Verification of SPC Winter Weather Mesoscale Discussions Christopher D. McCray Lyndon State College...
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Verification of SPC Winter Weather Mesoscale Discussions Christopher D. McCray Lyndon State College Christopher Melick 1,2, William Bunting 1, Israel Jirak
Verification of SPC Winter Weather Mesoscale Discussions
Christopher D. McCray Lyndon State College Christopher Melick 1,2,
William Bunting 1, Israel Jirak 1, Patrick Marsh 1, Andrew Dean 1,
Ariel Cohen 1, Jared Guyer 1 1. NOAA/NWS Storm Prediction Center,
Norman, OK 2. Cooperative Institute for Mesoscale Meteorological
Studies, Norman, OK
Slide 2
WAGM-TV Winter Weather Mesoscale Discussions (MDs) Issued since
Winter 1997-98 Short term, high-impact winter weather 0-6 hours +
up to 3 hours lead time Impacts to transportation, commerce, life,
property Assist WFOs, other partners in decision making Brian
Cassella/Chicago Tribune
Slide 3
Research Questions and Objectives Put focus on SPC winter
operations What are the basic characteristics of winter MDs? How
can they be verified? Only minor efforts to verify until now
Develop operational tools to assist forecasters
Slide 4
Winter Weather Mesoscale Discussions Freezing Rain >0.05
liquid equivalent freezing rain in 3 hour period Heavy Snow 1+/hr
snow for 2+ hours
Slide 5
Challenges in Verifying Winter Weather Local Storm Reports
(LSRs) Lack of consistent issuance/reporting 2010-2012 Total Winter
LSRs From Sullivan et al. (2014) Snow/icing amounts ASOS/AWOS
Snowfall Observations
Slide 6
What are the basic characteristics of winter weather MDs?
Slide 7
How frequently are winter MDs issued? MDs analyzed from Jan
2007 Apr 2014 Early October - late April is winter MD season Peaks
in Dec/Feb n = 7 (May-Dec), 8 (Jan-Apr)
Slide 8
What are the most common types?
Slide 9
How can winter weather MDs be verified?
Slide 10
Verification Approach Did an observed event occur within the MD
area? To what extent? Determine what constitutes an observed event
Hourly Snowfall Icing Amounts Blizzard Conditions Precipitation
Type and/or Amount Compare MD forecast to observed event Utilize
Multiple Datasets Develop Gridded Analysis System GEMPAK
Slide 11
Datasets for Heavy Snow MD Verification
Slide 12
Datasets: Gauge-Corrected QPE NMQ System ( MRMS) (Zhang et al.
2011) 3D reflectivity mosaic + rain gauge correction QPE 0.01 x
0.01 grid spacing ~1km x 1km NMQ domain from Zhang et al. (2011),
Fig. 6
Slide 13
Datasets: Local Storm Reports (LSRs) LSRs now decoded locally
at SPC for winter types Snow Heavy Snow Blizzard Freezing Rain Ice
Storm Sleet Ex.) Winter LSRs from 2201-2300z 2/20/14
Slide 14
Datasets: Surface station obs./METARs Archived METARs parsed by
hour and precip type Rain/Drizzle, Snow, Sleet, Freezing
Rain/Drizzle Temperature QC checks T0C for rain Ex.) Surface precip
obs. 2201-2300z 2/20/14
Slide 15
Datasets: Snow-to-Liquid Ratio (SLR) Climatology Need SLR to
get snow from QPE 30-year SLR climo. using COOP data (Baxter et al.
2005) Monthly grids provided for 25 th, 50 th, 75 th percentile
SLRs February Mean SLR
Slide 16
Gridded Mesoscale Discussions Forecast object is gridded MD
GEMPAK Graph-to-Grid Gridpoint = 1 if within MD area, 0 if not
Slide 17
Combining Datasets for Verification Datasets need common grid
structure QPE grid cropped to CONUS 0.04x0.04 spacing Used for all
data
Slide 18
Determining Dominant Precipitation Type
Slide 19
Observation Weighting 10-gridpoint radius sweep from each
LSR/METAR obs. Sleet LSR
Slide 20
Gridding Precipitation Type Heavy Snow Blizzard Freezing Rain
Ice Storm LSR Snow LSR Freezing Rain LSR Freezing Rain LSR Sleet
Sleet Precip. Types from LSRs Snow
Gridding Precipitation Type Precip. Types from LSRs Precip.
Types from METARs Snow Sum Freezing Rain Sum Freezing Rain Sum
Sleet Sum Rain Sum Heavy Snow Blizzard Freezing Rain Ice Storm LSR
Snow LSR Freezing Rain LSR Freezing Rain LSR Sleet Sleet Snow METAR
Snow METAR Freezing Rain METAR Freezing Rain METAR Sleet METAR
Rain
Slide 23
Gridding Precipitation Type Dominant Precipitation Type Binary
(1/0) Grids Snow Sum Freezing Rain Sum Freezing Rain Sum Sleet Sum
Rain Sum Gridpoint Total Snow Sum Total Rain Sum Total Frzg. Rain
Sum Total Sleet Sum Total > > > > 50% Dom. Snow Dom.
