Application of a Portable Doppler Wind Lidar for Wildfire Plume Measurements Allison Charland and Craig Clements Department of Meteorology and Climate Science San José State University San José, CA American Meteorological Society 16th Symposium on Meteorological Observation and Instrumentation 25 January 2012 San José State University Fire Weather Research Laboratory

Introduction Doppler wind lidar deployed on a prescribed burn was conducted in complex terrain on 13 July 2011 San José State University Fire Weather Research Laboratory

Goals To observe structure of the velocity field in the vicinity of a wildland fire To test the performance of the Doppler wind lidar for wildland fire applications: - Determine the plume boundaries - Estimate fire spread rate - Identify maximum height of the plume San José State University Fire Weather Research Laboratory

CSU-MAPS Instrumentation California State University-Mobile Atmospheric Profiling System Portable 32-m Micromet Tower Vaisala, Inc. Digicora MW31 radiosonde sounding system Radiometrics, Inc., MP-3000A profiling radiometer Halo Photonics, Ltd. Stream Line 75 Doppler Wind Lidar San José State University Fire Weather Research Laboratory

Instrumentation Doppler wind lidar Halo Photonics, Ltd. Stream Line micron Eye-safe 75 mm aperture all-sky optical scanner Min Range: 80 m Max Range: 10km 550 user defined range gates (24 m) Temporal resolution: s Measurements: Backscatter Intensity Doppler Radial Velocity San José State University Fire Weather Research Laboratory

Experimental Site San Jose San Francisco Diablo Range Santa Cruz Mountains

Experimental Design Total of ~ 660 acres in the burn unit Prevailing wind from the northwest Ignited at the Northeast corner of the burn unit at 11:43 PST Lidar placed upwind of burn area RAWS

Weather Conditions Slight drizzle in the morning before the burn. Wind speeds from surface stations of 1-4 ms -1 With moisture in the morning and light wind speeds throughout the day, the fire intensity was fairly low for this particular burn. 13 July PST 13 July PST Background Soundings San José State University Fire Weather Research Laboratory

Lidar Scanning Techniques Multiple elevation and azimuth angles were adjusted throughout the experiment to obtain the best scan through the fire plume. – Stare: Vertically pointing beam – Wind Profile – RHI (Range Height Indicator): Fixed azimuth angle with varying elevation angles – PPI (Plan Position Indicator): Fixed elevation angle with varying azimuth angles San José State University Fire Weather Research Laboratory 95 o 30 o 70 o

San José State University Fire Weather Research Laboratory Lidar Processing Techniques

Lidar: PPI Scans Maps at o azimuth angle with increments of 1.0 o at a 10 o elevation angle. Lidar penetrates through the most intense part of the plume but is attenuated at times. San José State University Fire Weather Research Laboratory 30 o 70 o

San José State University Fire Weather Research Laboratory Finding Plume Edge Boundaries An algorithm for determining plume edge boundaries was implemented following Kovalev et al The plume edge boundary can be determined by the location of the maximum of Similar algorithm was applied to determine the edge behind the plume.

Velocity Field Around Plume Backscatter Intensity Doppler Radial Velocity (ms -1 ) 1750 PST 1752 PST

Velocity Field Around Plume Backscatter Intensity Doppler Radial Velocity (ms -1 ) 1755 PST 1757 PST

Estimated fire spread rate Two methods were used to determine average spread rate of the plume derived from 90 minutes of scans. San José State University Fire Weather Research Laboratory 2.4 ms ms -1 Convection Core Tracking Plume Tracking

Lidar: RHI Scans Backscatter intensity and radial velocity vertical cross sections o elevation angle with increments of 2.5 o and at a 95 o azimuth angle. 95 o San José State University Fire Weather Research Laboratory 1804 PST x z

Estimating Plume Height Backscatter Intensity 1830 PST 1746 PST For each range gate, the ratio F as a function of elevation angle ø can be computed by: By finding the maximum value of F throughout the scan, the maximum height of the plume can be found.

Estimating Plume Height Backscatter Intensity 1830 PST 1746 PST Doppler Radial Velocity (ms -1 ) 1746 PST 1830 PST

Summary Scanning Doppler lidar performed well, able to penetrate main convection core of the plume. Determination of the plume boundaries allowed for easier analysis of the velocity field around the plume. Reduced velocities observed downwind of the plume indicating ambient wind modification. Convection-core tracking may be a useful surrogate for estimating fire spread rate. Algorithm was able to identify the maximum height of the plume. Strong radial velocities beneath and within the plume. San José State University Fire Weather Research Laboratory

Future Work Develop faster scanning strategies. Lidar will be truck-mounted for an experiment in May. Test Lidar performance on more intense fires. San José State University Fire Weather Research Laboratory

Acknowledgements CalFire – Battalion Chief Dave McLean NSF Grant # USDA #07-JV San José State University Fire Weather Research Laboratory Neal Waters Photography