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AmeriFlux:Progress and emerging challenges
Beverly Law, Oregon State University, AmeriFlux Science Team Chair
AmeriFlux Science Steering GroupDennis Baldocchi, University of California, BerkeleyDavid Bowling, University of UtahJing Chen, University of TorontoKenneth Davis1, The Pennsylvania State UniversityDavid Hollinger, USDA Forest ServiceXuhui Lee, Yale UniversityHank Margolis, Laval UniversityWilliam Munger, Harvard UniversitySteven Running, University of MontanaHans Peter Schmid, Forschungszentrum KarlsruhePeter Thornton, National Center for Atmospheric ResearchShashi Verma, University of Nebraska1presenting
outline
• Overview of AmeriFlux• Status report• Recent research progress• Emerging challenge: improving climate
system modeling• What is needed to meet the challenge?
0. Overview of AmeriFlux
AmeriFlux Networkhttp://public.ornl.gov/ameriflux
• 93 active sites in 3 countries• 32 research teams• Companion Canadian network• Most major ecoregions in N. America covered
• Calibration lab runs comparisons across sites• Open-access, central data base enables global use of observations• Operational since 1996
Science objectives• Quantify exchange of carbon, water and energy
between terrestrial ecosystems and the atmosphere across a range of vegetation types, disturbance histories, and climatic conditions.
• Understand processes governing the terrestrial carbon cycle and linkages with the water, energy and nitrogen cycles.
• Produce a high-quality data base and synthesize observations across the network.
Core measurements• Fluxes of CO2, water vapor, and sensible heat
flux via eddy covariance.• Radiative fluxes and micrometeorological
conditions.• Biophysical characterization of sites (e.g.
vegetation age and type, nutrient status, carbon pool sizes, soil type).
• Membership requirements:– Address common science questions in strategic plan– Collect certain measurements year-round – Share data in standard format via common database – Participate at annual meetings– Participate in calibration and intercalibration activities– Participate in network-wide syntheses of results
• No support or funding comes with membership– e.g. for data management and submission requirements,
synthesis contributions
• Responsibilities of membership are not binding
Current AmeriFlux Structure:A Cooperative
• Structure is very inclusive– participation is broad– growth has been rapid (20 sites 10 years ago, now ~100, 350
worldwide)
• Funding structure encourages experimentation and innovation – Each funding cycle, each site must propose something “new”
or risk a poor review.
• Structure is ideal for learning how to build a network.• Structure is not ideal for maintaining a coherent, long-
term network.
Characteristics of theCooperative Structure
1. Status of AmeriFlux
AmeriFlux Productivity
0
100
200
300
400
500
600
1999 2001 2003 2005 2007
SitesReportingSite Years
Data Holdings• 548 site-years of
half-hourly data from 100 sites
• Flux measurements span 1991-2007
Publications• Investigators have
produced roughly 100 peer-reviewed publications/year for the past 5 years.
• Multi-site syntheses are increasingly common.
http://public.ornl.gov/ameriflux/viewstatus_Ameriflux.cfm
Following 3 figures courtesy of Tom Boden
AmeriFlux in a global context
• 74 AmeriFlux sites in Fluxnet dataset account for 305 site-years of data• More than 50 proposals for global synthesis papers received from site investigators. Global data not yet open-access
(AmeriFlux portion is open).• About 30% of submitted AmeriFlux site-years were rejected due to incomplete or insufficient quality data - network is
somewhat heterogeneous.
Number of sites contributing data to the La Thuile Fluxnet global synthesis data base
Length of Data Record and Sponsors for Active AmeriFlux Sites
0
2
4
6
8
10
12
14
16
18
1 2 3 4 5 6 7 8 9 10 10+
11 new sites began in 2007
Mean operating age – 5.7 yrs
10 sites operating over a decade but some of these have uncertain future funding
Number of years of operation for a given site
Nu
mb
er
of s
ites
• Major sponsors for active sites – DOE (39), None (17), USDA (15), NOAA (7), NSF(7), Universities (5), and NASA (3).• Non-centralized nature of AmeriFlux leads to instability in the network - potentially high turnover rate among sites.
