Correlations between NAM forecasts of banded snow ingredients and snowfall, for a broad spectrum of snow events

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Correlations between NAM forecasts of banded snow
ingredients and snowfall, for a broad spectrum of
snow events

• Mike Evans and Mike Jurewicz
• NOAA/NWS Binghamton, NY

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Purpose

• Many case studies have shown utility of looking
  at certain key dynamical ingredients prior to
  major, banded snow events.
• Question What about smaller events can the same
  conceptual models applied to big events be
  applied to smaller events?

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Outline

• Review of conceptual models regarding banding
  associated with major storms and moderate storms.
• Our findings.
• Now what?

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Heavy Banded Snowfall Conceptual Model (from
Nicosia and Grumm)
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Frontogenesis and Stability (from Novak et al.)
Frontogenesis (shaded) and saturated equivalent
potential temperature (contoured)
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Novak et al. summarized these findings by listing
3 key ingredients for snow banding

• Frontogenesis
• Reduced stability
• Moisture

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Next Question What about moderate events?
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Forecasters are using these parameters
especially at short ranges
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What weve done

• Examine 27 cases (maximum snowfall from 4 to 39
  inches).
• Look for existence of the ingredients.
• Look for relationships between the magnitude,
  depth and persistence of the ingredients and
  snowfall.

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Findings related to magnitude of key ingredients

• Ingredients identified by Novak et. al. also
  exist in smaller storms.
• Significant correlations were found between event
  max snowfall and 12-hr forecast event maximum Fn
  convergence and event maximum upward vertical
  motion.
• No significant correlation was found between
  event max snowfall and 12-hr forecast event
  minimum geostrophic EPV.
• Correlations with max snowfall decreased rapidly
  from 12 hour forecasts to 24 hour forecasts.

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Findings related to depth and persistence of key
ingredients

• Significant correlations were found between max
  snowfall and depth and persistence of Fn
  convergence and negative geostrophic EPV.
• Better correlations were found between max
  snowfall and depth and persistence of parameters
  that combined ingredients ( Signature).
• No ingredient or combination parameter correlated
  better with max snowfall than depth and
  persistence of omega lt -8 µbs-1
• Depth and persistence of key ingredients are all
  strongly correlated to depth and persistence of
  upward vertical motion.
• Correlations between max snowfall and depth and
  persistence of key ingredients all decreased
  significantly between 12 and 24 hours.

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More findingstemporal trends in EPV

• A strong correlation was found between max
  snowfall and the magnitude of negative EPV, 3
  hours prior to the most intense banding.
• A strong correlation was found between max
  snowfall and the change in EPV, from 3 hours
  prior to the most intense banding, to the time of
  most intense banding (EPV increased rapidly in
  major events).

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More findings microphysics

• No correlation between max snowfall and depth of
  the dendrite zone.
• Strong correlation between max snowfall and
  magnitude, depth and persistence of omega in the
  dendrite zone.

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Final question can we show benefits of looking
at ingredients vs. just looking at omega?

• We cant prove that examining depth and
  persistence of ingredients or combinations of
  ingredients, at a point over the entire time of
  the storm, provides any improvement over
  examination of depth and persistence of strong
  model omega.
• However, there is evidence that the magnitude of
  certain ingredients at key times (during the most
  intense banding), correlates more closely with
  event total snowfall than does model omega.

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Now what?

• Complete a draft of a paper, submit to ER
  Scientific Service Division (late May).
• Develop teletraining (fall, 2007).