background

Overarching scientific questions

• Why does this terrestrial carbon sink exist?

• Where is it located?

• What is the cause of the large degree of interannual variability?

• How is this terrestrial sink likely to change with time?

Need for regional to continental studies

• The intersection of climate variability and biome is regional.

• Political units are regional to continental. (carbon cycle manipulation, emission credits)

• Human land use activities and natural disturbance patterns are regional.

Motivation I

What is and what governs ecosystem-atmosphere exchange of CO2 on spatial

scales of geopolitical and bioclimatological relevance?

Motivation II

What is and what governs the interannual variability in ecosystem-atmosphere exchange of CO2 on spatial scales of geopolitical and bioclimatological

relevance?

Methods for quantifying the terrestrial carbon cycle

Ch

am

be

r flu

x

Tower flux

Airborne flux

Forest inventory Inverse study

year

month

hour

day

Tim

e S

cale

Spatial Scale

(1m)2 = 10-4ha

(1000km)2 = 108ha

(100km)2 = 106ha

(10km)2 = 104ha

(1km)2 = 102ha

Rearth

Flux tower upscaling hypothesis

Flux:R, NEE, GEP

Climate variables (x, y)

Flux = ax + by + c,interpolate fluxes over ~ (1000 km)2

Each point~ (1 km)2

Segregate further by ecosystem characteristics?Stand type (conifer, deciduous, grass, crop)Stand age (young, mature, old)

Flux tower upscaling hypothesis II – interannual variability

flux) = flux – mean flux

Climate variables (x, y)

(flux) = ax + by + c,interpolate interannual variability in fluxesover ~ (1000 km)2

Each point~ (1 km)2

Ecosystem fluxes respond similarly to climate variabilityacross a wide range of forest types and ages(?)

Inverse Modeling of CO2

Air Parcel Air Parcel

Air Parcel

Sources Sinks

wind wind

SampleSample

Changes in CO2 in the air tell us about sources and sinks

Complementary nature of inversion downscaling and flux tower upscaling

Inversion downscaling Flux tower upscaling

Excellent spatial Intrinsically local

integration measurements.

Strong constraint on Difficult to upscale flux

flux magnitude magnitudes. Variability easier.

Poor temporal Excellent temporal resolution

resolution

Limited mechanistic Strong mechanistic

understanding. understanding

Joint constraints! Complementary methods

Upscaling

Downscaling

Ch

amb

er

flux

Tower flux

Airborne flux

Forest inventory Inverse study

year

month

hour

day

Tim

e S

cale

Spatial Scale

(1m)2 = 10-4ha

(1000km)2 = 108ha

(100km)2 = 106ha

(10km)2 = 104ha

(1km)2 = 102ha

Rearth

ChEAS regional intensive proposal

Chequamegon Ecosystem-Atmosphere Study (ChEAS) region flux towers

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WLEF tall tower (447m)CO2 flux measurements at: 30, 122 and 396 mCO2 mixing ratio measurements at: 11, 30, 76, 122, 244 and 396 m

WLEF CO2 flux and mixing ratio observatory

NOAA CMDLPenn StateU. MinnesotaUSDA-FS

Support from:NOAADoE

ChEAS land cover/vegetation

Green = upland forest Purple = forested wetlandBlue = open water Yellow = agriculture or grassland

Why is the ChEAS region unique?• Existing flux tower network, including old growth,

wetlands, world’s only tall tower with CO2 fluxes• Existing “top-down” efforts

– Ring of towers: Davis, Richardson, Denning– COBRA regional: Lin, Gerbig, Wofsy– Simple ABL budgets approaches: Helliker, Berry, Bakwin

• NOAA CMDL tall tower and aircraft sampling site• Extensive paleoecological history and relatively simple

land use history• Simple topography, light population density • Complex forest mosaic including human management,

extensive wetlands.• Ecosystem intersection nearby – temperate forest, boreal

forest, agriculture/prairie – vulnerable to climate change

What issues general to the NACP can be addressed via a ChEAS regional intensive?