Summary of status• An AmeriFlux network of decadal-scale flux measurements is emerging within a global coop of networks of "standardized" flux and biological measurements.
• Coherent network observations are central elements of many new synthesis studies. Research and publication is moving from site studies to network studies.
•There is increasing use of network data products by the carbon cycle and climate modeling communities.
• There is a recent decrease in the number of funded sites and the potential for a high turnover rate among sites.
• Some sites are providing insufficient data for synthesis activities.
• Network goals are compromised by funding sites individually.
2. Recent research highlights
- Process studies quantify and understand processes that influence ecosystem-atmosphere interactions
- Diagnoses of regional carbon budgetsconstruct large scale flux estimates
- Applications of flux network data to improving climate system modeling
Quantification of climate-ecosystem interactions: Clouds, aerosols and ecosystems
• AmeriFlux data quantifies the impact of clouds and aerosols on carbon sequestration and evapotranspiration at the land surface
• Flux observations showed aerosol and cloud effects on light quality and photosynthesis
• Importance of diffuse light effects now being incorporated in regional/global land surface models
• Similar process-oriented studies, using single or multiple sites, are ongoing and common across AmeriFlux sites.
Aspen forest, BOREAS southern study area
PPFD (mol m-2 s-1)
0 500 1000 1500 2000
Ne
t E
co
sys
tem
Ex
ch
an
ge
(
mo
l m-2
s-1
)
-40
-30
-20
-10
0
10
20
30
Cloudy daysClear days
Niyogi et al. 2004
Law et al. 2002 sink
Net
CO
2 F
lux
(m
ol m
-2 s
-1)
Diagnoses of regional carbon budgets:Regional clusters of flux towers
(Law et al. 2004, Turner et al. 2007)
(Desai et al., 2007; in press)
Several studies have now combined flux tower observations, satellite remote sensing, environmental conditions and terrestrial carbon cycle models to estimate regional fluxes.
Diagnosis of regional carbon budgets: MODIS-AmeriFlux synthesis
r = 0.855 ± 0.175
Heinsch et al., 2006
Figures courtesy of Steve Running
Improvement of a climate system model using flux network data: NCAR
CCSM/CLM example
AmeriFlux, Canadian and Amazon sites8 sites and 52 site-years of data
CarboEurope sites7 sites and 45 site-years of data
Temperate, tropical, sub-alpine, boreal and mediterranean sites
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
Community Land Model (CLM) versions
CLM3.0: original code (Oleson et al. 2004)
CLMgw: prognostic ground water scheme, more infiltration, sun-shade canopy etc.
CLMgw+rsoil: new bare soil evaporation resistance
CLM3.5: diagnostic nitrogen control on Vmax, photosynthesis and stomatal conductance
CLM3.0 vs. CLM3.5 yields large differences in regional hydrologic balances.
Courtesy Reto Stoeckli, Colorado State University
Assimilation of flux measurements into terrestrial carbon cycle models for model evaluation
Site-years analyzedWLEF: 1997-2004Harvard: 1992-2003Howland: 1996-2003UMBS: 1999-2003M. Monroe: 1999-2003
TRIFFID model (used in Cox et al., 2000)
Ricciuto et al., in prep
Environmental conditions at flux
tower site
Flux tower site vegetation, soil, and disturbance characteristics
Terrestrial carbon cycle model
Bayesian parameter estimation algorithm
Model prior parameter values
(and pdfs)Modeled fluxes at tower sites
1
2
Optimized terrestrial carbon
cycle model
3
Modeled fluxes at tower sites
Optimized model parameters (and pdfs)
Flux observations
(subset)
Biometric data. Soil moisture.
Leaf area.
Flux observations (independent
set)
4
Evaluation
Evaluation
Assimilation of flux measurements into terrestrial carbon cycle models
seasonal cycle
mean annual flux
Diurnal, synoptic and seasonal cycles, and mean annual fluxes can be reproduced well.
Interannual variability in mean annual fluxes is not simulated well.
Results broadly consistent with previous efforts (e.g. Braswell et al., 2005)
3. Emerging challenge: Evaluate and improve climate prediction/projection
using climate system models
Problem: Uncertainty in the interaction of the terrestrial carbon cycle and climate
• C4MIP: comparison of 10 coupled climate/carbon models.
