tundra fire in alaska: a weather perspective€¦ · fire in the tundra - over the past 50 years,...
TRANSCRIPT
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Tundra Fire in Alaska:A Weather Perspective
By: James WhiteThe Ohio State University: Atmospheric and Earth Sciences
Mentor: Rick ThomanNational Weather Service Alaska Region: Climate Science and Services Manager
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Project Background
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Fire in the Tundra
- Over the past 50 years, more than 4.5 million acres of Alaska tundra have burned2
- Fires are very rapid but sporadic, leading to difficult forecasts
- Impacts vegetation, wildlife, permafrost, carbon cycling, air quality and local communities3
- May increase rapidly with climate change4
Photo: Jennifer Barnes, National Park Service
Photo: Robert Ziel, Alaska Fire Service
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Fire Weather in the Tundra
- Ignition and fire growth centered around the summer solstice during peak solar drying and before late summer rains.
- Current models based off grass and shrub fuels7:
- Heavily weights wind as a critical spread variable
- Sensitive to short term, fine fuel moisture
- Long term build up important to burn severity, but not necessarily spread
Figure: Most common fuel models used in tundra fire, Adapted from (Scott, 2005)8
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The connection between weather and tundra fire growth has not been studied
in detail!
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Goal: Determine weather variables critical to forecasting tundra fire spread
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Step 1: Identify Tundra Fire
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Defining Tundra
- A vast, treeless arctic ecosystem marked by grasses, dwarf shrubs, mosses, and lichens and underlain with permafrost.
- We used vegetation maps from the NLCD5 and University of Alaska Anchorage6 to define tundra regions
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- Focused on only 3 regions due to lack of data:
- Noatak River Basin
- Seward Peninsula and SelawikRiver Basin
- Yukon-Kuskokwim River Delta
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Determining Fire Growth Days
- Used high resolution daily fire growth perimeters from the NASA ABoVE program which uses MODIS satellite data9
- Provides daily fire growth information for all large fires after 2001
- Worked with GaBriella to get yearly burned acreage since 1970
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Determining Fire Growth Days
- Zeke identified initial growth events as the most important to forecast, used a formula to highlight these dates
- Identified several large fire growth days from each region:
- Noatak: 17 days, Seward: 21 days, YK Delta: 30 days
- All days fell between May 24th and August 20th
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Some Tundra Fire Examples
- Noatak:
- 2005 Imelyak
- 2010 Sidik Lake
- 2010 Eli River
- 2010 Kaluktavik River
- 2012 Uvgoon Creek
- Seward Peninsula:
- 2003 Kerulu Creek
- 2004 Oregon Creek
- 2010 Kilovilik Creek
- 2011 Fish River
- 2015 Koyuk
- 2015 Mingvk Lake
- YK Delta:
- 2005 Talbiksok
- 2006 Negeethluk River
- 2009 Allman Creek
- 2013 Doestock Creek
- 2015 Whitefish Lake
- 2015 Fog River
Photo: Uvgoon Creek, Alaska Fire Service Photo: Whitefish Lake Fire, Alaska Forestry Service
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Step 2: Obtaining Reliable Weather Data
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Obtaining Reanalysis Data
- Previous analysis has shown that MERRA reanalysis performs best for Alaskan tundra locations10
- Retrieved weather information from MERRA for use in this analysis11
Photo: NASA Global Modeling and Assimilation Office
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Obtaining Station Data
- Retrieved historical station data to validate MERRA data and check historic fire weather index calculations12
- Lack of historical network density meant only one record could be accurately created for each region
- Noatak: KTZA2
- Seward: HDOA2 and QRZA2
- YK Delta: PABE
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Validating MERRA
- Using hourly station data and hourly data from MERRA, created a 15 year (2001-2015) summer (May 24th – Aug 20th) climatology of daily surface variables
- Compared MERRA grid cells with corresponding stations over climatology, showed good agreement for variables of interest.
