Investigating Land-Atmosphere CO2 Exchange with a Coupled Biosphere-Atmosphere Model: SiB3-RAMS

K.D. Corbin, A.S. Denning, I. Baker, N. Parazoo, A. Schuh, L. LuDepartment of Atmospheric Science, Colorado State University, Fort Collins, CO 80523-1371

AcknowledgementsResearch funded by NASA Earth System Science Fellowship

53-1970.

MotivationUsing atmospheric tracer transport models, inverse modelers can estimate

the strengths and spatial distribution of carbon sources and sinks; however, the fossil fuel CO2 emissions must be accurately estimated so that the

biospheric and oceanic fluxes can be isolated and quantified. The most current fossil fuel CO2 emissions estimates are based on country level

production data allocated to a 1o by 1o map using political units and human population density [Andres et al., 1996]. To improve the current estimates, high-resolution fossil fuel emissions estimates (36 km spatial resolution at

timescales of one hour) are being produced by incorporating CO2 emissions factors into a process-based, data-driven air quality emissions model for the United States [Kevin Gurney, personal communication]. The goal of this

research is to evaluate the high-resolution fossil fuel emission estimates and to analyze the impacts of various spatial and temporal resolutions of fossil

fuel emissions on the CO2 concentration using a coupled biosphere-atmosphere model.

New Model Features

The Model: SiB3-RAMS

The Model: SiB3-RAMS

Preliminary Model Evaluation

• Updated model to SiB version 3 and introduced new features• Further testing and model refinement required• Implement CO concentrations in SiB3-RAMS - Source from fossil fuel combustion - Monthly-mean OH map for conversion to CO2

Conclusions and Future Work

August 10-18, 2004Meteorology compared to WLEF tall towerobservations in Wisconsin Fluxes compared to WLEF

CO2 concentrations at WLEF tower

July 15-18, 2004WLEFSGP

Satellite Driver Data

Initial Soil Moisture and Respiration Factors

CO2Initial Conditions:

Lateral Boundary Conditions:

Initial CO2 concentration at 30 m for July 15, 2004.

• Initialized CO2 concentrations from the Parameterized Chemical Transport Model (PCTM) - 1o x 1.25o spatial resolution - 20 vertical levels

• Lateral boundaries of SiB3-RAMS simulations nudged to PCTM CO2 concentrations - 3 hourly time-step - Interpolated spatially and vertically

• Initial soil moisture field created for each individual grid cell using offline SiB3

• Autotrophic and heterotrophic respiration factors created for each individual grid cell with SiB3

• Initial prognostic variables for SiB3-RAMS created for each grid cell from SiB3 offline simulation

• Photosynthesis can be driven by MODIS satellite data - Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) > Updated each 8-day period > 1 km resolution

Simple Biosphere Model Version 3.0 (SiB3):• Photosynthesis: Farquhar C3 (1980) and Collatz C4 (1992)• Ball-Berry equation links assimilation to stomatal conductance and the surface energy budget• Respiration based on Q-10 temperature response and soil moisture, calculated to balance NEE annually• Two-stream radiation approximation to calculate incident direct and diffuse visible and near-IR radiation• Fully implicit calculations for prognostic variables (T, CO2, water)• 10 soil layers and up to 5 snow layers

CSU Regional Atmospheric Modeling System (RAMS):• Comprehensive mesoscale meteorological modeling system [Pielke et al., 1992; Cotton et al. 2002]• Harrington two-stream radiation scheme [1997]• Grell convection parameterization scheme [1993]• Lateral boundary nudging of meteorology

SiB3-RAMS simulations:• August 10-18, 2004• July 15-18, 2004• Covers most of NA (see initial CO2 for grid coverage)• 40 km grid spacing• NCEP Eta-40 km Reanalysis Data for init/boundary meteorology• Soil classification from IGBP with 10 km resolution• Fossil fuel emissions from Andres et al. [1996]• Biome classification at 1 km resolution from AVHRR [Hansen et al., 2000]• Initial and boundary CO2 from PCTM simulation

• Simulates observed wind at 396 m• Reasonable water vapor and relative humidity at 30 m • Overestimates daytime surface windspeeds• Overestimates temperature • Underestimates temperature diurnal cycle

CO2 concentrations at Southern Great Plains tower (SGP) in Oklahoma (25 m)

• Slight overestimate of sensible heat flux

• Reasonable latent heat flux

• Captures night-time respiration • Daytime draw-down slightly overestimated• Not enough diurnal variability• No flux on the 10th due to overcast conditions

• Not enough near- surface CO2 build-up at night• Modeled CO2 too low, likely due to PCTM initial conditions • Captures jump in 396 m CO2 on 16th

• Simulates surface CO2 well at site• Captures diurnal cycle and variability reasonably well

• Diurnal cycle underestimated• 396 m follows PCTM concentrations rather than obs• NEE well-captured with model

• Diurnal cycle underestimated• Respiration during evening overestimated in model