Transcript CN: CO 2
Fundamental influence of carbonnitrogen cycle coupling on climatecarbon cycle feedbacks Peter Thornton NCAR, CGD/TSS Collaborators: Keith Lindsay, Scott Doney, Keith Moore, Natalie Mahowald, Mariana Vertenstein, Forrest Hoffman, Jean-Francois Lamarque, Nan Rosenbloom, Beth Holland, Johannes Feddema Overview • Review carbon-nitrogen coupling hypotheses • Summarize results from offline simulations • New results from fully-coupled simulations • Review disturbance history hypotheses • Preliminary results from fully-coupled simulations with landcover change Recent findings from field experiments • Norby et al., Finzi et al., Hungate et al., Gill et al., 2006 (Ecology) – CO2 fertilization shifts N from soil organic matter to vegetation and litter – Some sites show progressive N limitation • Reich et al., 2006 (Nature) – Low availability of N progressively suppresses the positive response of plant biomass to elevated CO2 • Perennial grassland: CO2 x N x (sp. diversity) • van Groenigen et al., 2006 (PNAS) – Soil C accumulation under elevated CO2 depends on increased N inputs (fixation or deposition). Brief history of coupled C-N modeling • Pre-1983: Decomposition models • Parton et al., 1983, 1987, 1988, 1989, etc. – CENTURY: soil organic matter and vegetation model, coupled C, N, P, and S dynamics • McGuire et al., 1992 – TEM: C, N interactions control net primary production (N.Am.) • Rastetter et al., 1992, 1997 – MEL: Effects of CO2, N deposition, and warming on carbon uptake • Schimel et al., 2000 – VEMAP: Terrestrial biogeochemistry model intercomparison • Thornton et al., 2002 – Biome-BGC: C, N, and disturbance history control net ecosystem carbon exchange (evaluation against eddy flux obs.) • Liu et al., 2005 – IBIS: NPP estimates improved when N dynamics added to a Conly model (evaluation against remote sensing NPP est.) Brief history of coupled climate – carbon cycle modeling • Cox et al., 2000 – HADCM3 / MOSES / TRIFFID: Strong positive carbon-climate feedback. • Joos et al., 2001 – BERN-CC: • Dufresne et al., 2002 – LMD5 / SLAVE: Moderate positive carbon-climate feedback • Thompson et al., 2004 – CCM3 / IBIS: Strong negative CO2 feedback • Fung et al., Doney et al., 2005 – CCM3 / LSM / CASA’: moderate CO2 feedback, weak climate feedback • Friedlingstein et al., 2006 – C4MIP Phase 2: Eleven models, wide range of CO2 and climate (temperature) sensitivities. Carbon-Nitrogen CENTURY MEL Biome-BGC TEM VEMAP IBIS+N Carbon-Climate Convergence toward a fully coupled carbonnitrogen-climate model Hadley C4MIP Phase 2 IPSL Carbon-Nitrogen-Climate CCSM/CLM-CN ‘86 ‘88 ‘90 ‘92 ‘94 ‘96 ‘98 ‘00 ‘02 ‘04 ‘06 Nitrogen cycle Carbon cycle Internal (fast) Atm CO2 photosynthesis External (slow) denitrification N deposition Plant assimilation respiration litterfall & mortality Litter / CWD Soil Mineral N decomposition Soil Organic Matter mineralization N leaching N fixation Schematic of terrestrial nitrogen cycle Image source: US EPA C-N coupling: hypotheses • Smaller CO2 fertilization effect, compared to Conly model – Reduced ecosystem base state – Stoichiometric constraints on new growth – Progressive N-limitation: carbon accumulation in litter and soil leads to increased nitrogen immobilization • Reduced carbon cycle sensitivity to temperature and precipitation variability – Reduced ecosystem base state – Internal N cycling links plant and microbial communities C-N coupling: hypotheses (cont.) • Climate x CO2 response – Expect changes over time in land carbon cycle sensitivity to variability in temperature and precipitation, forced by land carbon cycle response to increasing CO2. • Different fertilization responses