1. 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

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

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

4. Heavy Banded Snowfall Conceptual Model (from Nicosia and Grumm)

5. Frontogenesis and Stability (from Novak et al.) Frontogenesis (shaded) and saturated equivalent potential temperature (contoured)

6. Novak et al. summarized these findings by listing 3 key ingredients for snow banding… Frontogenesis Frontogenesis Reduced stability Reduced stability Moisture Moisture

7. Next Question… What about “moderate” events?

8. Forecasters are using these parameters – especially at short ranges

9. What we’ve done Examine 27 cases (maximum snowfall from 4 to 39 inches). Examine 27 cases (maximum snowfall from 4 to 39 inches). Look for existence of the ingredients. Look for existence of the ingredients. Look for relationships between the magnitude, depth and persistence of the ingredients and snowfall. Look for relationships between the magnitude, depth and persistence of the ingredients and snowfall.

10. Findings related to magnitude of key ingredients Ingredients identified by Novak et. al. also exist in smaller storms. 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. 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. 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. Correlations with max snowfall decreased rapidly from 12 hour forecasts to 24 hour forecasts.

11. 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. 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). 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 < -8 µbs -1 No ingredient or combination parameter correlated better with max snowfall than depth and persistence of omega < -8 µbs -1 Depth and persistence of key ingredients are all strongly correlated to depth and persistence of upward vertical motion. 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. Correlations between max snowfall and depth and persistence of key ingredients all decreased significantly between 12 and 24 hours.

12. More findings…temporal 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 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). 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).

13. More findings… microphysics No correlation between max snowfall and depth of the dendrite zone. 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. Strong correlation between max snowfall and magnitude, depth and persistence of omega in the dendrite zone.

14. Final question – can we show benefits of looking at ingredients vs. just looking at omega? We can’t 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. We can’t 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. 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.

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