Snow to Liquid Ratio Variation with Snow to Liquid Ratio Variation with Temperature:Temperature:

Whose Assumptions are These, Whose Assumptions are These, Anyway?Anyway?

Robert A. Weisman and Jacob Yurek*Robert A. Weisman and Jacob Yurek*EAS Dept., Saint Cloud State EAS Dept., Saint Cloud State

UniversityUniversity*Current affiliation: DTN/Meteorologix, Burnsville, MN*Current affiliation: DTN/Meteorologix, Burnsville, MN

Email: raweisman@stcloudstate.eduWeb: http://web.stcloudstate.edu/raweisman/

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Snow-to-Liquid RatiosSnow-to-Liquid Ratios Huge operational problemHuge operational problem

– if we could get QPF right…(Hah!)if we could get QPF right…(Hah!)– Regional knowledge not well known 10 years agoRegional knowledge not well known 10 years ago

Depends on Cloud Physics within Each CloudDepends on Cloud Physics within Each Cloud– Efficiency of Ice Crystal Growth RateEfficiency of Ice Crystal Growth Rate

Having saturated layer with temperature colder than -15Having saturated layer with temperature colder than -15°°CC Having a feeder layer with high liquid water contentHaving a feeder layer with high liquid water content Good Review by Baumgardt, NWS LaCrosseGood Review by Baumgardt, NWS LaCrosse

Effect of moist-melting layersEffect of moist-melting layers Effect of ground temperatures, especially in recent Effect of ground temperatures, especially in recent

mild yearsmild years Compaction IssuesCompaction Issues

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Forecast Tools – Proxy MethodsForecast Tools – Proxy Methods

Knowledge of individual cloud physics lackingKnowledge of individual cloud physics lacking 10:1 or bust!...except maybe lake effect? (1995)10:1 or bust!...except maybe lake effect? (1995)

– Baxter et al. 2005 Baxter et al. 2005 SLU Research on mean SLU Research on mean snow:liquidsnow:liquid by area by area Mean ratio based on NWS Forecast AreasMean ratio based on NWS Forecast Areas

– Roebber et al. 2003 Extrapolation of Snow-to-liquid ratio Roebber et al. 2003 Extrapolation of Snow-to-liquid ratio based on model databased on model data

Best: Know what sounding will look likeBest: Know what sounding will look like– Forecast soundings often stink!Forecast soundings often stink!

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Forecast Tools – Proxy Methods(2)Forecast Tools – Proxy Methods(2)

Sounding SnapshotsSounding Snapshots Critical ThicknessesCritical Thicknesses

– 1000-500 mb 5400 m 1000-500 mb 5400 m Mostly underground away from oceanMostly underground away from ocean

– 1000-850 mb 1200 m1000-850 mb 1200 m Critical Temperature StructureCritical Temperature Structure

– Being Saturated at Critical Temperatures for Ice Crystal Being Saturated at Critical Temperatures for Ice Crystal growthgrowth

– Wetzel Winter Weather Forecasting Ingredients Wetzel Winter Weather Forecasting Ingredients looks at looks at 600 mb temperatures600 mb temperatures

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Snow-to-liquid vs Surface Temp.Snow-to-liquid vs Surface Temp.

Frequently used simplificationFrequently used simplification Old “Study”?Old “Study”?

– Gives a single value conversion for surface Gives a single value conversion for surface temperature rangestemperature ranges

– Advanced from “everything is 10:1”Advanced from “everything is 10:1”– Version previously posted on NWS Quad Cities, Version previously posted on NWS Quad Cities,

IA/IL website (not found now)IA/IL website (not found now)

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Still found at ToolKit - Envirocast - the weather & watershed newsletter

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Jacob Yurek Senior Research Jacob Yurek Senior Research ProjectProject

Frequent error in bad snow forecastsFrequent error in bad snow forecasts.. Single ratio doesn’t make sense from Single ratio doesn’t make sense from

operational experienceoperational experience– Empirical Rules Based on Henn, Jurek, and Empirical Rules Based on Henn, Jurek, and

Weisman work to come laterWeisman work to come later Determine snow:liquid for long term staffed Determine snow:liquid for long term staffed

reporting station:reporting station:– Minneapolis-St. Paul International Airport, MN Minneapolis-St. Paul International Airport, MN

(KMSP)(KMSP)

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MethodsMethods

Time period: 1961-1995Time period: 1961-1995– Source: Local Climatological Data for KMSPSource: Local Climatological Data for KMSP

822 Cases822 Cases– No sleet, freezing rain, nor mixed precipitation No sleet, freezing rain, nor mixed precipitation

allowed in any caseallowed in any case– Must have produced measurable liquidMust have produced measurable liquid– Before period when ASOS used entirely for Before period when ASOS used entirely for

liquid equivalentliquid equivalent

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Methods cont.Methods cont.

Stratified by surface temperature categories Stratified by surface temperature categories as noted in old “study”as noted in old “study”– 34-2834-28°°F (261 cases)F (261 cases)– 27-2027-20°°F (240 cases)F (240 cases)– 19-1519-15°°F (117 cases)F (117 cases)– 14-1014-10°°F (87 cases)F (87 cases)– 9-09-0°°F (90 cases)F (90 cases)– -1 to -20-1 to -20°°F (27 cases)F (27 cases)

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Mean ValuesMean Values

Other Statistics?