• Large uncertainty (225 ppm range in cumulative atmospheric CO2) in terrestrial biosphere contribution to atmospheric CO2 through 2100.
Friedlingstein et al., 2006
IPCC WG1 AR4 Summary for Policy Makers
Page 14: “Models used to date do not include uncertainties in climate-carbon cycle feedback nor do they include the full effects of changes in ice sheet flow, because a basis in published literature is lacking.”
Page 17: “Climate carbon cycle coupling is expected to add carbon dioxide to the atmosphere as the climate system warms, but the magnitude of this feedback is uncertain. This increases the uncertainty in the trajectory of carbon dioxide emissions required to achieve a particular stabilisation level of atmospheric carbon dioxide concentration.”
3rd IPCC report
AmeriFlux network record: a fundamental climate system observation
AmeriFlux network record: a fundamental climate system observation
Causal chain: CO2 fluxesCO2 mixing ratioSurface temperature
Note: A single flux measurement does not capture a global value
Challenge: Improve predictive skill in coupled climate-carbon
cycle modeling
• AmeriFlux role: Provide a CO2 flux network data product that can be used as the instrumental temperature record has been used.
Future: Poorly maintained network
hindcast forecast
Future: Well maintained network
Current
present
Observational constraints
Potential coupled climate-carbon cycle model evaluation
Terrestrial uptake of carbon (GtC yr-1)
Time
0
10
5
-5
Possible carbon cycle forecasts
Objectives:• To provide feedback to the science community on the
performance of terrestrial biogeochemistry models coupled to CLM within CCSM3
• To provide a new observation-based diagnostics package for terrestrial carbon cycling in coupled carbon-climate models
• To define, conceptually, how biogeochemistry should be evaluated in climate models
The NCAR Community Climate Systems Model (CCSM) Carbon and Land Model
intercomparison Project (C-LAMP)
Forrest Hoffman, Peter Thornton, Yen-Huei Lee, Nan Rosenbloom, Jim Randerson, Inez Fung and Steve Running
C-LAMP Model SimulationsRun Description Time period
Forcing with observed climate (Dai et al.)
1.1 Spin-up ~4000 years
1.2 Control 1798-2005
1.3 Varying climate 1948-2005
1.4 Varying climate, CO2, and N
deposition
1798-2005
1.5 Varying climate, CO2, N deposition,
and land use change
1798-2005
Land-atmosphere coupled
2.1 Spin-up ~1000 years
2.2 Control 1800-2005
2.3 Varying climate (Hadley SSTs) 1800-2005
2.4 Varying climate, CO2, and N
deposition
1800-2005
2.5 Varying climate, CO2, N deposition,
and land use change
1800-2005
C-LAMPevaluation
metrics utilize:
flux network data,
ecological inventories,
remote sensing,
atmospheric CO2,
ecosystem experiments
Table 2. Biogeochemical Model Evaluation Datasets:
Metric Metric components Sub-Score
Total Score
Status
NPP Matching EMDI Net Primary Production (NPP) observations 5 20 Complete EMDI comparison, normalized by PPT 5 Complete Correlation with MODIS (r2) 5 Complete Latitudinal profile (r2) 5 Complete
LAI Matching MODIS observations - Phase (derived separately for major biome classes) 5 20 Complete - Mean (derived separately for major biome classes) 5 Complete - Maximum (derived separately for major biome classes) 5 Complete - Growing season length (derived separately for major biome
classes) 5 Complete
CO2 Seasonal
Cycle Matching the phase and amplitude at NOAA GMD Globalview observation stations
20 Complete
Carbon Stocks Aboveground vegetation within the Amazon Basin from Saatchi
et al. (2006) 5 10 Complete
Global belowground carbon (top 30 cm) from Batjes (2005). 5 In progress
Energy & CO2 Matching eddy covariance observations from FLUXNET fluxes - Net radiation (monthly means) 5 20 In progress
- Latent heat (monthly means) 5 In progress - Sensible heat (monthly means) 5 In progress - CO2 fluxes (monthly means) 5 In progress
Transient dynamics
Beta factor for CO2 fertilization – Norby mean 10 Complete
Rate constants for litter decomposition (LiDAT from Parton) and litter mass from Holland and Post.
