Background Objectives Double Trouble State Park (DTSP) Wildfire E vent

1. The diagnosis of mixed-layer characteristics and their relationship to meteorological conditions above eastern U.S. wildland fires Joseph J. Charney USDA Forest Service, Northern Research Station, East Lansing, MI and Daniel Keyser Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, NY

2. Organization • Background • Objectives • Double Trouble State Park (DTSP) Wildfire Event • WRF Model Configuration • Ingredients and Indices • Results • Conclusions

3. Background The overall projects goals address identifying dry air in the lower troposphere and processes that could transport this dry air to the surface. This presentation focuses on mixed-layer characteristics that are important for understanding and predicting when dry air aloft might influence fire behavior. Diagnostic methodologies are proposed that address variability in surface conditions over time scales of a few hours can be detected using mesoscale model simulations.

4. Objectives • Using mesoscale model simulations of the 2 June 2002 DTSP wildfire event, we will: • examine the Ventilation Index (VI) to assess whether the index is sensitive to differences between the mixed-layer depth (MLD) and PBL depth (BLD); • determine whether Downdraft Convective Available Potential Energy (DCAPE) can diagnose the potential for low relative humidity to occur at the surface.

5. DTSP Wildfire Event • Occurred on 2 June 2002 in east-central NJ • Abandoned campfire grew into major wildfire by 1800 UTC • Burned 1,300 acres • Forced closure of the Garden State Parkway • Damaged or destroyed 36 homes and outbuildings • Directly threatened over 200 homes • Forced evacuation of 500 homes • Caused ~$400,000 in property damage • References:  • Charney, J. J., and D. Keyser, 2010: Mesoscale model simulation of the meteorological conditions during the 2 June 2002 Double Trouble State Park wildfire. Int. J. Wildland Fire, 19, 427–448. • Kaplan, M. L., C. Huang, Y. L. Lin, and J. J. Charney, 2008:  The development of extremely dry surface air due to vertical exchanges under the exit region of a jet streak.  Meteor. Atmos. Phys., 102, 3–85.

6. DTSP Wildfire Event "Based on the available observational evidence, we hypothesize that the documented surface drying and wind variability result from the downward transport of dry, high-momentum air from the middle troposphere occurring in conjunction with a deepening mixed layer." "The simulation lends additional evidence to support a linkage between the surface-based relative humidity minimum and a reservoir of dry air aloft, and the hypothesis that dry, high-momentum air aloft is transported to the surface as the mixed layer deepens during the late morning and early afternoon of 2 June." (Charney and Keyser 2010)

7. WRF Model Configuration • WRF version 3.1 • 4 km nested grid • 51 sigma levels, with 21 levels in the lowest 2000 m • NARR data used for initial and boundary conditions • Noah land-surface model • RRTM radiation scheme • YSU and MYJ PBL schemes

8. Ingredients and Indices • Fire weather ingredients • wind speed • humidity (RH, mixing ratio) • temperature • Meteorological variables • mixed layer depth (MLD) • (depth over which near-surface eddies rise freely) • PBL depth (BLD) • (a parameter from the mesoscalemodel PBL scheme) • In a well-mixed boundary layer, the • MLD and the BLD would be expected • to be similar. (Potter 2002)

9. Ingredients and Indices Ventilation Index (VI) Definition: the MLD multiplied by the “transport wind speed” The VI can be calculated from mesoscale model data using either the MLD or the BLD. The transport wind speed can be interpreted in several different ways: • mixed-layer average wind speed • surface wind speed (usually 10 m) • 40 m wind speed For the purposes of this study, the mixed-layer averaged wind speed will be used.

10. Results – VI We now turn our attention to time series at the fire location of the components of the VI: • MLD • MLD-average wind speed • BLD • BLD-average wind speed Note: the fire started to exhibit rapid spread between 1700 and 1800 UTC.

11. Results – VI The YSU simulation generally produces MLDs and BLDs that are higher than those in the MYJ simulation.  YSU MLDs and BLDs track quite closely to each other, while MYJ MLDs and BLDs differ more. 

12. Results – VI The YSU VIs are higher than the MYJ VIs wherever the MLDs/BLDs are higher. The apparent dependence of the VI on average wind speed is weaker than on the MLD/BLD.

13. Ingredients and Indices DCAPE DCAPE was originally formulated to estimate the potential strength of evaporatively cooled downdrafts beneath a convective cloud (Emanuel 1994). It has been suggested that the quantity could be applied to wildland fires (Potter 2005). We hypothesize that in the case of a mixed layer produced by dry convection, large DCAPE may correlate well with low surface relative humidity when the mixed-layer is deep and the top of the mixed layer is dry.

14. Ingredients and Indices DCAPE • DCAPE calculation: • choose a starting level for the “source air” • saturate that air with respect to water vapor • bring the parcel to the surface while maintaining saturation • evaluate the negative buoyancy of the parcel as it passes the “level of free sink” and reaches the surface • The cumulative energy of the negative buoyancy when the air reaches the surface is DCAPE. • For the starting point: • Potter (2004) proposes a starting level of 3000 m • we choose the top of the MLD

15. Results – DCAPE Examine time series of simulated 3000 m and MLD DCAPE at the fire location using the YSU PBL scheme.

16. Results – DCAPE • The 3000 m DCAPE and the MLD DCAPE tend to vary together in that they both reach a maximum at 1700 UTC. • The MLD DCAPE varies more than the 3000 m DCAPE due to the variable starting level. Thus the diurnal cycle in the starting level is reflected in the DCAPE time series, which contributes to a higher peak at the time when low relative humidity occurred at the surface during the DTSP wildfire.

17. Results – DCAPE We now examine an animation of horizontal plots of simulated MLD DCAPE using the YSU PBL scheme from 1300 UTC through 1800 UTC.

18. Results – DCAPE

19. Results – DCAPE

20. Results – DCAPE

21. Results – DCAPE

22. Results – DCAPE

23. Results – DCAPE

24. Results – DCAPE The horizontal plots of DCAPE show elevated values over south-central NJ and the Delmarva Peninsula. We hypothesize that these elevated DCAPE values diagnose the potential for anomalously low surface relative humidity in these locations as the mixed layer deepened between 1300 and 1800 UTC on 2 June 2002.  (Charney and Keyser 2010)

26. Conclusions The VI exhibits more sensitivity to variations in the MLD/BLD than it does to changes in the average wind speed for this event. The YSU simulation generally produces MLDs and BLDs that are higher than those in the MYJ simulation, and exhibits smaller differences between the two quantities. This result suggests that care should be taken in interpreting VI calculations from simulations that employ the MYJ PBL scheme and use the BLD from the scheme to calculate the VI. While the 3000 m DCAPE and the MLD DCAPE exhibit similar types of temporal variability, the variable starting level in the MLD DCAPE shows more sensitivity to the diurnal cycle. This sensitivity contributes to a higher peak in DCAPE values where and when anomalously low surface relative humidity occurred during the DTSP wildfire event.