# Presentation: 657119

## AmeriFlux:Progress and emerging challenges

- Beverly Law, Oregon State University, *AmeriFlux Science Team Chair*
*AmeriFlux Science Steering Group*
- Dennis Baldocchi, University of California, Berkeley
- David Bowling, University of Utah
- Jing Chen, University of Toronto
- Kenneth Davis1, The Pennsylvania State University
- David Hollinger, USDA Forest Service
- Xuhui Lee, Yale University
- Hank Margolis, Laval University
- William Munger, Harvard University
- Steven Running, University of Montana
- Hans Peter Schmid, Forschungszentrum Karlsruhe
- Peter Thornton, National Center for Atmospheric Research
- Shashi Verma, University of Nebraska
*1**presenting*

## outline

- Overview of AmeriFlux
- Status report
- Recent research progress
- Emerging challenge: improving climate system modeling
- What is needed to meet the challenge?

**Notes:**
Ending - more forceful ending statement.

## 0. Overview of AmeriFlux

**Notes:**
Need to condense the next 9-10 slides into a 1-2 slide summary.

## AmeriFlux Networkhttp://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

- 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.

- 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

- 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://](http://public.ornl.gov/ameriflux/viewstatus_Ameriflux.cfm)__[public.ornl.gov/ameriflux/viewstatus_Ameriflux.cfm](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

**Notes:**
Decline in supported sites is overlapping with the value of the data as a global database.  This is a concern.  Spectacular growth of interest in data.  Decline - lateness in reporting and lack of support.  Poor for synthesis.

La Thuille dataset
~30% of AmeriFlux site-years didn’t make it into Fluxnet synthesis set: Some of AmeriFlux sites didn’t submit 2006, some sites discontinued. Dario can’t process sites without storage term in forested sites
Concern over loss of observation base

## Length of Data Record and Sponsors for Active AmeriFlux Sites

- 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

- Number of sites

-  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.

**Notes:**
New Sites – Marcy Litvak (6), Tilden Meyers – urban/SD, 2 everglades, Russ Scott –southern Az., Tim Griffis – KCMP

10+ Sites – Sky Oaks (old & young), Barrow, Niwot Ridge, Mize, Bondville, Harvard, Howland, Duke (loblolly), WLEF/Park Falls

## 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 budgets
- construct 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.

- Niyogi et al. 2004

- Law et al. 2002

- sink

- Net CO2 Flux (mol m-2 s-1)

**Notes:**
Aided by records of direct and diffuse sunlight and of temperature changes, Gu et al. (2003) demonstrated an increase in canopy photosynthesis on cloud-free days during summer, caused by the increase in diffuse light, and separate these changes in photosynthesis from changes in respiration.
Volcanoes and pollution reduce surface light and temperature directly, and GHG emissions increase temperature and possibly reduce light. The key feature is that volcanoes, pollution, and GHG may all increase diffuse light.
Detection of change would not have been possible without long-term records
Although the importance of diffuse light has long been recognized in the agricultural community, its effects have yet to be incorporated in large-scale terrestrial production models

## 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

- 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 _
- _sites_
- 8 sites and 52 site-years of data
- _CarboEurope sites_
- 7 sites and 45 site-years of data
- Temperate, tropical, sub-alpine,
- boreal and mediterranean sites

- _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

**Notes:**
Note that the water budget of regions in CLM3.5 was much different than that with CLM3.0.

## Assimilation of flux measurements into terrestrial carbon cycle models for model evaluation

- Site-years analyzed
- WLEF:         1997-2004
- Harvard:      1992-2003
- Howland:     1996-2003
- UMBS:         1999-2003
- M. Monroe:  1999-2003

