Management Group

Prevention and Restoration Study Group

Process Study Group

Forecast Study Group

Circulation of knowledgeRESEARCH PLATFORM

Arctic Research used with IARC-JAXA Information System4th Phase Research plan(Wildfire research group)

3rd Phase

P2: Pre -fire Condition

P1: Damaged ForestP3: Combustion

P5: Healthy Forest P4: Recovery

Pinched from JAXA hompage

Final Target on the 4th Generation

Improving and summarizing the findings obtained during 1st and 3rd phases

The results gotten by IARC-JAXA project should be published by papers and dissertations

Contribute IPCC 5th, 6th AR, ICARP3 by IASC, and others via operational use by satellite and field data

Subgroup Japan-side US-side Objective Approach

Management Tsuyuzaki (PI)Fukuda MHomma T

Hinzman L Oversight and Integration Communications, Meetings and coordination

Process Study Group現象解明班

Kushida KSaito KHobara SMatsuura YNoguchi KMorishita TJomura M

Kim Y-WNakai THeinrichs TZhou JMacfarlane S

Plant functional type map(tundra)Monthly C budget MapMonthly Burnt moss map(boreal forest)Snow water equivalent

US: Satellite and Field observationJP: Satellite and Field observation Discussion between both

Forecast Study Group火災予測班

Hayasaka HKimura KHarada KSawada YFukuda MNarita K

Cahill CF(Yoshikawa K)Iwahana GMacfarlane S

Wildfire detection algorithmThaw depth

JP: algorithm development US: comparisonJP: US: ground measurement, UAV observation

Prevention and Restoration Study Group火災抑制・ 修復班

Tsuyuzaki SHarada K Kodama Y (Chikita K)Sawada Y Kimura K Ishii YNarita K

Chapin FS(Yoshikawa K)Iwahana GNakai T

PF Fieldwork (Thaw slamp) Firespread model

US: Satellite analysis & mapping Meteorological dataJP: Field observation dataJP: Simulation US: UAV obs. (from Forecast G)

GHG Flux Mesurement Group

Kodama Y HarazonoIwataKim Y W

Fire impact and regionalestimation of GHG flux

US: Tower measurementJP: Meteorological measurement

Structure

(P1)

Prevention and Restoration Study Group (P2)

Koichiro HARADAMiyagi University

topics

Our group is constructed to develop the past (and future) findings to apply the prevention and restoration of tundra and taiga. There are three applications planned. • Conservation and restoration of vegetation after

severe wildfire• Producing hazard map of suspended sediment

caused by thawing of permafrost after wildfire• Offering of wild fire spread forecast information

Conservation and restoration of vegetation after severe wildfire

From the past studies conducted in tundra and taiga in Alaska, These are to clarify: • Relationships between successional direction and

fire severity• Relationships between environmental factors and

the spontaneous succession• Restoration of P. mariana forest through facilitating

Sphagnum recovery• Validation of restoration success on regional scale,

by the comparison with satellite data.

Seed immigration

Unburned vs Burned

SeedlingEmergence Survival Growth

Seed trap

Germination(2006-2010)

Summer 2006

Picea mariana vs deciduous trees

EnvironmentBurned severity [Canopy, ground]Light (Canopy openness, Albedo)

Topography / Permafrost /Moisture / Nutrients (Litter)

Large-scale environmental changes remote sensing

Monitoring

SpringSummer

2005Summer

2008

SpringSummer

2006

SpringSummer

2007

Biomass / Cone Summer

2009

Litter

Summer2010

We have done

Objectives:

1. To detect revegetation patterns in the early stages of succession along fire severity gradient

Seed immigration and emergence were determined soon after the wildfire (confirmed by monitoring for 6 years)

Next step, we have to confirm survival and growth! 2. Restoration (and conservation) of ecosystems by introducing

Sphagnum propagules

3. The restoration technique should be validated over a wide area, by using remote sensing data

What we should do (future plan) (2011-2014)

Additional plan

Supporting the other project(s)Do you need vegetation surveys?

Baby fire

Research Plan

• LocationPoker Flat , Seward Peninsula (Alaska)

• Expected ResultsConservation and restoration of Sphagnum vegetation have been controversial in boreal regions. We provide the new insights on the restoration of P. mariana forest through the introduction of Sphagnum forest floor.

Offering of wild fire spread forecast information

(1) Wild fire detection with MODIS data analysis(2) Weather prediction simulation,(3) Wild fire expansion simulation (4) Showing the results of wild fire expansion simulation through internet

IJIS

(2)

(1)

(3) (4)

Producing hazard map of suspended sediment caused by thawing of permafrost after wildfire

• To estimate an amount of soil flowed into the river or lake, which is caused by the retrogressive thaw slump after wildfire,

• To clarify an impact of thaw slump to the surrounding environment.

Research Plan

• 2011-2012:To build the wild fire expansion simulation in semi-real time

Selawik River suspended sediment transportation

AVNIR-2 July 22, 2007

0.1 1 10 100 10001

10

100

1000

10000

100000

1000000 before con-fluencethaw slump

distance from the thaw sump (km)

suspended s

edim

ent

concentr

ati

ons (

mg/l)

RGTS near Toolik Lake2006

2010

Observation plan

• Field observations will be conducted to measure the amount of discharged sediments from the thermokarst, and to measure the sediment transported by the river system. Traditional triangular survey will hired to estimate the volume of discharged sediments at the thermokarst site. The observation will be held in Toolik Lake, Alaska.

Research Plan

• LocationToolik Lake and more…. (Alaska)

• Expected Results An estimation of amount of flowing soil will be developed by using the satellite data, a hazard map can be created, and information about a disaster will be released.