for increased CO2 and increased mineral N – CO2: increased storage in vegetation carbon – N: increased storage in vegetation and soil carbon Offline simulation protocol 1. Drive CLM-CN with 25 years of hourly surface weather from coupled CAM / CLM-CN. 2. Spinup at pre-industrial CO2, N deposition, landcover 3. Transient experiments (1850-2100) • Increasing CO2 • Increasing N deposition • Increasing CO2 and N deposition 4. Repeat experiments in C-only mode • Supplemental N addition eliminates N-limitation • Test dependence on base state Evaluation of fluxes and states Thornton and Zimmermann, J. Clim. (in press) Land biosphere sensitivity to increasing atmospheric CO2 (L) GPP (PgC/y) (2100) CLM-C 1014 177 1.44 CLM-C2 771 146 1.25 CLM-CN 653 102 0.35 % change Veg C GPP L CLM-C2 -24% -18% -13% CLM-CN -35% -42% -76% CN : C2 1.5 2.3 5.8 CLM-C CLM-C2 CLM-CN (CO2) C4MIP models C4MIP mean Thornton et al., GBC (in review) L Veg C (Pg C) Spatial distribution of L 2000 2100 C-N C-N C-only C-only Thornton et al., GBC (in review) 5 0 4 -5 3 -10 CLM-C CLM-C(2) CLM-CN 2 -15 1 -20 0 -25 Tair Prcp % change VegC GPP Tair Prcp CLM-C2 -24% -18% -17% -32% Figure 2 Sensitivity of global-35% NEE from CLM-C and CLM-CN to interannual variability in CLM-CN -42% -77% -58% global mean air temperature (Tair) and precipitation (Prcp) over land. Error bars one standard deviation around mean response. CNshow : C2 1.5 Thornton et al., GBC (in review) 2.3 4.5 1.8 NEE sensitivity to Prcp (PgC / mm d-1) NEE sensitivity to Tair (PgC / K) NEE sensitivity to Tair and Prcp (at steady-state) NEE sensitivity to Tair and Prcp (at steady-state) Tair Prcp C-N C-N C-only C-only Thornton et al., GBC (in review) NEE sensitivity to Tair and Prcp: effects of rising CO2 and anthropogenic N deposition 80 % change from control 60 40 20 0 CLM-C: +CO2 -20 CLM-C(2): +CO2 CLM-CN: +CO2 CLM-CN: +CO2 +Nmin -40 Tair Prcp Carbon-only model has increased sensitivity to Tair and Prcp under rising CO2. CLM-CN has decreased sensitivity to both Tair and Prcp, due to increasing N-limitation. Thornton et al., GBC (in review) Fertilization responses to CO2 and mineral N deposition (period 2000 – 2100) Tot C (PgC) 204 % Veg C % Lit C % SOM C 79 13 8 50 56 13 31 C-only: CO2 843 66 14 20 C-only(2): CO2 740 66 13 21 C-N: CO2 C-N: Ndep • C-N gives qualitative match to observations from field experiments • Changing the base state has negligible effect on partitioning of fertilization response • Important because of order-of-magnitude differences in turnover times for vegetation and SOM pools, regionalization of sink permanence. Thornton et al., GBC (in review) Summary of offline results • C-N coupling results in large decrease in CO2 fertilization of land ecosystems. • Sensitivities of net carbon flux to temperature and precipitation variation are damped by C-N coupling. • C-N coupling reverses sign of trend in carbon-climate sensitivity under increasing CO2. • Model agrees with experimental studies on contrasting effects of CO2 and N fertilization Fully-coupled climate-carbon-nitrogen simulations • CCSM3 framework: CAM + CICE + POP Doney/Moore/Lindsay ocean ecosystem + CLM-CN • 1000-year stable pre-industrial control • Historical + A2 (1890-2100), forced with fossil fuel emissions and nitrogen deposition. • Coupled vs. fixed radiative effects of atmospheric CO2. Land biosphere sensitivity to increasing atmospheric CO2 (L) Offline results Land sensitivity to increasing CO2 is not significantly different between offline and fully-coupled simulations Negative climate feedback of land carbon cycle Results from fully-coupled runs: Changes in land carbon stocks: 1870-2100 Pool Change % of total