Regional flux estimate methodology• Downscaling: The techniques needed to determine regional carbon

fluxes via atmospheric budgets are still experimental. Existing work is advancing this methodology in ChEAS.

• Upscaling: The measurements and models needed to upscale fluxes to regional scale are uncertain. The density of flux towers, simple topography, complex forest mosaic and tall flux tower in ChEAS collectively present a unique site for upscaling experiments.

• Evaluation: Verifiable regional flux estimates (at least two independent methods) have yet to be constructed. This can be done at ChEAS.

• Regional mechanistic understanding: The mechanisms that govern interannual and decadal-scale forest-atmosphere carbon exchanges remain uncertain. This mechanistic understanding is limited by the lack of regional flux measurements that can accurately resolve seasonal-scale fluxes yet be deployed for several years. This can be achieved at ChEAS.

Flux tower up-scaling with simultaneous top-down constraints

Within stand: biometric data,chamber fluxes

Stand: Eddy covariance flux towers

Forest: Map ecosystem variables, model fluxes

WLEF tower

Continent: Map biomes and climate, model fluxes

Region: Map ecosystem variables, model fluxes

N. Wisconsin [CO2]

N. American [CO2]

What more region-specific scientific issues can be addressed via a ChEAS regional

intensive?

• What is causing a net source of carbon dioxide to the atmosphere at the forest (WLEF) scale?

– Forest management practices?

– Climate change and wetland drying?

• Are forest-scale (WLEF) fluxes representative of the region? What is preventing simple regional flux-tower up-scaling from being successful?

– Wetland margins?

– Forest management/disturbance history?

– Systematic errors in tower flux measurements?

– Find general guidance for up-scaling methodology

What more region-specific scientific issues can be addressed via a ChEAS regional

intensive?• What is causing observed interannual variability in carbon

fluxes? Can consistent mechanistic explanations be found across the plot, stand, forest and regional scales?

• Methane and wetlands:– How is the methane/CO2 flux ratio linked to climate and the

hydrological budget?

– Are the combination of methane and co2 fluxes in the region a net source or sink for GHG forcing?

– How does management and climate influence this net GHG source/sink?

What additional resources are needed for a ChEAS region intensive?

• Methane measurement infrastructure• Continued support for the existing flux tower

network• Additional emphasis on:

– Remote sensing and advanced ecosystem modeling– Forest inventory and disturbance history studies

• Longer-term support of a regional mixing ratio observing network, and associated inverse modeling.

• Support for integration of existing measurements

Existing ChEAS research and results

ChEAS flux tower arrayForest-scale flux: WLEF tower, 1997-present

Dominant stand types and flux towers:

Northern Aspen Forested Coniferhardwood wetland

youn

g

old

m

atur

e

Willow Creek (UMBS) Lost Creek Chen B2000-present 1999-present 2001-present 2002-presentBolstad et al, in pressCook et al, in prep

Chen A2002–present

Sylvania2002-presentDesai et al, in prepDesai et al, B52D-04

Chen mobile Chen mobile2003 2002

Yi et al, 00Berger et al, 01Davis et al, 03Ricciuto et al, B51

Mackay et al, 02Mackay et al, H29Ewers et al, 02Ewers et al, H30

Testing the upscaling hypothesis:

Regional clusters of flux towers

• Can fluxes be up-scaled from stand to forest or region?

• Clusters can isolate the role of ecosystem characteristics via identical climate across sites.

• What must be measured and mapped for flux upscaling?

Respiration and soil moisture content

NEE of CO2 at WLEF(forest scale)

1. The region is a net source of CO2 to the atmosphere.

2. Interannual variability is significant – resolved by the measurements.

3. Interannual variability is caused by changes in the timing of leaf-out, and correlated with changes in soil moisture.

 

NEE (gC m-2)

Respiration (gC m-2)

Photosynthesis (gC m-2)

WLEF 1997 27 991 964

WLEF 1998 48 986 938

WLEF 1999 100 1054 954

WLEF 2000 74 1005 931

WLEF 2001 141 1067 926

WLEF average 78 1021 942

Willow Creek 2000 -347 762 1109

Willow Creek 2001 -108 741 849

Willow Creek 2002 -437 648 1085

Willow Creek average -297 717 1014

Lost creek 2001 1 759 758

Lost Creek 2002 -58 631 689

Lost Creek average -30 695 724

NEE and gross fluxes at ChEAS sites: 1997-2002

Chamber respiration fluxes

Table 4. Estimated annual respiration for the whole ecosystems and components, 1999-2002. All rates are reported in Mg C ha-1 yr-1.Bolstad et al, in press.

