a challenge to the flux-tower upscaling hypothesis? a multi-tower comparison from the chequamegon...
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A challenge to the flux-tower upscaling hypothesis? A multi-tower comparison from the Chequamegon
Ecosystem-Atmosphere StudyK.J. Davis1, D.R. Ricciuto1, B.D. Cook2, M.P. Butler1, A.R.
Desai1, W. Wang1, C. Yi3, P.S. Bakwin4, P.V. Bolstad2, J. Martin2, E. Carey2, D.S. Mackay5, B.E. Ewers6, J.
Chen7, A. Noormets7, F.A. Heinsch8, A.S. Denning9, R. Teclaw10
1Penn State, 2U.Minnesota, 3U.Colorado, 4NOAA-CMDL, 5U.Buffalo, 6U.Wyoming, 7U.Toledo, 8U.Montana, 9Colorado State, 10USDA
Forest Service
With support from:DoE Terrestrial Carbon Processes Program,
DoE National Institutes for Global Environmental Change, NOAA, NSF Division of Environmental Biology
Motivation
What is and what governs ecosystem-atmosphere exchange of CO2 on spatial
scales of geopolitical and bioclimatological relevance?
Outline
• What is the “flux tower upscaling hypothesis?”
• Method: How do we test this hypothesis?
• Results: Flux magnitudes and flux variability.
• Simultaneous up-scaling and down-scaling.
Flux tower upscaling hypothesis
Fluxes of CO2 (NEE, R, GEP) = f (climate variables, ecosystem characteristics)
Climate and ecosystem variables can be mapped, functions determined, fluxes interpolated and integrated across space.
NEE = net ecosystem-atmosphere exchange, R = ecosystem respiration, GEP = gross ecosystem productivity, NEP = net ecosystem productivity
NEE = R – GEP = - NEP
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
Plots at towers Within stand: biometric data,chamber fluxes
Tower sites Stand: Eddy covariance flux towers representing key biomes and climate regions
Continent: Map biomes and climate, model fluxes
Upper Midwest,N. America
Flux tower upscaling hypothesis with simultaneous constraints
Within stand: biometric data,chamber fluxes
Stand: Eddy covariance flux towers
Forest: Clusters of flux towersWLEF tower
Continent: Map biomes and climate, model fluxes
Region: Map ecosystem variables, model fluxes
N. Wisconsin [CO2]
N. American [CO2]
Chequamegon Ecosystem-Atmosphere Study (ChEAS) region
Testing the upscaling hypothesis
Flux:R, NEE, GEP
Climate variables (x, y)
ChEAS
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?
Pho
to c
redi
t:
UN
D C
itatio
n cr
ew,
CO
BR
A
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
Forest-scale evaluation of the upscalinghypothesis: WLEF flux tower
ChEAS vegetation
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
ChEAS upscaling test results1. Climate alone does not explain
ChEAS CO2 fluxes.
2. The WLEF region is a source of CO2 to the atmosphere.
• drying wetlands?• disturbance/management?
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?
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
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?
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?• Chamber R >> W Creek R implies error?
5. Sylvania (old growth) fluxes differ from Willow Creek (mature) fluxes as expected due to stand age (similar GEP, old R > mature R).
• But soil respiration from chambers contradicts this result.
Sylvania – Willow Creek flux tower comparison
GEP, old growth (red) vs. mature (blue) forest
R, old growth (red) vs. mature (blue)
Summary
• Simple tower upscaling hypothesis, WLEF = a*W Creek + b*L Creek, fails.
• Means of reconciliation is not clear.
• Upscaling the magnitude of R, GEP, NEE is challenging.
Motivation II
What is and what governs the interannual variability in ecosystem-atmosphere exchange of CO2 on spatial scales of
geopolitical and bioclimatological relevance?
Interannualvariabilityin the rate ofaccumulationof atmosphericCO2
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(?)
Testing the interannual variability upscaling hypothesis
Flux tower clusters deployed for multiple years test the hypothesis that various
forest stands respond similarly to climate variability.
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, this session) An extreme climatic event.
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
Flux tower upscaling hypothesis with simultaneous constraints
Within stand: biometric data,chamber fluxes
Stand: Eddy covariance flux towers
Forest: Clusters of flux towersWLEF tower
Continent: Map biomes and climate, model fluxes
Region: Map ecosystem variables, model fluxes
N. Wisconsin [CO2]
N. American [CO2]
ChEAS regional flux experiment domain
= LI-820 sampling from 75m above ground on a communications tower.
= 40m Sylvania flux towerwith high-quality standardgases.
= 447m WLEF tower. LI-820, CMDLin situ and flaskmeasurements.
Potential VTT network:Selection of new sites to be based on optimization study, Skidmore et al, and plans for a Midwest regional intensive
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-130 -125 -120 -115 -110 -105 -100 -95 -90 -85 -80 -75 -70 -65 -60
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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
Complementary nature of inversion downscaling and flux tower upscalingInversion 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
Conclusions
• It is relatively difficult to upscale stand level fluxes to a region.
• Upscaling interannual variability may be more tractable than absolute flux magnitudes.
• Clustered flux towers provide upscaling methods testbeds.
• Flux tower up-scaling and inversion down-scaling are very complementary.
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