PgC Plant 300 89% CWD 20 6% Litter 1 <1% Soil 17 5% Total 338 (25%) 5 0 4 -5 3 -10 CLM-C CLM-CN CCSM3 2 -15 1 -20 0 -25 Tair Prcp Land carbon cycle sensitivity to variation in temperature and precipitation is not significantly different between offline and fully-coupled simulations NEE sensitivity to Prcp (PgC / mm d-1) NEE sensitivity to Tair (PgC / K) NEE sensitivity to Tair and Prcp (at steady-state) Climate-carbon cycle feedbacks CO2-induced climate change (warmer and wetter) leads to increased land carbon storage Climate-carbon cycle feedbacks Vegetation C CWD C Litter C Soil C Climate change feeds back to carbon cycle in part through change in nitrogen availability Climate-carbon cycle feedbacks Climate change impact on land carbon uptake closely related to changes in precipitation Climate-carbon cycle feedbacks Fractions of 1870-2100 anthropogenic emissions in land, ocean, and atmosphere pools CCSM3.1-BGC C4MIP mean uncoupled coupled uncoupled coupled Land-borne fraction 0.15 0.18 0.29 0.21 Ocean-borne fraction 0.22 0.21 0.25 0.25 Airborne fraction 0.63 0.61 0.46 0.54 What about disturbance history and landcover change? Results: NEE response to disturbance, changing [CO2]atm, and Ndep shows strong interaction effects Fully-coupled simulations with prescribed landcover changes (prognostic fluxes) • Using subset of data from Johannes Feddema – Annual time slices from 1870-2100, originally on half-degree grid. – Historical data from Ramankutty and Foley (1999), Goldewijk (2001), integration with present-day MODIS landcover. – Landcover change for 2000-2100 based on SRES A2 scenario. • New prognostic component in CLM-CN to handle carbon and nitrogen fluxes and mass balance associated with landcover change. – Conversions to/from all plant functional types. – Tracking two wood product pools in each land gridcell (10-yr and 100-yr turnover times). • Fossil-fuel emissions, N deposition, radiatively coupled Grass Influence of landcover change on land carbon flux and global pools Tree +200 ppmv net (by 2100) Shrub Agric +250 ppmv from land -50 ppmv from ocean G T S A • GPP falls and then recovers during landcover transition • Plant respiration increases, due to replacement of woody with herbaceous biomass • NPP falls and remains lower (GPP is offset by plant respiration) • Soil respiration rises in response to conversion fluxes, then falls in response to reduced NPP Carbon cycle impacts of landcover change • Transient fluctuations in GPP as new ecosystem is established • Reduced NPP due to increased plant respiration – Depends on tree-to-ag vs. grass-to-ag transition and regional climate (biggest effect for tropical forest conversion) • Increased soil respiration due to more labile litter inputs. • Reduced potential for CO2 fertilization of land ecosystems, due to loss of area of woody vegetation. Changes in vegetation carbon pools due to landcover change Comparison to previous results (preliminary) • IPCC TAR includes estimates of fluxes due to landcover change, for the A2 scenario, which are more than an order of magnitude smaller than those predicted here for the 21st century. – Appear to ignore the mechanism of reduced sink potential. • Gitz and Ciais (2003): EMIC. Landcover flux much larger than IPCC, smaller than CCSM3-BGC. Conclusions • Carbon-nitrogen cycle coupling has a fundamental influence on climate-carbon cycle dynamics • Mechanistic treatment of landcover change suggests this signal will be a major factor influencing future atmospheric CO2 concentrations, and regional patterns of climate change. • Next generation models should explicitly include the factors driving fossil fuel emissions and landcover change.