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EFFECTS OF CLIMATE CHANGE ON FOREST FIRES OVER NORTH AMERICA AND IMPACT ON U.S. OZONE AIR QUALITY AND VISIBILITY.

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slide1

EFFECTS OF CLIMATE CHANGE ON FOREST FIRES OVER NORTH AMERICA AND IMPACT ON U.S. OZONE AIR QUALITY AND VISIBILITY

Rynda Hudman 1,2, Dominick Spracklen1,3, Jennifer Logan1, Loretta J. Mickley1, Maria Val Martin1,4, Shiliang Wu1,5, Rose Yevich1, Alan Cantin6, Mike Flannigan6, Tony Westerling7

UC BERKELEY GEOGRAPHY SEMINAR DECEMBER 10, 2008

Affiliations: 1 School of Engineering, Harvard 2 Now at UC Berkeley 3 Now at University of Leeds 4 Now at Barcelona Supercomputing Center 5 Now at Michigan Tech 6 Canadian Forest Service 7 UC Merced

slide2

WHY DO ATMOSPHERIC SCIENTIST CARE ABOUT WILDFIRES?

  • Releases 1-4 Pg C / yr (~30-50% of the fossil fuel source)
  • Accounts for 2/3 of the variability in CO2 growth rate between 1997 and 2001
  • 20-60% of the global organic carbon aerosol (particulate) emission, 30% of the black carbon (soot) emission
  • Potential for climate feedbacks
  • Impacts ozone/aerosol air quality, visibility, human health
slide3

TROPICS DOMINATE FIRE ACTIVITY BUT NORTH AMERICAN RECORD PUNCTUATED BY LARGE FIRE YEARS

[Bowman et al., 2009]

Mean area burned:

~3 million hectares

2x size of Connecticut

Large fire years  increase emissions by X10

slide4

NORTH AMERICAN FIRES AFFECT ATMOSPHERIC COMPOSITION ON A HEMISPHERIC SCALE

In 2004, a blocking ridge set up over Canada and Alaska creating one of the

largest fire seasons on record.

http://asl.umbc.edu/pub/mcmillan/www/index_INTEXA.html

slide5

LOCAL EFFECTS OF WILDFIRE EMISSIONS

Hayman fire caused worst air quality ever in Denver

  • 56000 ha, June 8-22, 2002
  • 30 miles from Denver and Colorado Springs
  • EPA 24-hr standard = 35 µg/m3, and annual standard = 15 µg/m3.

June 8, 2002

June 9, 2002

PM10 = 40 μg/m3

PM2.5 = 10 μg/m3

PM10 = 372 μg/m3

PM2.5 = 200 μg/m3

Colorado Department of Public Health and Environment

Vedal et al., Env Res, 2006

slide6

WILDFIRE DRIVES INTERANNUAL VARIABILITY IN ORGANIC CARBON AEROSOL IN THE SUMMER

Model gives same variability as observed OC in summer at IMPROVE sites in the West

OC contribution to total fine aerosol:

40% in low fire years

55% in high fire years

same fires every year

[Spracklen et al., 2007]

[Spracklen et al., 2007]

slide7

PRESENT DAY FIRE IMPACTS ON OZONE

Ozone enhancement from NA biomass burning 0-2 km

Simulated July 2004 mean

Max enhancement during July 15-24 2004

8-hr max ozone air quality standard in the United States = 75 ppbv

[Hudman et al., 2009]

slide8

CLIMATE DRIVES FIRE ACTIVITY OVER NORTH AMERICA

Temperature

Rainfall

Wind speed

Relative Humidity

Canadian Fire Weather Index Model

Other factors:

Large Scale circulation

Fuel availability

Ignition Source

Fire Suppression

slide9

OBSERVED INCREASE IN WILDFIRE ACTIVITY OVER NORTH AMERICA DUE TO CLIMATE CHANGE?

Area burned in Canada has increased since the 1960s, correlated with temp. increase.

5 year means

[Gillett et al., 2004]

Increased fire frequency over western U.S. in recent decades – related to warmer temp., earlier snow melt.

