B22A-01 INVITED 10:20h
The Role of Terrestrial Ecosystem Processes in Determining Patterns of Terrestrial Carbon Fluxes and Atmospheric CO$_2$ Concentrations: Results From a Regional-Scale Coupled Atmosphere-Ecosystem Model
Inverse studies of the carbon cycle have traditionally relied on low-frequency flask measurements collected at remote stations specifically located to eliminate variance in CO$_2$ concentrations arising from terrestrial processes. The insensitivity of these observations to terrestrial CO$_2$ fluxes makes it difficult to infer regional terrestrial carbon fluxes or to attribute large-scale fluxes to particular causes such as climate variability, land-use change or CO$_2$ fertilization. We are addressing this issue by developing a constrained implementation of Regional Atmospheric Modeling System-Ecosystem Demography Model Version 2 (RAMS- ED2) for the New England region. RAMS-ED2 is a new, coupled atmosphere-ecosystem model that naturally scales between the fast timescale responses of individual plants to the atmosphere and the long-term, regional-scale dynamics of heterogeneous ecosystems subject to land-use change and forest harvesting. The model is designed to predict carbon fluxes on spatial scales from hectares to thousands of square kilometers that are consistent with fast timescale flux-tower measurements of CO$_2$ fluxes, seasonal measurements of canopy phenology from remote sensing data and decadal scale forest inventory measurements and land-use history forcing. The ecosystem state variables and environmental response functions of the optimized model provide a comprehensive description of short and long term factors regulating fluxes in the regional carbon cycle. The optimized model will provide a unique tool for quantifying the contributions of environmental forcing, ecosystem recovery from land-use change, forest harvesting and CO$_2$ fertilization to current and future patterns of terrestrial carbon fluxes and resulting patterns of atmospheric CO$_2$ concentrations in North America.
B22A-02 10:40h
Diagnosis of the North American Carbon Cycle Using Data and Models
Estimation of spatial and temporal variations of carbon sources and sinks with their associated uncertainties has previously been limited by the representativeness of local measurements and by the sparsity of atmospheric data. Anticipating much denser coverage of both in-situ and remotely sensed carbon data later in this decade, it will be feasible to obtain much more detailed and credible information about sources and sinks. Previous experience with global inverse modeling from atmospheric trace gas observations indicates that one of the most difficult challenges regional efforts will face is the quantitative specification of temporal and spatial patterns in CO$_{2}$ exchanges and their covariance structure. This will be particularly important over the continents where the variance in atmospheric observations is dominated by diurnal, synoptic, and seasonal changes and spatial heterogeneity of sources and sinks is severe. We are developing a method for estimation of carbon sources, sinks, and uncertainties across North America at high spatial resolution by combining satellite imagery, in-situ sampling of the atmosphere, and deterministic models of weather, transport, and emissions in an optimization system. The method relies on temporal decomposition of sources and sinks processes into "fast" ecophysiology driven primarily by radiation, temperature, and moisture, and "slow" variations that control the time-mean distribution. Mesoscale weather, fast carbon cycling (photosynthesis, biological carbon allocation, and biogeochemical transformations), and atmospheric transport will be simulated using a coupled regional modeling system. Time-mean sources and sinks resulting from slow processes will then be inferred from atmospheric CO$_{2}$ observations, and will be constrained using detailed emissions estimates and fire data. Lateral boundary conditions for atmospheric CO$_{2}$ and weather and their uncertainties will be prescribed from a global model. Selected model parameters and state variables will be optimized using an Ensemble Kalman Filter method that includes formal estimation of model error. Preliminary evaluation suggests that the lateral boundary problem is tractable, and that anticipated atmospheric observing systems will provide strong constraint on twice-monthly fluxes at regional resolution.
http://biocycle.atmos.colostate.edu
B22A-03 10:55h
Regional CO$_2$ Flux Estimates for North America from Atmospheric Transport Inversions
We combine the global atmospheric transport model TM5 with observations from the NOAA-CMDL cooperative air sampling network to estimate CO$_2$ fluxes from North America on an 80$\times$80 km grid. We produce weekly, global CO$_2$ flux maps that are optimally consistent with CO$_2$ observations at more than 70 sites worldwide by adjusting surface fluxes in a Bayesian inversion framework. This includes many new aircraft profiles over the United States associated with the North American Carbon Program. The two-way nesting capability of TM5 allows us to study the North American carbon flux on a fine scale while constraints from remote observations are provided by a coarser (600$\times$400 km) grid within the TM5 model. Further constraints on the North American CO$_2$ flux are introduced into our inversion as spatial and temporal correlations between regions with similar land cover. Continuous CO$_2$ measurements from tall towers in the US provide an independent check on the estimated regional CO$_2$ fluxes. We will present our North American flux estimates, their uncertainty, and their agreement with independent information focussing on the period 2000-2004.
