Multiple observation types reduce uncertainty in Australia's terrestrial carbon and water cycles
- 1CSIRO Marine and Atmospheric Research, P.O. Box 3023, Canberra ACT 2601, Australia
- 2CSIRO Ecosystem Sciences, P.O. Box 1700, Canberra ACT 2601, Australia
- 3CSIRO Land and Water, P.O. Box 1666, Canberra ACT 2600, Australia
- 4IBM Research-Australia, 204 Lygon St., Carlton, VIC 3053, Australia
Abstract. Information about the carbon cycle potentially constrains the water cycle, and vice versa. This paper explores the utility of multiple observation sets to constrain a land surface model of Australian terrestrial carbon and water cycles, and the resulting mean carbon pools and fluxes, as well as their temporal and spatial variability. Observations include streamflow from 416 gauged catchments, measurements of evapotranspiration (ET) and net ecosystem production (NEP) from 12 eddy-flux sites, litterfall data, and data on carbon pools. By projecting residuals between observations and corresponding predictions onto uncertainty in model predictions at the continental scale, we find that eddy flux measurements provide a significantly tighter constraint on continental net primary production (NPP) than the other data types. Nonetheless, simultaneous constraint by multiple data types is important for mitigating bias from any single type.
Four significant results emerging from the multiply-constrained model are that, for the 1990–2011 period: (i) on the Australian continent, a predominantly semi-arid region, over half the water loss through ET (0.64 ± 0.05) occurs through soil evaporation and bypasses plants entirely; (ii) mean Australian NPP is quantified at 2.2 ± 0.4 (1σ) Pg C yr−1; (iii) annually cyclic ("grassy") vegetation and persistent ("woody") vegetation account for 0.67 ± 0.14 and 0.33 ± 0.14, respectively, of NPP across Australia; (iv) the average interannual variability of Australia's NEP (±0.18 Pg C yr−1, 1σ) is larger than Australia's total anthropogenic greenhouse gas emissions in 2011 (0.149 Pg C equivalent yr–1), and is dominated by variability in desert and savanna regions.