Satellite data

• AVNIR-2, PALSAR and PRISM, ALOS, for hazard mapping

• MODIS for forecast information

Forecast Study Group Forecast Study of wild fire occurrence and environmental change caused by wildfire

Hiroshi HAYASAKA Graduate School of Engineering, Hokkaido UniversityKita-ku, Sapporo, Japan, hhaya@eng.hokudai.ac.jp

2009 Minto Fire: Photo by Frank V. Cole

(P3)

MembersGroup leader: Hiroshi HAYASAKA (Hokkaido Univ.)Forest, tundra, and peat fire, Hotspot, Weather1. Koichiro HARADA (Miyagi Univ.) Permafrost2. Yuki SAWADA (Fukuyama City Univ.) Permafrost3. Kenji YOSHIKAWA (UAF) Permafrost4. Cathy CAHILL (UAF) Smoke, Hotspot detection5. Keiji KIMURA (Hokkaido Univ.) Fire Modeling

※ Collaboration Researchers in IARC (satellite, weather…) , GINA, & AFS (Alaska fire service)

Background

Minto Fire, Aug.5, 2009Photo by Frank V. Cole

0

5,000

10,000

15,000

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25,000

30,000

0 10 20 30 40 50 60Rank

Bu

rnt

area

(km

2)

1σ

2σ

4σ

3σ

Average

Alaska1956-20102004

1957

2005

1969

19902009

1977

20021988

1997 1991

Large Top 11 Fires

Smallest 5 Fires

Once in a decade

Thrice in a decade

2007

Alaskan Fire History by Size

Severe Lightning & Drought Year

Severe Lightning & Drought Throughout Summer9 Large Fires (>1,000 km2)

Severe Lightning but Wet Year

North Slope, Sep. 29, 2007

Tundra Fire1,039km2

Purposes Use of satellite imagery and ground-truth measurements to enhance and improve models for determining location of fires, fire behavior (expansion, burn severity, etc.) and fire impacts on local and regional climate and global change.(1) 　 Forecast for wild fire occurrence(2) 　 Prediction of fire occurrence in tundra(3) 　 Prediction of variation of active layer in permafrost(4) 　 Determination of satellite thresholds for detectable wild fire smoke(5)　 Verification of wild fire occurrence model, smoke flow model, and satellite detection algorithm

1 & 2. Forecast for wild fire occurrence 1-1. Prediction of wild (tundra) fires= forecast of lightning occurrence

Hiroshi HAYASAKA (Hokkaido Univ.)

A2. Check Lightning Forecast Index:~12 amLFI(N) = 0.7*Te850, (N-1) - LIFT (N)

(N=day number)

A3. Check satellite images: ~12 amMODIS, GEOS…. IR3 (6.5 〜 7.0μ

ｍ )Thundercloud, vapor flow,….

B. Prepare lightning or fire occurrence: 13~ pm ≅73%

OrdinaryCell Thunderstrom

Surface & Underground Fire

Thunderclouds Vapor flow& Lightning

Forecast: Daily→ Weekly→ Monthly→ Seasonally

IR3 (6.5 〜 7.0μ ｍ )

A1. Check weather and fuel conditions: ~12 am (Temp., Rainfall, weather maps….)

Methods:1. Analysis: using data sets of thaw depth and

ground temperature after forest and tundra fires.

2. Simulation: to show a variation of thaw depth in each fire severity, and predict a future thaw depth

3. Prediction of variation of active layer in permafrost

Y. SAWADA, K. HARADA, K.YOSHIKAWA

Thermal resistance of the remaining organic layer determine the thickness of active layer

Temperature changes of active layer in Poker Flat. “High disturbance” site has large amplitude of temperature changes.

Yuki SAWADA (Fukuyama City Univ.)

0 2 4 6 80

50

100

150

200

250

300

350

ξ

2007

2009

2008Disturbance

High

Moderate

Low

Active layer thickness and index of the thermal resistance of organic layer (ξ; Yoshikawa et al., 2003) .

Mapping of thermal condition of permafrost after wildfire using field and satellite data

• Surface roughness from field observations• Entropy from ALOS PALSAR PLR data

0

20

40

60

80

100

120

140

0 10 20 30 40 50

Hei

ght (

m)

Distance from starting point (m)

unburned

burned

rough: 18.7

smooth: 8.9

burned

unburned

Fig. Surface roughness measured in Kougarock site.

Fig. Entropy image form ALOS PALSAR PLR data.

Koichiro HARADA (Miyagi Univ.)

4. Determination of satellite thresholds for detectable wildfire smoke

Wildfire Aerosol, Satellite, and Model Integration

Purpose:1) To obtain high-quality ground and airborne measurements of aerosol size distributions and compositions for satellite smoke retrieval and smoke emission model input and validation2) To obtain infrared and synthetic aperture radar (SAR) imagery of fire perimeters and behavior for validation of satellite fire perimeter determinations and model spread predictions

Cathy CAHILL (UAF)Gregory W. Walker

Figure courtesy of the Geographic Information Network of Alaska

Published Papers

1. Recent Anomalous Lightning Occurrence in Alaska – the Case of June 2005-, Murad Ahmed Farukh, Hiroshi Hayasaka, Keiji Kimura, Journal of Disaster Research, 6-3, 321-330, 2011. 2. 　 Characterization of Lightning Occurrence in Alaska Using Various Weather Indices for Lightning Forecasting, Murad Ahmed Farukh, Hiroshi Hayasaka and Keiji Kimura, Journal of Disaster Research, Vol.6-3,343-355, 2011.

Under reviewing:??. 　 Active Forest Fire Occurrences in Severe Lightning Years in Alaska, Murad Ahmed Farukh, Hiroshi Hayasaka, Journal of Natural Disaster Science, Vol.??-??,??-??, 201?.