[Westerling et al., 2007]

slide10

PREDICTING THE IMPACT OF FUTURE CLIMATE CHANGE ON WILDFIRE AND AIR QUALITY

1. DEVELOP RELATIONSHIPS BTWN CLIMATE AND ANNUAL AREA BURNED

OBSERVED AREA BURNED

OBS WEATHER & FUEL MOISTURE/ FIRE SEVERITY

Yearly Area Burned = C1X1 + C2X2 + … + C0

Climate Model

Output

2. CLIMATE MODEL OUTPUT PREDICT FUTURE AB

3. PRED. FUTURE AIR QUALITY

FUTURE AREA BURNED

Emissions

CHEMICAL TRANSPORT MODEL

slide11

I. WESTERN U.S. ECOREGIONS & MET USED IN REGRESSION

Combine ecoregions of similar vegetation and topography

Use observed meteorology from surface weather stations (USFS)  FWI

(Spracklen et al., 2009)

slide12

WHERE ARE THE FIRES IN THE WESTERN U.S.?

Mean area burned (1º x 1º grid) in 1980-2004 (Westerling, UC Merced)

Mean fuel consumed

Large areas burned in CA and the southwest, but fuel burned is greater in forest than in shrub ecosystems

The Pacific North West and Rocky Mountain Forests are most important for biomass consumption and emissions.

(Spracklen et al., 2009)

slide13

PREDICTING WILDFIRE OVER THE WESTERN U.S.

Area Burned (ha)

R2 of Area Burned regressions

48%

57%

52%

Area Burned (ha)

37%

24%

49%

Year

Regressions ‘capture’ 24 – 57% of the interannual variability in area burned over western US. Temperature contributes 80-90% of the regression in forested regions.

(Spracklen et al., 2009)

slide14

CHANGES IN MAY-SEPT TERMPERATURE (2000 – 2050)

GISS GCM3 A1B Scenario - CO2 concentrations reach 522ppm

Temperature

Predicted met Changes

Temp. +1-3ºC across West

Rainfall and RH increase slightly

Wind speed decreases slightly

(Spracklen et al., 2009)

slide15

PREDICTED INCREASE IN AREA BURNED

Pacific Northwest US

Observed area burned

Predicted area burned

78%

increase

Rocky Mountain Forests

175%

increase

Predicted area burned for 1995-2004 does not match observed areas on a yearly basis, as it is based on GCM output, but 10 year mean is the same.

(Spracklen et al., 2009)

slide16

PREDICTED INCREASE IN AREA BURNED

+ 1-3K

Pacific Northwest US

Rocky Mountain Forests

Predicted area burned for 1995-2004 does not match observed areas on a yearly basis, as it is based on GCM output, but 10 year mean is the same.

(Spracklen et al., 2009)

slide17

FUTURE WILDFIRE AND PARTICULATE AIR QUALITY

Change in wildfire biomass consumption

AB + FUEL

Emissions

Δbiomass consumption = + 90%

Change in surface OC aerosol (Jun-Aug)

Δsurface OC aerosol = + 40%

Chemical Transport Model

Climate change projected to cause a 90% increase in biomass consumed and 40% increase in OC concentrations by 2050.

(Spracklen et al., 2009)

slide18

FUTURE WILDFIRE AND PARTICULATE AIR QUALITY

Present day fires in black, 1996-2000

Future fires in red, 2046-2050

OC increases by 40%, EC increases by 20% (not shown).

For OC, 75% of increase is from fire emissions, 25% from higher biogenic emissions in a warmer climate.

(Spracklen et al., 2009)

slide19

PREDICTED JULY MEAN MAXIMUM 8-HR OZONE

perturbation from fires doubles

5 Years Future (2046-2050) vs. 5 Years Present (1996-2000)

Consistent with these results, recent observational estimates of regional enhancements of 2 ppbv for each 1 million acres burned [Jaffe et al., 2008]

(Hudman et al., in prep)

slide20

SUMMARY WESTERN U.S.