- TRIFFID model
- (used in Cox et al., 2000)
- Ricciuto et al., in prep

*Modeled fluxes at tower sites*

**1**

**2**

**3**

* **Modeled fluxes at tower sites*

*Optimized model parameters (and pdfs)*

**4**

*Evaluation*

*Evaluation*

## Assimilation of flux measurements into terrestrial carbon cycle models

- 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

*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

**Notes:**
Note:  changing model structure (add N cycling) and get yet a different answer - Thornton.

## 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 

- 3rd IPCC
- report

## AmeriFlux network record: a fundamental climate system observation

**Notes:**
Figure presents a mechanistic sequence from CO2 flux to CO2 in air to global T.

Points:  
Climate-scale time series are being produced by the flux towers.
Need multiple sites to construct regional to global response (see flux upscaling - region carbon budgets, remote sensing evaluation)
Need longer flux time series to effectively merge with other climate system data

CCSP program elements:
Climate prediction
Climate forcing
Ecosystem responses to climate change
(Climate mitigation is emerging - as predictive skill develops, this suggests guidance regarding mitigation.)

Time series of terrestrial CO2 fluxes from Hforest and 1-3 other long-running sites that differ from H Forest (10-15 years)
Time series of global CO2 (50 years)
Time series of the instrumental T record (100+ years)

## AmeriFlux network record: a fundamental climate system observation

- Causal chain:
- CO2 fluxes
- CO2 mixing ratio
- Surface temperature
- Note:  A single flux measurement does not capture a global value

**Notes:**
Figure presents a mechanistic sequence from CO2 flux to CO2 in air to global T.

Points:  
Climate-scale time series are being produced by the flux towers.
Need multiple sites to construct regional to global response (see flux upscaling - region carbon budgets, remote sensing evaluation)
Need longer flux time series to effectively merge with other climate system data

CCSP program elements:
Climate prediction
Climate forcing
Ecosystem responses to climate change
(Climate mitigation is emerging - as predictive skill develops, this suggests guidance regarding mitigation.)

Time series of terrestrial CO2 fluxes from Hforest and 1-3 other long-running sites that differ from H Forest (10-15 years)
Time series of global CO2 (50 years)
Time series of the instrumental T record (100+ years)

## 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.

**Notes:**
Show IPCC-cited hindcasting of global T (natural, anthropogenic forcing) as an analogy
Show desired analogous result - hindcasting of tower flux records to establish coupled carbon-climate model predictive skill - imagined goal, not results we have to date - fabricate.
Include different processes changing hindcast
Show how a poorly designed or fragmented flux measurement network may yield inability to distinguish model structures/parameters
Show prediction as well, and possible link to ecosystem experiments that simulate future climate and atmospheric conditions.

## Potential coupled climate-carbon cycle model evaluation

**Notes:**
Coupled models would be jointly constrained by atmospheric co2 and instrumental T records.

## 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

- 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 Simulations

| Run | 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-LAMPevaluation metrics utilize:flux network data, ecological inventories, remote sensing, atmospheric CO2, ecosystem experiments

## Role of AmeriFlux within the North American Carbon Program

- Diagnose, attribute, predict.

**Notes:**
Tower flux mechanisms are especially valuable when trying to attribute cause of observed fluxes, since the spatial scale that they measure can be characterized in sufficient detail to identify causes of changes in fluxes over time.

## 4. What is needed to meet this challenge?  

## Vision

**Notes:**
Sustain and enhance a core set of long-term, high-quality flux measurement sites.
Continue mechanistic research to improve model structure and focus on essential mechanisms
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?
An easily-accessed, homogeneous, well-maintained data base

## Sustain and enhance a core set of long-term, high-quality flux measurement sites.
Continue mechanistic research to improve model structure and identify important climate-ecosystem interactions
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?
Sustain and enhance an easily-accessed, homogeneous, data base

- Continue mechanistic research to improve model structure and identify important climate-ecosystem interactions
- 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?
- 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.*

## Recommendations

*The 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.*

## Slide 38

## 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

**Notes:**
Apparent coherence across the upper Midwest of interannual variability of upland forest cumulative annual carbon fluxes.  Note that the wetland site (LC) and partly wetland site (WLEF) do not appear to show as much interannual variability.

LC, WC, Syl and WLEF are all ChEAS towers.  UMBS is Michigan Biological Station.  MMSF is Indiana, Monroe-Morgan.

2002 WLEF data acquisition failed - no data available.  2004 data from UMBS and MMSF were not yet available.

Causes of variability, temporal details, have not yet been determined.

## 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