Evan Webb

NOAA/National Weather Service Forecast Office Grand Rapids, MI

USING GIS TO ENHANCE IMPACT-BASED WEATHER WARNINGS

OUTLINE

• Objectives

• Starting Point: Winter 2013-2014 NWS Grand Rapids Impact Graphic

• Winter Storm Impact Index (WSII) – NWS Burlington, VT

• Role of GIS

• Further Development

www.weather.gov/grandrapids

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

www.weather.gov/grandrapids

• Winter 2013-2014 Prototype

• First populated with snowfall forecast

• Hand-edited

• Subjective

IMPACT GRAPHIC – WFO GRAND RAPIDS

www.weather.gov/grandrapids

Immediate – Life Saving Action Extremely Life Threatening Everything Will be Shut Down Possibly for Days or Weeks

Be Prepared – Major Actions Expect Dangerous ConditionsExpect Major Disruption of Normal Activities

Be Aware – Minor Actions Caution – Especially When TravellingPlan 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

www.weather.gov/grandrapids

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

www.weather.gov/grandrapids

MARCH 1, 2014 OBSERVED SNOWFALL

www.weather.gov/grandrapids

EXPECTED IMPACTS VS. OBSERVED SNOWFALL

www.weather.gov/grandrapids

http://www.crh.noaa.gov/images/grr/presentations/March_1_Snowfall_Summary_Revised_2014-03-02_15-38-52.pdfMarch 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

www.weather.gov/grandrapids

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 = 0 - 152 = 15 - 193 = 19 - 234 = 23 - 275 = 27 - 31

6 = 31 - 357 = 35 - 408 = 40 - 459 = 45 - 5010 = > 50

www.weather.gov/grandrapids

WaterPerennial iceBare rock/sandRow cropsSmall grainsFallowPastureGrassland

ShrublandTransitionalUrban grass

Low intensity residentialOrchards/vineyards

High intensity residentialCommercial/industrialQuarriesHerbaceous wetlands

5 (100%)Low Friction

Deciduous forestEvergreen forestMixed forestWoody wetland

1 (10%)High Friction

4 (75%) 3 (50%)

2 (25%)

www.weather.gov/grandrapids

www.weather.gov/grandrapids

• 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

www.weather.gov/grandrapids

• 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

www.weather.gov/grandrapids