  • Regressions capture much of the variability in annual area burned over the western U.S. (24-57%). Temperature is the key predictor.
  • 2050 climate change (A1B) is predicted to increase annual mean area burned over western U.S. (+54%)  90% increase in biomass consumed relative to the present-day driven by 1-3K increase in temperature.
  • Future fires drive a 40% increase in organic carbon aerosol over the western US and a 1-3 ppbv enhancement (doubling fire enhancement) in summertime afternoon ozone.
slide21

II. BOREAL ECOREGIONS & MET USED IN REGRESSION

Largest Area Burned over Plain regions

[French et al., 2003]

[Stocks et al., 1999]

[105 ha]

Combine ecoregions of similar vegetation and topography (12 ecoregions)

Alaska wx stations (USFS) & Canadian wx stations (CFS)

(Hudman et al., in prep)

slide22

SUMMER 2004: 500hPa GEOPOTENTIAL HEIGHT

Height of pressure level above mean sea level

Strong ridges are accompanied by warm and dry weather conditions at the sfc

+60

Jul 1 – Aug 15 2004

Anomaly

Strong Alaskan Ridge  record fires

(Hudman et al., in prep)

slide23

CANADIAN FIRE WEATHER INDEX MODEL

Drying time

2/3 day

15 day

52 day

Severity Rating

Severity Rating is a combination of drought and fire spread potential

slide24

REGRESSIONS CAPTURE VARIABILITY IN REGIONS WITH LARGEST AREA BURNED (15-62%)

  • ALASKA/CANADA SUMMARY: 2-3 predictors chosen per region
  • Most Common Predictors:
  • Monthly/Seas. 500 mb GPH Anomaly (Max contributor 7/12 ecoregions)
  • Max/Mon./Seasonal Severity Rating (Max contributor in 3/12 ecoregions)

More influenced by fire suppression and human caused fires

GPH was chosen over temperature

(Hudman et al., in prep)

slide25

PREDICTING WILDFIRE OVER CANADA AND ALASKA

- - - national totals for Canada (not included in regression) + Alaska

Regressions capture 71% of the variability in Canada and Alaska

About as good a non-linear regression which use many more variables

(Hudman et al., in prep)

slide26

DOES RAIN OFFSET TEMPERATURE/GPH INCREASE?

GISS simulated May – August 2046-2055 vs. 1996-2005

June 500mb anomaly over Fairbanks, Alaska (1940 – 2006)

GISS Mean 1999-2008 : -14 m

2045-2054 : 5 m

[Fairbanks GPH Courtesy of Sharon Alder, BLM]

(Hudman et al., in prep)

slide27

DOES RAIN OFFSET TEMPERATURE INCREASE?

GISS simulated May – August 2046-2055 vs. 1996-2005

Rain

Seasonal Severity Rating

Dry spell length important…GISS suggests decreased dry spell length, likely very model dependent

(Hudman et al., in prep)

slide28

MOST GCMS PREDICT INCREASED SUMMERTIME PRECIPITATION

A1B 1980-1999 vs. 2080-2099

Predicted Summer ppt Change

# of models showing increased ppt

Dry spell length important…GISS suggests decreased dry spell length, likely very model dependent

(IPCC, 2007, Ch 11)

slide29

PREDICTED CHANGE IN AREA BURNED

2000-2050 change in area burned

GPH dominates

DSR dominates

Combination

34% increase over Alaska, 8% (-34 to +118%)increase in Canada. Large regional variability. Seems consistent with recent study by Meg Krawchuck (UCB)

(Hudman et al., in prep)

slide30

PREDICTING FUTURE AIR QUALITY

  • Distribute annual area burned by month ( ha/month)
  • Randomly place AB w/in ecosystem into 1°x1° (based on current fire size stats)
  • Combine with fuel consumption which varies throughout season based on fuel moisture + make assump. severity (kg DM/ha)
  • Combine with emission factors ( g species/kgDM)
  • Assume 20% of emissions in FT (Maria Val Martin MISR work)
  • Input into GEOS-Chem CTM (w/ GISS met)  future air quaity

(Hudman et al., in prep)

slide31

PRESENT DAY SURFACE OZONE ENHANCMENT JUL-AUG

Fires predicted to enhance 8-hr max ozone by 3-10 ppbv, 1-4 ppbv reaching Midwest U.S.