- Used line of best fit to create a rough bias correction for some variables
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Step 3: Determining Significant Variables
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Significance Testing
- Performed significance tests on many surface variables for large fire spread days vs 15 year summer climatology
- Tests applied to MERRA data and surface stations independently reach the same conclusions.
- Hypothesis:
- Synoptic, wind driven spread
- Requires low humidity (~30%)
- Needs dry fine fuels
Photo: KNOM Radio Mission
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Significance Conclusions
- Synoptic wind speed is a poor fire forecast variable
- This does not mean local, plume associated winds are unimportant!13
- Note that tundra has climatologically high winds
- High maximum temperatures (~70° F) and low minimum relative humidity (< 45%) associated with strong diurnal solar heatingappear critical to fire spread
- In sunlight, tundra surfaces can heat significantly above 2m air temperature14
- Cloud cover and hence diurnal solar radiation is likely the single most important variable to forecast
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Step 4: Synoptic Analysis
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Synoptic Analysis
- Used MERRA and 30 year climatology to map variables
- Conducted a brief synoptic analysis of each identified fire event
- Created composite maps for the previously identified fire days
- Found clear synoptic patterns
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2m Temperature Anomaly
Noatak Seward YK Delta
Temperature Anomaly (F)
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Sea Level Pressure
Noatak Seward YK Delta
Pressure (mb)
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500mb Height
Noatak Seward YK Delta
Height (m)
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500mb Wind Speed
Noatak Seward YK Delta
Wind Speed (mph)
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Synoptic Conclusions
- Large synoptic patterns:
- Well above average 2m temperatures (+4° F or more)
- Broad surface low pressure pattern
- Weak, localized 500mb ridge often with a moderate Aleutian low
- Local 500mb wind speed minimum with a jet streak in the Gulf of Alaska
- This pattern is consistent with solar heating being more important than synoptic winds!
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A Note on Mixing
- Many extreme fire spread days associated with low level (850mb) dry air
- There seems to be a weak but independent relationship between humidity minimum and boundary layer depth
- These may indicate low level dry air mixing as a fire growth driver in some events
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Step 5: Fire Weather Index Performance
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Fire Weather Index System
- Looked at 3 main indices: FFMC, ISI, and BUI
- Used historic calculated daily variables, followed the same overall methodology as the variable significance testing
- Included all spread days
- Hypothesis:
- FFMC and ISI will both perform well
- BUI will perform poorly
Figure: Fire Weather Index System description, Mesowest Alaska Fire and Fuels
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Fire Weather Index Conclusions
- FFMC had high skill at identifying spread days and often even distinguishes between small and large spread days
- General threshold of ~85 FFMC for large spread
- ISI had little skill at distinguishing spread days
- BUI had some skill at generally identifying spread
- General spread values between BUI = 30 and 80
- BUI may assist in predicting burn severity which is not addressed here
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Step 6: Weather Model Performance
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Checking the GFS
- Checked GFS performance of some key forecast variables
- Pulled the GFS forecasts of 12 large growth days (4 from each region) and analyzed model skill up to 7 days from the event over the Alaska Region
- Used a normalized measure of skill
Figure: An example GFS output retrieved from Tropical Tidbits
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Weather Model Conclusions
- Synoptic variables had high skill by day 5
- Temperature had high skill by day 3
- Humidity had moderate skill by day 3
- Unfortunately, cloud cover data could not be retrieved from NCEP
- This analysis was very provisional with a very coarse resolution; GFS performance should be explored in significantly more depth!
- Special thanks to Brian Brettschneider for assisting in GFS data processing!
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Conclusion
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Improving Fire Weather Forecasts
- Cloud cover and solar heating are the most critical forecast variables
- Weak upper-level dynamics often promote growth
- FFMC is the single best fire weather index parameter
- GFS can have high skill for many fire variables within 3 days
Current tundra fire models often overweight wind as a spread variable.
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Future Research
- Consider seasonal climate parameters.
