Appalachian Lee Troughs and their Association with Severe Thunderstorms

Transcription

1 Appalachian Lee Troughs and their Association with Severe Thunderstorms Daniel B. Thompson, Lance F. Bosart and Daniel Keyser Department of Atmospheric and Environmental Sciences University at Albany/SUNY, Albany, NY Thomas A. Wasula NOAA/NWS, Albany, NY Matthew Kramar NOAA/NWS, Sterling, VA 46 th CMOS Congress 25 th AMS Conference on Weather Analysis and Forecasting 1 June 2012 NOAA/CSTAR Award # NA01NWS

2 Motivation Region of study: Mid-Atlantic U.S. Accurate forecasts of location, mode and severity of thunderstorms are important, due to proximity of Eastern Seaboard Region is often characterized by weak forcing and ample instability during warm season Mesoscale boundaries important Sea breeze boundary Outflow boundaries Lee trough

3 Outline Climatology of Appalachian lee troughs (ALTs) Categorization scheme for ALTs Spatial frequency of storm reports by ALT category Summary of key points

4 Outline Climatology of Appalachian lee troughs (ALTs) Categorization scheme for ALTs Spatial frequency of storm reports by ALT category Summary of key points

5 Data and Methodology Climatology 1. Analyzed 13 cases of ALT events associated with warm-season severe convection Sterling, VA (LWX), CWA 0.5 CFSR (Climate Forecast System Reanalysis) 2. Identified common features and used them as criteria to construct a climatology May September,

6 ALTs Common Low-Level Features MSLP (black, hpa), hPa thickness (fills, dam), 10-m winds (barbs, kt) 1800 UTC Composite (N=13)

7 ALTs Common Low-Level Features MSLP (black, hpa), hPa thickness (fills, dam), 10-m winds (barbs, kt) 1800 UTC Composite (N=13)

8 ALTs Common Low-Level Features Winds orthogonal to mountains MSLP (black, hpa), hPa thickness (fills, dam), 10-m winds (barbs, kt) 1800 UTC Composite (N=13)

9 ALTs Common Low-Level Features Winds orthogonal to mountains Thermal ridge MSLP (black, hpa), hPa thickness (fills, dam), 10-m winds (barbs, kt) 1800 UTC Composite (N=13)

10 Domain for Climatology WIND ZONE ALT ZONE DOMAIN

11 Methodology for Climatology Climatology was based on the following three criteria: 1) 925-hPa Wind Direction Checked for wind component directions orthogonal to and downslope of Appalachians Appalachians in the Mid-Atlantic are oriented ~ 43 right of true north Satisfactory meteorological wind directions exist between 223 and 43 Criterion: wind direction computed from zonal average of wind components along each 0.5 of latitude within Wind Zone must be between 223 and 43 WIND ZONE ALT ZONE DOMAIN

12 Methodology for Climatology Climatology was based on the following three criteria: 2) MSLP Anomaly Averaged MSLP along each 0.5 of latitude within domain Checked for minimum MSLP along each 0.5 of latitude within ALT Zone Criterion: difference of minimum and zonal average MSLP must be less than 0.75 hpa WIND ZONE ALT ZONE DOMAIN

13 Methodology for Climatology Climatology was based on the following three criteria: 3) hPa layer-mean temperature anomaly Averaged hPa layer-mean temperature along each 0.5 of latitude within domain Checked for maximum hPa layer-mean temperature along each 0.5 of latitude within ALT Zone Criterion: difference of maximum and zonal average hPa layer-mean temperature must be greater than 1 C WIND ZONE ALT ZONE DOMAIN

14 Methodology for Climatology The three criteria must be met for six consecutive 0.5 latitudes An algorithm incorporating the three criteria was run for the length of the climatology at 6-h intervals (0000, 0600, 1200 and 1800 UTC) ALTs identified by this algorithm were manually checked for false alarms (e.g., frontal troughs, cyclones, large zonal pressure gradients)