Not ready
El Nino anomaly 1998 (NEE and fire components) – TRANSCOM, CarbonTracker, and Van der Werf et al. fires
In progress
dNPP/dT, dNPP/PPT Not ready Total: 100
Role of AmeriFlux within the North American Carbon Program
Tower flux
Ecological inventory
Atmospheric inventory
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
Cha
mbe
r flu
x/pl
ot d
ata
Remote sensing and terrestrial models
Diagnose, attribute, predict.
4. What is needed to meet this challenge?
Observational constraints
Terrestrial uptake of carbon (GtC yr-1)
Time
0
10
5
-5
hindcast forecast
present
Possible carbon cycle forecasts
CurrentFuture: Well maintained network
Vision
1. Sustain and enhance a core set of long-term, high-quality flux measurement sites.
2. Continue mechanistic research to improve model structure and identify important climate-ecosystem interactions
3. Conduct network design studies– How many sites are needed? – What mix of shorter vs. longer term sites is optimal?– How long are the required time series?– What complementary data are needed at each site?
4. Sustain and enhance an easily-accessed, homogeneous, data base
Needs
Summary of status• An AmeriFlux network of decadal-scale flux measurements is emerging within a global coop of networks of "standardized" flux and biological measurements.
• Coherent network observations are central elements of many new synthesis studies. Research and publication is moving from site studies to network studies.
•There is increasing use of network data products by the carbon cycle and climate modeling communities.
• There is a recent decrease in the number of funded sites and the potential for a high turnover rate among sites.
• Some sites are providing insufficient data for synthesis activities.
• Network goals are compromised by funding sites individually.
RecommendationsThe AmeriFlux science steering group recommends
sustaining and enhancing a core network of long-term, high-quality flux measurement sites to address the increasing need for syntheses of multi-site, long-term data records.
A coherent network of sites has added value that exceeds a collection of individual, short-term studies. A mechanism should be developed to recognize this added value when
questions of funding arise.
A stable core network will provide a critical contribution to our ability to predict future climate by enabling the
development and evaluation of coupled carbon-climate models and earth systems analysis models.
Additional materials in case of questions.Delete when posting talk online.
Relationship between AmeriFlux and NEON: Complementary, intersecting efforts
AmeriFlux NEON
Scientific endeavor including infrastructure, human resources (PIs and their collective expertise), and well-established international ties
Infrastructure project
Wild and managed lands Wildlands focus
More than a decade of data and data management
Not yet funded
Committed to DOE/CCSP and NACP objectives
Broad ecological research agenda
Role of AmeriFlux within the North American Carbon Program
Flux tower upscaling
Atmospheric inventory
Ecological inventory
Strengths Potent source of mechanistic understanding. Excellent temporal precision and resolution.
Absolute net carbon balance at global scales.
Absolute above ground carbon balance at plot scales.
Weaknesses Difficult to cover large areas. Potential systematic errors.
Poor spatial resolution.
Difficult to determine mechanisms.
Difficult to cover large areas.
Poor temporal resolution.
Topics that can be addressed with integration of AmeriFlux data and models
• Where and when will forests be vulnerable to fires, and how do changes in forest processes affect climate?
• How would biofuel harvesting impact forest functioning and C sequestration?
• How will changes in water availability and population impact water availability to crops and forested watersheds that serve urban areas?
• What are potential interactions between future climate scenarios, and carbon, water, and nitrogen cycling?
Observed interannual variability: Only local processes? Probably not.
Gap-filled fluxes from the 6 midwestern flux tower sites.
Interannual variability of similar plant functional types appears to be coherent.
Similar processes, linked to climate, influencing sites as far as several hundred kilometers apart in a similar way?
LC = wetland; WC, MMSF, UMBS = mature hardwood; Syl = mixed old growth; WLEF = mixed
Contributions of AmeriFlux Research to DOE Climate Change Science Program Elements
• Climate forcing – carbon cycle, atmospheric water vapor
• Climate change prediction• Responses of ecosystems to climate change• Climate mitigation