Impacts of Soil Freeze/Thaw Dynamics on the North American Carbon Cycle

Between 68 and 80 percent of North America experiences seasonal freezing and thawing with the relative influence of these processes on terrestrial carbon budgets generally increasing at higher latitudes and elevations. The timing and duration of soil freeze/thaw state are closely linked to vegetation phenology, and growing season dynamics in northern temperate, sub-alpine, boreal and arctic biomes. Variability in these environmental variables also has been shown to have dramatic impacts on spatial patterns, seasonal to inter- annual variability and long-term trends in terrestrial carbon budgets and surface-atmosphere trace gas exchange primarily through biophysical controls on both photosynthesis and respiration. These processes are strongly influenced by land cover and soil properties, as well as the timing and condition of seasonal snow cover. Based on this background, we will integrate remote sensing data sets, ground-based measurements, and numerical modeling to quantify the effects of soil temperature, soil freeze-thaw dynamics, and snow cover on seasonal to inter-annual variability in the North American terrestrial carbon cycle. Our overall goal is to understand the role of freeze-thaw processes in determining seasonal and inter-annual variability in terrestrial biomass, photosynthesis, respiration, and net CO2 fluxes over continental North America. Using remote sensing products, in situ observations, and a soil thermodynamic model, we will estimate soil temperatures and snow cover over North America at 25-km resolution for North America from 1981-2003 (23 years). We will feed these estimated soil temperatures and snow cover, along with additional remote sensing data, into an ecosystem model to estimate biomass and net carbon fluxes. Both models will use the North American Regional Reanalysis, so the resulting estimates of soil thermodynamic properties, biomass, and carbon fluxes will be optimally consistent with each other and with actual weather conditions in North America. We will statistically analyze these optimal carbon fluxes to understand the environmental drivers and biophysical responses regulating the spatial patterns and temporal variability in the North American terrestrial carbon cycle. Using standard Monte Carlo techniques, we will quantify uncertainty in our estimated carbon fluxes. Lastly, we will perturb our input data to assess the sensitivity of our estimated fluxes to long-term climate change.