15 Climatology Results MSLP anomaly < 0.75 hpa Temperature anomaly > 1 C ALT recorded 26.6% of the time throughout the climatology

16 Climatology Results MSLP anomaly < 0.75 hpa Temperature anomaly > 1 C ALT recorded 26.6% of the time throughout the climatology 33.3% % ALTs by Time (UTC, N=1629) 31.9% 18.8% 25.0% ALTs by Month (N=1629) 27.8% 7.1% 17.0% 23.0% May June July August September Over 75% of ALTs occur in June, July and August Nearly 66% of ALTs occur at 1800 or 0000 UTC The seasonal and diurnal heating cycles likely play a role in ALT formation

17 Outline Climatology of Appalachian lee troughs (ALTs) Categorization scheme for ALTs Spatial frequency of storm reports by ALT category Summary of key points

18 ALT Categories ALTs can be grouped into four categories based on their relationship with synoptic-scale cold fronts ALTs that occur in advance of cold fronts can be considered prefrontal troughs (PFTs) Categories: 1. Inverted 2. No PFT: Non-prefrontal 3. PFT, partial FROPA: Prefrontal without frontal passage through entire ALT Zone 4. PFT, total FROPA: Prefrontal with frontal passage through entire ALT Zone

19 ALT Categories Examples 1. Inverted trough extends northward from south of the ALT Zone 0000 UTC 31 May 2001 MSLP (black, hpa) and hPa thickness (fills, dam)

20 ALT Categories Examples 2. No PFT trough occurs in the absence of a synoptic cold front 0000 UTC 10 July 2000 MSLP (black, hpa) and hPa thickness (fills, dam)

21 ALT Categories Examples 3. PFT, partial FROPA Front must be south of the NY/PA border or east of the western third of PA Front does not pass through entire ALT Zone 0000 UTC 3 June 2000 MSLP (black, hpa) and hPa thickness (fills, dam)

22 ALT Categories Examples 4. PFT, total FROPA Front must be south of the NY/PA border or east of the western third of PA Front passes through entire ALT Zone within 24 h 1800 UTC 13 May 2000 MSLP (black, hpa) and hPa thickness (fills, dam)

23 ALT Categories Relative Frequency Category 2 (No PFT) occurs most frequently ALT % of Occurrence by Category (N=1629) 8.0% 4.5% 1 (Inverted) 36.8% 50.8% 2 (No PFT) 3 (PFT, partial FROPA) 4 (PFT, total FROPA)

24 ALT Categories Relative Frequency Category 2 (No PFT) occurs most frequently PFTs account for 44.8% of ALTs ALT % of Occurrence by Category (N=1629) 8.0% 4.5% 1 (Inverted) 36.8% 50.8% 2 (No PFT) 3 (PFT, partial FROPA) 4 (PFT, total FROPA)

25 ALT Categories Monthly Distribution Category 2 (No PFT) ALTs by Month (N=827) 23.3% 4.5% 18.1% Category 3 (PFT, partial FROPA) ALTs by Month (N=599) 6.5% 10.9% 30.2% 22.9% 29.9% 24.2% Category 2 and 3 are more common in JJA, while category 4 is more common in May and September Stronger westerlies, more FROPA during transition months Category 4 ALTs (PFT, total FROPA) by Month (N=130) 22.3% 13.8% 15.4% 29.5% 30.8% 17.7%

26 Outline Climatology of Appalachian lee troughs (ALTs) Categorization scheme for ALTs Spatial frequency of storm reports by ALT category Summary of key points

27 Spatial Frequency of Storm Reports by Category Methodology Severe local storm reports were obtained from the NCDC Storm Data publication Included all tornado, severe thunderstorm wind and severe hail (> 1 in) for May September, % Report Type (N=12,330) 4.4% 79.1% Wind Hail Tornado ALT ZONE

