Scaling up of Carbon Exchange Dynamics from AmeriFlux Sites to a Super-Region in the Eastern United States Page: 4 of 31
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2 Rationale: Broad Outline of Activities
Our primary activity will be to develop and apply a new strategy for estimating large-scale
terrestrial biotic carbon dynamics based on a bottom-up approach that integrates eddy-covariance
flux measurements, ecosystem-scale modeling, and a mesoscale meteorological model.
Robustness in our scaling and aggregation strategy is achieved by cross-links to independent
observations and model products at various scales and sites. These links offer opportunities for
direct comparisons to alternative approaches and impose constraints on aggregation errors.
The proposed bottom-up carbon exchange scaling strategy
We propose a new strategy to scale up carbon exchange from observations at specific sites to a
large region by combining four general classes of information (Figure 1):
1. Flux observations. We will integrate eddy-flux observations of CO2 exchange from over 40
active AmeriFlux sites into our scaling strategy by applying flux footprint-based selection
criteria.
2. Numerical models. We will use several different numerical models to provide both the
functional link between flux observations and their biophysical drivers, and the spatial link
between the observational nodes of the AmeriFlux network.
3. Meteorological Re-analysis Data. To provide spatial coverage of meteorological drivers for
the ecosystem exchange models, reanalysis data will be used.
4. Satellite data products and surface databases at nested resolutions and coverage domains.
Surface databases and satellite derived ecosystem indices form the spatial context in which
our numerical models will operate.
These sources of information are linked in a scaling strategy involving five principal stages
(Figure 1). The steps leading from one stage to the next are governed by the following
overarching considerations:
A. In-situ flux observations are in general spatially and/or temporally limited. Therefore, to
achieve valid regional exchange rates, models must be used to interpolate and extrapolate the
temporal and spatial domain covered by these observations.
B. Observations and model results can only be linked if they represent the same ecosystem type
and time period. Because all ecosystems are spatially heterogeneous at some range of scales,
this requirement may be a problem, but can be satisfied by selecting observations that are
representative of the type of ecosystem identified in the model (Schmid, 1997). The spatial
representativeness of flux observations in inhomogeneous ecosystems can be tested using a
flux footprint methodology, which is the time-varying "field-of-view" of an eddy-flux sensor.
C. Comparisons of observations and independent models at various scales can form plausibility
constraints on modeling results and aggregation errors. Such comparisons also serve to test
and develop our understanding of the mechanistic functioning of ecosystem exchange and its
biophysical drivers. Spatial data (such as satellite derived variables, topography, inventories,
or soil information) are needed as boundary conditions for numerical models. They are
essential in linking observations and models at small scales to models of ecosystem exchange
at large scales.Scaling up of Carbon Exchange Page 3
Technical Report
Scaling up of Carbon Exchange
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Schmid, Hans Peter & Wayson, Craig. Scaling up of Carbon Exchange Dynamics from AmeriFlux Sites to a Super-Region in the Eastern United States, report, May 5, 2009; United States. (https://digital.library.unt.edu/ark:/67531/metadc932770/m1/4/: accessed April 23, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.