•Look at Distributions

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28 – 3428 – 34°°FF

10:1

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27 – 2027 – 20°°FF

10:115:1

20:1

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19 – 1519 – 15°°FF

10:1

15:120:1

30:1

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14 – 1014 – 10°°FF

10:1

15:120:1

30:1

25:1

40:1

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9 – 09 – 0°°FF

15:1

20:1

30:1

25:1

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-1 – -20-1 – -20°°FF20:1

30:1 40:1

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ResultsResults

Study contaminated by observational biasStudy contaminated by observational bias Anecdotal confirmationAnecdotal confirmation In fact, look at Mean ratio based on NWS In fact, look at Mean ratio based on NWS

Forecast AreasForecast Areas Next step:Next step:

– Is Cooperative Data contaminated?Is Cooperative Data contaminated?– New, independent data taken without New, independent data taken without

assumptionsassumptions

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Empirical SCSU Snow Forecasting Empirical SCSU Snow Forecasting RulesRules

Wet snow (850 temp. of -2 to 0Wet snow (850 temp. of -2 to 0°°C) usually 5-8:1C) usually 5-8:1– Surface temperature: 32-34Surface temperature: 32-34°°FF– Can be 10:1 for surface temperature of 28-32Can be 10:1 for surface temperature of 28-32°°FF

Dry “dendritic snowfall”Dry “dendritic snowfall”– 850 mb temp of -8 to -4850 mb temp of -8 to -4°°C C

Saturated at -10 to -15Saturated at -10 to -15°°C in soundingC in sounding Surface temperatures generally in the 20’sSurface temperatures generally in the 20’s°F°F Saturated at -10 to -15Saturated at -10 to -15°°C in soundingC in sounding

– Wet snow: around 10:1Wet snow: around 10:1– Dry snow: 12-15:1Dry snow: 12-15:1

Colder “dendritic snowfall” Colder “dendritic snowfall” – 850 mb temp of -12 to -5850 mb temp of -12 to -5°°C C

Saturated at -10 to -15Saturated at -10 to -15°°C in soundingC in sounding– Surface temperature: 18-24Surface temperature: 18-24°°FF– 15-20:1 15-20:1

Even colder or lake effect: 20+:1Even colder or lake effect: 20+:1

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ReferencesReferencesBaumgardt, D., 1998: Wintertime cloud microphysics review. NWS Baumgardt, D., 1998: Wintertime cloud microphysics review. NWS

LaCrosse, WI. http://www.crh.noaa.gov/arx/micro/micrope.phpLaCrosse, WI. http://www.crh.noaa.gov/arx/micro/micrope.phpBaxter, M. A., C. E. Graves, and J.T. Moore, 2005: A climatology of snow-Baxter, M. A., C. E. Graves, and J.T. Moore, 2005: A climatology of snow-

to-liquid ratio for the contiguous United States. to-liquid ratio for the contiguous United States. Wea. and ForecastingWea. and Forecasting, , 2020, 729-744. , 729-744. http://www.eas.slu.edu/CIPS/Research/snowliquidrat.htmlhttp://www.eas.slu.edu/CIPS/Research/snowliquidrat.htmlCOMET module: COMET module:

http://www.comet.ucar.edu/class/aes_canada/06-1/html/descriptions/snowhttp://www.comet.ucar.edu/class/aes_canada/06-1/html/descriptions/snowRatio.htmRatio.htm

National Environmental Education and Training Foundation, 2003: National Environmental Education and Training Foundation, 2003: ToolKit. ToolKit. EnviroCast: The Weather and Watershed NewsletterEnviroCast: The Weather and Watershed Newsletter, 1(3), , 1(3), http://www.stormcenter.com/envirocast/2003-01-01/envirocast-article2.http://www.stormcenter.com/envirocast/2003-01-01/envirocast-article2.phpphp

Roebber, P. J., S. L. Bruening, D. M. Schultz, and J. V. Cortinas, Jr., Roebber, P. J., S. L. Bruening, D. M. Schultz, and J. V. Cortinas, Jr., 2003: Improving snowfall forecasting by diagnosing snow density. 2003: Improving snowfall forecasting by diagnosing snow density. Wea. and ForecastingWea. and Forecasting, , 1818, 264-287. , 264-287. http://sanders.math.uwm.edu/cgi-bin-snowratio/sr_intro.plhttp://sanders.math.uwm.edu/cgi-bin-snowratio/sr_intro.pl

Wetzel-Seemann, S. W., and J. E. Martin, 2001: An operational Wetzel-Seemann, S. W., and J. E. Martin, 2001: An operational ingredients-based methodology for forecasting mid-latitude winter ingredients-based methodology for forecasting mid-latitude winter season precipitation. season precipitation. Wea. and ForecastingWea. and Forecasting, , 1616, 156-167. , 156-167. http://speedy.meteor.wisc.edu/~swetzel/winter/winter.htmlhttp://speedy.meteor.wisc.edu/~swetzel/winter/winter.html