28 Spatial Frequency of Storm Reports by Category Methodology Clustering attempt to control for population bias in Storm Data Overlay a 0.5 by 0.5 grid box over the domain If a storm report occurs within a certain grid box, that grid box is considered active Any subsequent storm reports occurring within the active box are discarded within a 6-h period The number of active grid boxes for each 6-h period are tallied to measure the spatial extent of severe weather 6-h periods begin at 0000, 0600, 1200, and 1800 UTC

29 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 3 (PFT, partial FROPA; N=599) Category 2 (No PFT; N=827)

30 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 3 (PFT, partial FROPA; N=599) Category 2 (No PFT; N=827) Distribution within ALT Zone is similar

31 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 3 (PFT, partial FROPA; N=599) Category 2 (No PFT; N=827) Distribution within ALT Zone is similar Difference lies in areas NW of ALT Zone

32 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 4 (PFT, total FROPA; N=130) Category 1 (Inverted; N=73)

33 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 4 (PFT, total FROPA; N=130) Category 1 (Inverted; N=73) South half of ALT Zone favored in Category 1

34 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 4 (PFT, total FROPA; N=130) Category 1 (Inverted; N=73) South half of ALT Zone favored in Category 1 Proportionally more storm reports near the coast in Category 4 than 2 or 3

35 Spatial Frequency of Storm Reports by Category Percentage of 6-h periods with at least one active grid box Category 4 (PFT, total FROPA; N=130) Category 1 (Inverted; N=73) South half of ALT Zone favored in Category 1 Proportionally more storm reports near the coast in Category 4 than 2 or 3 Maximum in Category 4 from DCA PHL

36 Category 4: PFT, Total FROPA Cat 4 (N=130) Percentage of 6-h periods with at least one active grid box

37 Cat 4 (N=130) Category 4: PFT, Total FROPA Plume of high CAPE is collocated with kt of shear in northern ALT Zone Collocation of high CAPE and shear values suggest that category 4 severe events may favor the DCA PHL corridor Percentage of 6-h periods with at least one active grid box Cat 4 (N=17) Composite of 17 days with most active grid boxes Surface to 500-hPa bulk shear (black, kt), MUCAPE (fills, J/kg)

38 Category 3 and Category 4 Comparison Cat 3 (N=17) Higher shear in category 4 severe composites suggest severe events are more organized Composite of 17 days with most active grid boxes Cat 4 (N=17) Surface to 500-hPa bulk shear (black, kt), MUCAPE (fills, J/kg)

39 Outline Climatology of Appalachian lee troughs (ALTs) Categorization scheme for ALTs Spatial frequency of storm reports by ALT category Summary of key points

40 Summary Key Points ALTs form preferentially during diurnal and seasonal heating maxima

41 Summary Key Points ALTs form preferentially during diurnal and seasonal heating maxima Frequency of each ALT category varies by month Category 2 and 3 are more common in JJA, while category 4 is more common in May and September Stronger westerlies, more FROPA during transition months

42 Summary Key Points ALTs form preferentially during diurnal and seasonal heating maxima Frequency of each ALT category varies by month Category 2 and 3 are more common in JJA, while category 4 is more common in May and September Stronger westerlies, more FROPA during transition months Spatial distribution of storm reports varies by ALT category Category 2 and 3 have similar distributions within ALT Zone Category 4 favors DCA PHL corridor, linked to collocated high CAPE and shear

43 Contact Information Dan Thompson

44 Spare slides

45 Climatology Results ALT Occurrence (%) as a Function of MSLP/Temperature Anomaly Thresholds (n=6120) hPa Mean Temperature Anomaly Threshold ( C) MSLP Anomaly Threshold (hpa) Stricter Stricter Each bubble denotes the percentage of time an ALT is recorded under a particular set of MSLP/temperature anomaly constraints Boxes indicate the criteria adopted as the ALT definition

46 Spatial Frequency of Storm Reports by Category Methodology Storm reports were binned based on nearest earlier ALT category present Example: Category 2 ALT occurred at 1800 UTC Storm reports occurring from 1800 to 2359 UTC fall into the category 2 bin