WISE GROCERY WEATHER EXPERTS PRESENT The Weis Weather Scale CREATED BY Meteorologists Ryan Breton, Faith Eherts, Bret Eilertson, Andrea Paparelli, Dan Rupp

Weis’ status among grocers: Focus study – Superstorm Sandy

Social Media Before & During Sandy

 Did not stand out in advertising or social media.  Did not stand out in terms of supply available.  D batteries, milk, bread, water ran out at the same time as other local stores  News of storm came from local media.  Most Weis are a 24/7 operation, but several had to close due to power outages.  Estimated losses of over $125,000 per affected store in perishables.  Those that were renovated were able to continue operations on safely located and efficient generators (few).  renovations are still underway Bolded bullets indicate points in which our analyses will improve the company.

Meteorology History  Forecasting based on weather lore, farmers almanac, and personal observations  Instruments measured temperature, moisture, pressure, and wind  Observation based forecasting became prominent  Radiosondes released every 12 hours  Numerical weather prediction (Bjerknes and Richardson)  1940s team of meteorologists began to use modern computers  Eventually developed into super computers  Satellite (Visible, Infrared imagery)

Forecasting  HRRR (High Resolution Rapid Refresh) for short-range forecasts  MOS (Model Output Statistics) for 3 days in advance  GFS LAMP (Global Forecast System Local Aviation MOS Program) for short term visibility, winds, lightning, cloud height and temperatures  ECMWF (European Center for Medium Range Weather Forecasting) Known for its accuracy. Will be used for medium to long range forecasting

Forecasting  HRRR (High Resolution Rapid Refresh) for short-range forecasts  Path & intensity of storms and cells  Example: July, 8, 2014 at 7pm 9-hour HRRR projection: Actual Doppler Radar:

What is a Weather Index? Visual tool developed using various weather variables and their impacts Organized in such a way that an individual can look at it and make snap decisions regarding various operation components – at both the corporate and store levels Weather index is applicable to all areas of the company’s operations

Timeframes and Their Data Sources  Short Range  Between 6 and 24 hours: Designed to give specific information about weather that is occurring or imminent  Cold Season – mid-October to mid-April  Warm Season – mid-April to mid-October  Surface Data, Satellite/Radar, High-Resolution Computer Models  Medium Range  1-7 Days: Designed to give information about storm threats  GFS (Global Forecast System), NAM (North American Model), ECMWF (European Center for Medium Range Weather Forecasting)  Long Range  1-3 weeks: Threats to produce, goods due to drought, freezes, etc. nationwide  Data from NOAA’s Climate Prediction Center

Update Availability  Short Range  Active Weather Days – Especially after threat has been identified in Medium Range Index  Medium Range  Twice daily  Long Range  Twice a week on Mondays and Thursdays

All 3 Ranges Will Utilize The Same Color Code Index Value and Color Weather Impact 0 – NoneNone 1 – GreenLow 2 – YellowModerate 3 – OrangeHigh 4 – RedIndex Value & Color 5 – PurpleExtreme

Short-Range Index: COLD SEASON Variable Value Precipitation Amount Precipitation Type Average VisibilityTemperatureWind Speed RainSnow ”0”NoneUnrestricted>40<5 mph ”<3”Rain4-5 miles mph ”3-5”Rain & Snow3-4 miles mph ”5-8” Rain, Snow, or Sleet 2-3 miles mph 43-5”8-12” Rain, Snow, Sleet or Freezing Rain 1-2 miles mph 5>5”>12”Combination of All <1 mile<0>45 mph Index value = 0.5(Precipitation Amount) (Precipitation Type) + 0.1(Visibility) + 0.1(Temperature) (Wind Speed)

Short-Range Index: COLD SEASON Index value = 0.5(Precipitation Amount) (Precipitation Type) + 0.1(Visibility) + 0.1(Temperature) (Wind Speed) Scranton = 4.05 = 0.5(4) (5) + 0.1(5) + 0.1(2) (2) Philadelphia = 1.55 = 0.5(1) (2) + 0.1(3) + 0.1(1) (3)

Short-Range Index: WARM SEASON Index value = 0.5(Precipitation Amount) (SPC Convective Outlook Category) (Duration) (Wind Speed) (Temperature) Variable Value Amount of Rain SPC Convective Outlook DurationWind SpeedTemperature ”N/A <5 mph ”Marginal<1 hour5-15 mph ”Slight1-3 hours15-25 mph ”Enhanced3-6 hours25-35 mph ”Moderate6-12 hours35-45 mph >5”High12-24 hours>45 mph>95

Short-Range Index: WARM SEASON State College = 2.9 = 0.5(3) (3) (3) (2) (2) Philadelphia = 1.15 = 0.5(1) (1) (1) (2) (3) Index value = 0.5(Precipitation Amount) (SPC Convective Outlook Category) (Duration) (Wind Speed) (Temperature)

Medium-Range Index Index value = 0.5(Precipitation Amount) (Precipitation Type) (Duration) + 0.1(Temperature) + 0.1(Wind Speed) Variable Value Precipitation Type of Precipitation DurationTemperatureWind Speed RainSnow Warm Season Cold Season 0T – 0.25”T –1”N/A<3 hoursN/A Light & Var ”1 - 3”Rain3-6 hours60-70>40<15 mph ” 3 - 5”Rain & Snow6-18 hours mph ”6-10”Rain & Sleet18-36 hours mph ” ”+ Rain & Freezing Rain hours mph 5>5”>12 ”All Frozen Precipitation >48 hours>95<10>45 mph

Medium-Range Index Index value = 0.5(Precipitation Amount) (Precipitation Type) (Duration) + 0.1(Temperature) + 0.1(Wind Speed) State College = 3.85 = 0.5(4) (5) (2) + 0.1(4) + 0.1(1) Philadelphia = 2.1= 0.5(2) (2) (2) + 0.1(4) + 0.1(1)

Long-Range Index Index value = 0.5(Precipitation Departure) + 0.3(Duration) + 0.2(Temperature) Variable Value Departure from Normal Precipitation DurationTemperature Warm Season Cold Season 0N/A 1Normal7-10 days60-70>40 2Slightly Above/Below10-12 days Moderately Above/Below days Highly Above/Below2-3 weeks Severely Above/Below 3+ weeks>95<10

Long-Range Index New York State = 1 = 0.5(1) + 0.3(1) + 0.2(1) Southern California = 3.3 = 0.5(3) + 0.3(4) + 0.2(3) Index value = 0.5(Precipitation Departure) + 0.3(Duration) + 0.2(Temperature)

How Will You Receive the Index  Via  Developed App available for Apple and Android Devices  Password Protected  Push Notifications