B22A-04 11:10h
Coupling Bottom-Up and Top-Down Approaches to Understanding the Carbon Cycle: An Analysis of Data from the NOAA/CMDL WLEF-TV Tall Tower Monitoring Site in Northern Wisconsin
The NOAA/CMDL monitoring site at the WLEF-TV tower in Park Falls, WI frequently samples air that has been advected over the upper Midwest. Here, continuous measurements of CO$_{2}$ at WLEF from the year 2000 are analyzed using an atmospheric transport model, the Stochastic Time-Inverted Lagrangian Transport (STILT) model, and the Simple Biosphere (SiB) model of ecosystem CO$_{2}$ fluxes. Together, these models can produce a time series of modeled CO$_{2}$ mixing ratios at the WLEF tower. Differences between modeled and observed CO$_{2}$ time series indicate model deficiencies. Atmospheric transport errors could result e.g., from inadequate representation of convection or lack of mass-conservation of the meteorological fields used to drive the model. Potential errors in the representation of transport will be assessed using sensitivity studies and by comparing sampling footprints from the STILT model with footprints from two other models: the adjoint version of the Transport Model 5 (TM5), and the Lagrangian Particle Dispersion (LPD) model. Errors in predicted CO$_{2}$ fluxes could arise from factors such as inaccurate specification of vegetation types, insufficiently detailed parameterizations of photosynthesis and respiration, or errors in the meteorological fields used to drive SiB. For this study, we will examine the sensitivity of the predicted fluxes to C3 versus C4 vegetation types. The impact of fossil fuel sources on CO$_{2}$ mixing ratios at WLEF will also be considered.
B22A-05 11:25h
Relationship between Total Chlorophyll Content and CO2 Fluxes in Crops: Implications for the Remote Estimation of Net Ecosystem Carbon Dioxide Exchange
The ratio of leaf surface area to ground surface area, called leaf area index (LAI), is a measure of carbon and water balance in plants, because it describes the potential surface area available for leaf gas exchange. LAI can be separated into its photosynthetic and non-photosynthetic components. Total chlorophyll content in the canopy, expressed as the product of green LAI (portion of LAI composed of green leaf area) and leaf chlorophyll (Chl) content, is a quantitative measure of the photosynthetically functional component. Total Chl content is directly expressive of the photosynthetic apparatus of the vegetation, and it may relate to the photosynthetic potential of a vegetation stand. The goal of this study was to investigate whether total chlorophyll content in crops can be used as a proxy of the net ecosystem CO2 exchange (NEE) that a vegetation stand could reach under optimal radiation conditions. We studied the relationship between total Chl content and mid-day NEE of maize and soybean grown in irrigated and rainfed fields. Total Chl content and NEE relate very closely (r2=0.85) for both species. This close relationship between total Chl and NEE allowed the use of a technique, recently developed for the remote estimation of total Chl, to assess NEE. The technique uses two spectral bands: near infra-red and either green (around 550 nm) or red-edge (near 700 nm). The technique was able to predict 5-day maximum value mid-day NEE composite, ranging from 0 to 2.5 mgC/m2s, with an overall root mean square error (RMSE) of less than 0.33 mgC/m2s.
B22A-06 11:40h
Diagnosing Model Errors in Canopy-Atmosphere Exchange Using Empirical Orthogonal Functions
Multi-layer canopy process models (MLCPMs) have been established as tools for estimating local-scale canopy-atmosphere scalar (carbon dioxide, heat and water vapor) exchange as well as testing hypotheses regarding the mechanistic functioning of complex vegetated land surfaces and the interactions between vegetation and the local microenvironment. These model frameworks are composed of a coupled set of component submodels relating radiation attenuation and absorption, photosynthesis, turbulent mixing, stomatal conductance, surface energy balance and soil and subsurface processes. Submodel formulations have been validated for a variety of ecosystems under varying environmental conditions. However, each submodel component requires parameter values that are known to vary seasonally as canopy structure changes, and over shorter periods characterized by shifts in the environmental regime. The temporal dependence of submodel parameters limits application of MLCPMs to short-term integrations for which a specific parameterization can be trusted. We present a novel application of empirical orthogonal function (EOF) analysis to the identification of the primary source of MLCPM error. Carbon dioxide (CO2) concentration profiles, a commonly collected and underutilized data source, are the observed quantity in this analysis. The technique relies on an ensemble of model runs transformed to EOF space to determine the characteristic patterns of model error associated with specific submodel parameters. These patterns provide a basis onto which error residual (modeled - measured) CO2 concentration profiles can be projected to identify the primary source of model error. Synthetic tests and application to field data collected at Duke Forest (North Carolina, USA) are presented.
B22A-07 11:55h
Pilot Study on Reconciling Supply and Demand: Who are the Consumers of Information on the North American Carbon Balance?
A major stated goal of the North American Carbon Program (NACP) is to advance scientific understanding of the carbon balance of North America. The scientific reasoning behind this focus has been articulated previously (NACP 2002), and includes the need to resolve differences in the magnitude of carbon exchange over the region estimated by independent methods. In addition to these scientific reasons for focusing on the carbon balance of North America, the NACP has also stated that these results will support management of the carbon cycle by providing information of use to society and policy makers (North American Carbon Program Plan 2002, Strategic Plan for the U.S. Climate Change Science Program 2003). Given the ever-increasing interest in carbon sequestration and carbon management in business, government, technical and policy sectors, this is a natural assumption to make; but the hypothesis has not yet been tested. It is a research question, therefore, to understand precisely what needs exist, and how information on the North American carbon balance will meet them. This study will summarize briefly what is meant by the North American carbon balance, examine the issue of scale and measurement compatibility, provide a first look at the categories of potential users of such information, and outline a strategy for an in depth study of targeted sectors. This research builds on the concept of "Supply and Demand," borrowed from the classic economic concept of markets being driven by supply and demand for goods. The concept is applied to the use of information in order to identify where there is a good match of information needs and supply, and where there is a "missed opportunity," or a chance to perhaps better connect the supply of scientific information to societal need. Research on the use of information in climate prediction and water management areas suggests that such a systematic approach is necessary to realize the potential usefulness of research, avoid misuse or nonuse, and, indeed, meet the broader goals of the NACP to contribute useful information to decision makers.
http://sciencepolicy.colorado.edu/carboncycle/