Travelling Plan to Be Inconvenienced Little to No Action Little to No Impact on Daily Life Plan on Minor Inconvenience Created March 1, 2014

WSII – WFO BURLINGTON, VT WSII Components: Snow Load Index Snow Amount Index Uses maximum impact of either snow amounts or snow rate Sperry-Piltz Ice Index Blowing Snow Index Factors include wind gusts, snow amounts, snow ratios, land use

MARCH 1, 2014 EXPECTED IMPACTS

MARCH 1, 2014 OBSERVED SNOWFALL

EXPECTED IMPACTS VS. OBSERVED SNOWFALL March 1, 2014 Snowfall Summary:

Employ GIS and Python scripts to automate processing of algorithms/impact graphic creation Several scripts automate procedure of downloading National Digital Forecast Database grids Algorithms classify weather elements and modify values based on climatology, land use, etc. ROLE OF GIS NCDC Snowfall Climatology

Attempts to forecast where blowing snow could impact travel (6 hour wind gust reclassified) x (6 hour snow ratio) x ( 6 hour snow amount) x Land Use factor BLOWING SNOW INDEX – WFO BURLINGTON, VT Maximum wind gust calculated every 6 hours Reclassified to the following based on least amount of friction (Plains): 1 = = = = = = = = = = > 50

Water Perennial ice Bare rock/sand Row crops Small grains Fallow Pasture Grassland Shrubland Transitional Urban grass Low intensity residential Orchards/vineyards High intensity residential Commercial/industrial Quarries Herbaceous wetlands 5 (100%) Low Friction 5 (100%) Low Friction Deciduous forest Evergreen forest Mixed forest Woody wetland 1 (10%) High Friction 1 (10%) High Friction 4 (75%) 4 (75%) 3 (50%) 3 (50%) 2 (25%) 2 (25%)

The SPIA Index was developed to provide decision support to emergency management officials, utility companies and the public during the hours and days leading up to an ice storm. The index quantifies the potential for electrical interruptions, and thereby gives more tangible information to the public concerning the extent of preparations thought necessary. SPERRY-PILTZ ICE INDEX

Use GIS to derive impact level forecast Meteorological variables Land Use Population Density Infrastructure Deciduous Tree Leaf-out Pre-storm conditions Ground temps, soil moisture, etc. Continued collaboration with NWS Burlington, VT to calibrate algorithms Communicating the meteorological threat info is key GIS-based impact index could improve decision support to all partners, including the public Use GIS to more accurately predict impacts and communicate them more effectively Appropriate response in preparation Saves lives Saves money SUMMARY / FUTURE WORK