Freezing Rain Dom. Freezing Rain Dom. Sleet Dom. Rain Mix Any Sum
Total = 50%
Slide 24
Verification Methods and Case Study
Slide 25
MD 0121 Heavy Snow 2/20/2014
Slide 26
Yes Verification Method for Heavy Snow Hourly Snowfall =
Dominant Snow Grid x QPE x Average SLR at point Hourly Snowfall =
Dominant Snow Grid x QPE x Average SLR at point Heavy Snow Event
Observed at Point Yes
Slide 27
Verification of MD 0121 Blue = Observed Event 2+ hours of 1+/hr
snowfall Event was observed, but small area
Slide 28
Neighborhood Verification Method SPC convective products
verified using 40km (25mi) neighborhood Did observed event occur
within 40km of point? Melick et al. (2012): Neighborhood objective
measures agreed most with subjective forecaster evaluations
Slide 29
Neighborhood Verification Method Blue = Observed Event 2+ hours
of 1+/hr snowfall within 40km of point Greater area within MD
Slide 30
Summary & Conclusions Gridded dominant precip. type product
useful for forecaster Standardization in reporting is needed,
workarounds are available QPE+SLR + LSRs + METARs combination
provides viable results Method is flexible, can easily incorporate
new data and methods PING, better SLR techniques Objective
verification system using neighborhood technique developed for
winter weather MDs
Slide 31
Current Progress Experimental real-time gridded precip. type
analysis now available locally at SPC Produces precip rates,
snowfall rates using SLR Uses MRMS radar-only QPE Gauge-corrected
not available in real time
Slide 32
Summary & Conclusions Gridded dominant precip. type product
useful for forecaster Standardization in reporting is needed,
workarounds are available QPE+SLR + LSRs + METARs combination
provides viable results Method is flexible, can easily incorporate
new data and methods PING, better SLR techniques Objective
verification system using neighborhood technique developed for
winter weather MDs
Slide 33
References Baxter, M. A., C. E. Graves, and J. T. Moore, 2005:
A Climatology of Snow-to-Liquid Ratio for the Contiguous United
States. Wea. Forecasting, 20, 729744. Branick, M. L., 1997: A
Climatology of Significant Winter-Type Weather Events in the
Contiguous United States, 198294. Wea. Forecasting, 12, 193207.
desJardins, M.L., K.F. Brill, and S.S. Schotz, 1991: Use of GEMPAK
on Unix workstations, Proc. 7th International Conf. on Interactive
Information and Processing Systems for Meteorology, Oceanography,
and Hydrology, New Orleans, LA, Amer. Meteor. Soc., 449-453.
Melick,C.J, I.L. Jirak, A.R. Dean, J. Correia Jr, and S.J. Weiss,
2012: Real Time Objective Verification of Convective Forecasts:
2012 HWT Spring Forecast Experiment. Preprints, 37th Natl. Wea.
Assoc. Annual Meeting, Madison, WI, Natl. Wea. Assoc., P1.52.
Roberts, N. M., and H. W. Lean, 2008: Scale-Selective Verification
of Rainfall Accumulations from High- Resolution Forecasts of
Convective Events. Mon. Wea. Rev., 136, 7897. Sullivan, B.T., C.J.
Melick, I.L. Jirak, R.M. Mosier, S.J. Weiss, and C.D. McCray, 2014:
The Usefulness of Winter Weather Local Storm Reports at the Storm
Prediction Center, 39th Natl. Wea. Assoc. Annual Meeting, Salt Lake
City, UT, Natl. Wea. Assoc., PXXXX. Wilks, D. S., 2011: Statistical
Methods in the Atmospheric Sciences. Academic Press, 704 pp. Zhang,
J., and Coauthors, 2011: National Mosaic and Multi-Sensor QPE (NMQ)
System: Description, Results, and Future Plans. Bull. Amer. Meteor.
Soc., 92, 13211338
Slide 34
Verification Approach Did an observed event occur within the MD
area? To what extent? Determine what constitutes an observed event
Hourly Snowfall Icing Amounts Blizzard Conditions Precipitation
Type and/or Amount Compare MD forecast to observed event QPE
Snow-to-Liquid Ratio LSRs Surface Obs. Develop Gridded Analysis
System GEMPAK
Slide 35
Verification Methods: Blizzard Blizzard Conditions @ Hour = Yes
Vis. < mi SN / BLSN/ DRSN Blizzard LSR OR Conditions Occur for
3+ Hours within 40km of point? Blizzard MD Verified at Point
Yes
Verification Methods: Heavy Snow Hourly Snowfall =QPE x Average
SLR at point (from Baxter et al. 2005) Hourly Snowfall =QPE x
Average SLR at point (from Baxter et al. 2005) Heavy Snow MD
Verified at Point Liquid Equiv. Snowfall = QPE x (Snow Grid) Liquid
Equiv. Snowfall = QPE x (Snow Grid) Add 1 to Event Hours grid
Yes
Slide 38
Severe vs. Winter MD Frequency *Through 30 April N=
1656/811/580/342/671/664/956/1194/2007/2288/2911/2213