- Use information and data from this research to analyze and improve individual fire model performance in the tundra
- Broaden analysis to other tundra regions (Canada, North Slope, Alpine)
- Further explore short term variables such as dry air mixing and GFS performance
Figure: Most common fuel models used in tundra fire, Adapted from (Scott, 2005)8
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Acknowledgments
- Thank you NOAA Hollings for making this research possible
- Thank you Rick Thoman, John Walsh, Alison York, and Tina Buxbaumfor all your wonderful mentorship and support
- Thank you Robert Ziel, GaBriella Branson, Sharon Alden, Heidi Strader and everyone at AFS and AICC for you advice and hard work
- Thank you Vladimir Alexeev, Celia Fisher, and all the IARC REU students for the interesting lectures, conversations, and adventures
Thank you for an unforgettable summer!
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Citations
1. Ziel, R. (2015). Modeling Fire Growth Potential by Emphasizing Significant Growth Events: Characterizing a Climatology of Fire Growth Days in Alaska’s Boreal Forest. Paper presented at 11th Symposium on Fire and Forest Meteorology, Minneapolis, United States. Retrieved from https://ams.confex.com/ams/11FIRE/webprogram/Paper272864.html
2. Alaska Interagency Coordination Center. (2018). Alaska Fire History [Dataset]. Retrieved May 30, 2018, from https://fire.ak.blm.gov/predsvcs/maps.php
3. Higuera, P. E., Chipman, M. L., Barnes, J. L., Urban, M. A., & Hu, F. S. (2011). Variability of tundra fire regimes in Arctic Alaska: millennial‐scale patterns and ecological implications. Ecological Applications, 21(8), 3211-3226. doi:https://doi.org/10.1890/11-0387.1
4. Young, A. M., Higuera, P. E., Duffy, P. A., & Hu, F. S. (2016). Climatic thresholds shape northern high‐latitude fire regimes and imply vulnerability to future climate change. Ecography, 40(5), 606-617. doi:https://doi.org/10.1111/ecog.02205
5. Multi-Resolution Land Characteristics Consortium. (2014, October 10). National Land Cover Database 2001 [Dataset]. Retrieved June 2, 2018, from https://www.mrlc.gov/nlcd01_data.php
6. Alaska Natural Heritage Program, Boggs, K., Flagstad, L., Boucher, T., Kuo, T., Fehringer, D., . . . Aisu, M. (2016, July 20). Vegetation Map and Classification: Northern, Western, and Interior Alaska Second Edition [Dataset]. Retrieved June 5, 2018, from http://accs.uaa.alaska.edu/vegetation-ecology/vegetation-map-northern-western-and-interior-alaska/
7. Alaska Wildland Fire Coordinating Group. (2018). Fuel Model Guide to Alaska Vegetation. Retrieved from https://www.frames.gov/files/9515/2887/5259/AK_Revised_FuelModelGuide_FINAL_May2018.pdf
8. Scott, J. H., & Burgan, R. E. (2005). Standard Fire Behavior Fuel Models: A Comprehensive Set for Use with Rothermel’s Surface Fire Spread Model. Retrieved from https://www.fs.fed.us/rm/pubs/rmrs_gtr153.pdf
9. Loboda, T. V., & Hall, J. V. (2017, December 27). ABoVE: Wildfire Date of Burning within Fire Scars across Alaska and Canada, 2001-2015 [Dataset]. Retrieved May 29, 2018, from https://daac.ornl.gov/ABOVE/guides/Wildfires_Date_of_Burning.html
10. Lader, R., Bhatt, U. S., Walsh, J. E., Rupp, S. T., & Bieniek, P. A. (2015). Two-Meter Temperature and Precipitation from Atmospheric Reanalysis Evaluated for Alaska. Journal of Applied Meteorology and Climatology, 55, 901-922. doi:10.1175/JAMC-D-15-0162.1
11. Global Modeling and Assimilation Office. (2015). MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4 [Dataset]. Retrieved July 13, 2018, from https://disc.gsfc.nasa.gov/datasets/M2T1NXSLV_V5.12.4/summary?keywords=single-level%20diagnostics
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