(Hudman et al., in prep)

slide32

CHANGE IN SURFACE OZONE ENHANCMENT JUL-AUG

Doubling of enhancement over Alaska, 1-2ppbv increase over populated Quebec cities and Midwest (20-40% increase)

A decrease of ozone toward the Arctic

(Hudman et al., in prep)

slide33

PERCENT CHANGE IN SURFACE OC/EC JUL-AUG

Preliminary Result

[%]

Transport of Black Carbon aerosol to the Arctic decreases by 40%

(Hudman et al., in prep)

slide34

FUTURE WORK

  • Examine change in extreme events using current simulations and Regional modeling (U. Houston)
  • Implement plume rise model into GEOS-Chem (Maria Val Martin)
  • Improve regressions of desert southwest using PDSI (Harvard)
  • Update Canada/Alaska regressions LFDB when avail.
  • Do an envelope study of GCM response to Canada/Alaska regressions to look at variability in response (Harvard)
  • Impacts of new understanding of NOx emission factors on ozone response (Harvard, Anna Mebust UCB)

Thanks for your attention!

slide35

SUMMARY CANADA/ALASKA

  • Regressions capture much of the variability in annual area burned over Alaska (53-57%), and Canada (15-62%). Key predictors : 500 mb GPH anomaly & severity rating.
  • 2050 climate change (A1B) increases annual mean area burned: Alaska (+34%) relative to the present-day, but unlike most previous studies little change over Canada as a whole (8%), but varies regionally (-34 - + 118%) due to increases in GCM precipitation vs. temperature (scenario/GCM dependent).
  • Present day ozone enhancements due to wildfire 3-10 ppbv over Canada and Alaska. Future fire increases range from -2 - +4 ppbv. Large decreases of BC toward the Arctic.
slide39

1. WILDFIRE PREDICTION MODEL

Observed daily Temperature, Wind speed, RH, Rainfall,

500hpa GPH anom. (Canada/Alaska)

Daily forest moisture/fire danger parameters

Canadian Fire Weather Index

System

Aggregate area burned to ecosystem

Linear stepwise regression

Area burned

database

Predictors of Area Burned

Stepwise linear regression between meteorological/forest moisture variables & area burned

[Flannigan et al. 2005]

slide41

IMPLICATION OF RISING OZONE BACKGROUND FOR MEETING AIR QUALITY STANDARDS

Europe AQS

(8-h avg.)

Europe AQS

(seasonal)

U.S. AQS

(8-h avg.)

U.S. AQS

(1-h avg.)

0 20 40 60 80 100 120 ppb

Preindustrial

ozone

background

Present-day ozone background at northern midlatitudes

EPA policy-relevant background (PRB) : U.S. surface ozone concentrations that would be present in absence of North American anthropogenic emissions

PRB is not directly observable and must be estimated from global models

slide42

GEOS-Chem GLOBAL MODEL OF TROPOSPHERIC CHEMISTRY

http://www.as.harvard.edu/chemistry/trop/geos

  • Driven by NASA/GEOS assimilated meteorological data with 6-h temporal resolution (3-h for surface quantities)
  • Horizontal resolution of 1ox1o, 2ox2.5o, or 4ox5o; 48-72 levels in vertical
  • Detailed ozone-NOx-VOC-PM chemical mechanism
  • Applied by over 30 research groups in U.S. and elsewhere to a wide range of problems in atmospheric chemistry
  • Extensively evaluated with observations
  • for ozone and other species (~200 papers in journal literature)
slide43

Mean Asian surface pollution

enhancement (GEOS-Chem)

slide44

Global Carbon Emissions

49% Africa

13% South America

11% equatorial Asia

9% boreal forests

6% Australia

slide45

Short-lived Pollutants Affect Climate and Air Quality

[IPCC, 2007]

Regulations of short-lived species that improve air quality and warm the planet (BC) present a “win-win” situation, while regulations of short-lived species that reduce cooling and improve air quality (SO2) present a “win-lose” situation.

slide46

ACCOUNTING FOR DRIZZLY GCM

Observations

GISS Present Day

GISS Future

-------- Corrected (GISS – 1.5 mm)

_____ Uncorrected

Frequency

Dryspell Length (days)

slide47

An increase from current conditions (red) is indicated by a PΔ greater than unity,

little or no change (yellow) is indicated by a PΔ around unit, and a decrease (green) is

indicated by a PΔ less than unity. Panels show the mean PΔ for the ensemble of ten

FIRENPP (A–C) and FIREnoNPP (D–F) sub-models. Climate projections include 2010–2039

(A, D), 2040–2069 (B, E) and 2070–2099 (C, F).

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