Forest type andrespiration (soil + leaf + stem)

1999 2000 2001 2002

Northern Hardwoods

11.55 11.92 12.71 10.89

MatureAspen

13.57 13.96 14.69 12.95

Intermediate Aspen

9.93 10.24 10.76 9.49

ChEAS upscaling test results1. Climate alone does not explain ChEAS CO2 fluxes.2. The WLEF footprint is a source of CO2 to the

atmosphere.• drying wetlands? • disturbance/management?

3. WLEF fluxes cannot be explained as a linear combination of Lost Creek and Willow Creek fluxes.

• aspen? conifers? WLEF footprint dissimilar? systematic errors that differ among flux towers?

4. Soil + leaf + stem respiration is similar in aspen and northern hardwoods in the Willow Creek area.

• WLEF high respiration rate due to coarse woody debris?

Interannual variability upscaling results

1. ChEAS annual fluxes (R, GEP, NEE) are moderately coherent across ChEAS sites, 2000-2001. (Caterpillars, not climate?).

2. ChEAS chamber and tower R fluxes show similar variability, 2001-2002, across sites. (2001 high flux, 2002 low flux).

(WLEF) = a*(W Creek) + b*(L Creek)?

3. Continental scale fluxes are very coherent, spring 1998, and linked to [CO2]! (Butler et al, in prep) An extreme climatic event.

ChEAS Regional Flux Experiment Domain

= LI-820 sampling from 75m above ground oncommunication towers.

= 40m Sylvania flux towerwith high-quality standardgases.

= 447m WLEF tower. LI-820, CMDLin situ and flaskmeasurements.

ChEAS Regional Flux Experiment

• Derive daytime and daily seasonal fluxes using regional atmospheric inversions and relatively inexpensive in situ CO2 sensors.

• Overarching goal – evaluate/merge multiple approaches of studying terrestrial fluxes of CO2.– Merge flux-tower based upscaling with downscaled inversion

methodology. Regional integration and mechanistic interpretation.

– Determine interannual variations in seasonal fluxes on a regional basis. Again, integrate with regional flux measurements/mechanistic interpretations.

– If possible, derive net annual fluxes. Spatial resolution is limited by the magnitude of the annual signal.

Expected Regional Mixing Ratio Differences (Winter to Summer)

2 to 5 ppm

~400 km

(full ring)

~24 hours

1 to 2 km

1 to 4

gC m-2 d-1

Diurnal

~0.2 ppm1 to 5 ppmChange in ABL CO2

400 km

(full ring)

~180 km

(half ring)

Advection distance

~10 hoursAdvection time

~10 km1 to 2 kmMixing depth

~ 1

gC m-2 d-1

1 to 10

mol m-2 s-1

Flux magnitude

AnnualDaytimeTime scale

Preliminary Results: Late August 2003

Planned continental CO2 network:Selection of new sites based on optimization study, Skidmore et al,

and plans for a Midwest regional intensive

-125 -120 -115 -110 -105 -100 -95 -90 -85 -80 -75 -70 -65

-130 -125 -120 -115 -110 -105 -100 -95 -90 -85 -80 -75 -70 -65 -60

25

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VVV V

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ChEAS region

ARM-CARTregion

Poker Flats, AK(aircraft profile + flux tower)

VP

LegendExisting VTTProposed VTTTall towerProfiling aircraftCO2 mesonet

Spatial coherence of seasonal flux anomalies

A similar pattern isseen at several fluxtowers in N. Americaand Europe.

Three sites have high-quality [CO2] measurements + dataat Fluxnet (NOBS,HF, WLEF).

The spring 98 warm period and a later cloudy period appear at all 3 sites.