1. A Gridded Snowfall Verification Method using ArcGIS: Zone-Based Verification & Bias Maps Joe Villani Ian Lee Vasil Koleci NWS Albany, NY

2. Motivation  Utilize Geographic Information Systems (GIS) technology for a gridded and more representative snowfall verification method  Legacy method (adding reports and dividing by # of reports) has become antiquated:  Does not factor in spatial variability between data points

3. Methodology  Use ArcGIS 10.2 software ArcCatalog and ArcMap  Create contoured snowfall maps and zonal statistics based on observations

4. Methodology  Careful QC of snowfall observations is necessary (from trained spotters, public, social media, etc.)  Summary of reports issued as Public Information Statement (PNS)  A Local Hydrometeorological Data Message (RRM) file is generated automatically from PNS  Contains location name, snowfall amount, LAT/LON

5. Methodology  Important to have snowfall reports outside forecast area  Allows for more representative interpolation  Gather RRM files from surrounding offices  Python script collects snowfall reports from RRM files and compiles them to a CSV file  Import CSV file into a spreadsheet

6. RRM File Example Relevant Data Extracted from RRM File

7. Creation of Gridded Snowfall Map  Generate GIS shape file of snowfall reports from spreadsheet using ArcCatalog  Import into ArcMap

8. Creation of Gridded Snowfall Map  Run an Inverse Distance Weighting (IDW) function in ArcMap  Can try other interpolation schemes such as Natural Neighbor or Spline  Creates a gridded (raster) dataset and contoured snowfall map  Color scheme can be matched to ER standardized forecast snowfall ranges

9. Gridded (IDW) Snowfall Map IDW takes into account distance between points & interpolates

10. Zonal Statistics Run Zonal Statistics (including mean) on the Gridded Map Image source: http://help.arcgis.com

11. Verification by Forecast Zone A verification map is created using ranges corresponding to local office advisory & warning criteria

12. Verification by Forecast Zone  Run Zonal Statistics as a table for statistical values  Output for Mean Snowfall and other stats within each forecast zone

13. Verification  Table is based on statistics computed from the Gridded (IDW) snowfall map  Mean snowfall used for verification by forecast zone

14. An Argument for the Gridded Method…  Legacy method would result in mean snowfall skewed towards higher totals in eastern part of the zone where the snowfall reports are concentrated  Gridded method more representative based on incorporating lower amounts west of the zone

15. Creation of Forecast Bias Maps  Preceding an event, export Forecast Snowfall from GFE to a netCDF file  Script converts netCDF file to a shape file,  Import into ArcMap and convert shape file to raster

16. Creation of Forecast Bias Maps  Create Gridded snowfall map from observations after event:  Subtract Forecast – Observed to compute bias

17. Creation of Forecast Bias Maps  Forecast – Observed Snowfall = Bias  Warm colors indicate over-forecast  Cold colors indicate under- forecast

18. Conclusions  This Gridded GIS-based verification method yields a more representative depiction of snowfall spatially across a region  Aides in computing legacy zone- based verification in a more comprehensive manner

19. Conclusions  Used for official snow verification at ALY during the 2013-2014 winter season and ALY staff has given positive feedback  Can be used in Social Media posts to give our users a graphical representation of snowfall after an event

20. Conclusions  Bias Maps show how well or poor a gridded forecast verified spatially  Bias maps of snowfall events can be compiled over entire winter seasons to compute potential positive or negative biases  Can be valuable for determining if certain areas consistently show a bias

21. More Examples

23. Acknowledgements  John Quinlan – NWS Albany, providing conceptual ideas for computing zone average statistics  Steve Welch – NWS Buffalo, method for creating shape file for snowfall based on reports and LAT/LON  Luigi Meccariello – NWS Albany, assisting in creating observed snowfall maps during the 2013-2014 winter season

24. Questions/Comments?Joe.Villani@noaa.govIan.Lee@noaa.govVasil.Koleci@noaa.gov