Joe Villani Ian Lee Vasil Koleci NWS Albany, NY NROW – November 2015 Update to Gridded Snowfall Verification: Computing Seasonal Bias Maps

Methodology Review  Utilize Geographic Information Systems (GIS) technology for a gridded and more representative snowfall verification method  Use ArcGIS 10.3 software ArcCatalog and ArcMap  Create contoured snowfall maps and zonal statistics based on observations

Geography/Topography Hudson Valley Adirondacks Catskills Berkshires & Greens Mohawk Valley

Methodology Review  Compile storm total snowfall reports from Public Information Statement (PNS)  Python script collects snowfall reports from PNS and compiles them to a CSV file

Gridded Snowfall Analysis Map Generate shape file from snowfall reports using ArcCatalog, import into ArcMap Run Inverse Distance Weighting (IDW) in ArcMap (or other interpolation scheme) Creates a gridded (raster) snowfall analysis map

Verification by Forecast Zone Run zonal statistics function to create a verification map Use ranges corresponding to local office advisory & warning criteria

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

Creation of Forecast Error Maps  Preceding an event, export Forecast Storm Total Snowfall from GFE to a netCDF file  Script converts netCDF file to a shape file,  Import into ArcMap and convert shape file to raster Forecast Snowfall Preceding Event

Creation of Forecast Error Maps  Create Gridded snowfall analysis map after event:  Subtract Forecast – Observed rasters to compute error map Forecast Snowfall Observed Snowfall

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

Creation of Seasonal Bias Maps Forecast error maps compiled over entire winter season to compute positive or negative bias Sum error rasters for each snowfall event into one map using raster calculator in ArcMap

Seasonal Bias Maps Must be careful since single large outlier events may skew bias

Seasonal Bias Maps Seasonal bias map without outlier (7 events)

Seasonal Bias Maps Seasonal bias map (3 events)

Seasonal Bias Maps / Combined bias map (10 events)

Seasonal Bias Maps / Combined bias map without outlier (9 events)

Conclusions  Error Maps show how well or poor a gridded forecast verified spatially  Error maps of snowfall events compiled over entire winter seasons to compute positive or negative biases  Determine areas of consistent positive or negative bias

Future Work  Continue working on automating some of the process to make method accessible to a wider audience  Improve on interpolation scheme by experimenting with other analysis techniques  Expand database to include all warning and advisory events for winter season  Stratify bias maps based on flow regime and/or storm track?