Uwe Wittenberg

Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term (1920-1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr(-1), which is within the uncertainty of analysis based on CO2 and O-2 budgets. Three of the four models indicated tin accordance with O-2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Nino/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system.

Evaluation of terrestrial carbon cycle models through simulations of the seasonal cycle of atmospheric CO2: First results of a model intercomparison study

Results of an intercomparison among terrestrial biogeochemical models (TBMs) are reported, in which one diagnostic and five prognostic models have been run with the same long-term climate forcing. Monthly fields of net ecosystem production (NEP), which is the difference between net primary production (NPP) and heterotrophic respiration RH, at 0.5° resolution have been generated for the terrestrial biosphere. The monthly estimates of NEP in conjunction with seasonal CO2 flux fields generated by the seasonal Hamburg Model of the Oceanic Carbon Cycle (HAMOCC3) and fossil fuel source fields were subsequently coupled to the three-dimensional atmospheric tracer transport model TM2 forced by observed winds. The resulting simulated seasonal signal of the atmospheric CO2 concentration extracted at the grid cells corresponding to the locations of 27 background monitoring stations of the National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory network is compared with measurements from these sites. The Simple Diagnostic Biosphere Model (SDBM1), which is tuned to the atmospheric CO2 concentration at five monitoring stations in the northern hemisphere, successfully reproduced the seasonal signal of CO2 at the other monitoring stations. The SDBM1 simulations confirm that the north-south gradient in the amplitude of the atmospheric CO2 signal results from the greater northern hemisphere land area and the more pronounced seasonality of radiation and temperature in higher latitudes. In southern latitudes, ocean-atmosphere gas exchange plays an important role in determining the seasonal signal of CO2. Most of the five prognostic models (i.e., models driven by climatic inputs) included in the intercomparison predict in the northern hemisphere a reasonably accurate seasonal cycle in terms of amplitude and, to some extent, also with respect to phase. In the tropics, however, the prognostic models generally tend to overpredict the net seasonal exchanges and stronger seasonal cycles than indicated by the diagnostic model and by observations. The differences from the observed seasonal signal of CO2 may be caused by shortcomings in the phenology algorithms of the prognostic models or by not properly considering the effects of land use and vegetation fires on CO2 fluxes between the atmosphere and terrestrial biosphere.

Evaluation of terrestrial carbon cycle models with atmospheric CO2 measurements: Results from transient simulations considering increasing CO2, climate and land-use effects

An atmospheric transport model and observations of atmospheric CO2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land-use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability.

On the influence of biomass burning on the seasonal CO2 signal as observed at monitoring stations

We investigated the role of biomass burning in simulating the seasonal signal in both prognostic and diagnostic analyses. The prognostic analysis involved the High-Resolution Biosphere Model, a prognostic terrestrial biosphere model, and the coupled vegetation fire module, which together produce a prognostic data set of biomass burning. The diagnostic analysis involved the Simple Diagnostic Biosphere Model (SDBM) and the Hao and Liu [1994] diagnostic data set of biomass burning, which have been scaled to global 2 and 4 Pg C yr−1, respectively. The monthly carbon exchange fields between the atmosphere and the biosphere with a spatial resolution of 0.5° × 0.5°, the seasonal atmosphere-ocean exchange fields, and the emissions from fossil fuels have been coupled to the three-dimensional atmospheric transport model TM2. We have chosen eight monitoring stations of the National Oceanic and Atmospheric Administration network to compare the predicted seasonal atmospheric CO2 signals with those deduced from atmosphere-biosphere carbon exchange fluxes without any contribution from biomass burning. The prognostic analysis and the diagnostic analysis with global burning emissions of 4 Pg C yr−1 agree with respect to the change in the amplitude of the seasonal CO2 concentration introduced through biomass burning. We find that the seasonal CO2 signal at stations in higher northern latitudes (north of 30°N) is marginally influenced by biomass burning. For stations in tropical regions an increase in the CO2 amplitude of more than 1 ppmv (up to 50% with respect to the observed trough to peak amplitude) has been calculated. Biomass burning at stations farther south accounts for an increase in the CO2 amplitude of up to 59% (0.6 ppmv). A change in the phase of the seasonal CO2 signal at tropical and southern stations has been shown to be strongly influenced by the onset of biomass burning in southern tropical Africa and America. Comparing simulated and observed seasonal CO2 signals, we find higher discrepancies at southern tropical stations if biomass burning emissions are included. This is caused by the additional increase in the amplitude in the prognostic analysis and a phase shift in a diagnostic analysis. In contrast, at the northern tropical stations biomass burning tends to improve the estimates of the seasonal CO2 signal in the prognostic analysis because of strengthening of the amplitude. Since the SDBM predicts the seasonal CO2 signal reasonably well for the northern hemisphere tropical stations, no general improvement of the fit occurs if biomass burning emissions are considered.

The substitution of high-resolution terrestrial biosphere models and carbon sequestration in response to changing CO2 and climate

Strategies are developed to analyze and represent spatially resolved biosphere models for carbon sequestration in response to changes in atmospheric CO 2 and climate by reduced-form, substitute models. We explore the High-Resolution Terrestrial Biosphere Model as implemented in the Community Terrestrial Biosphere Model (HRBM/CTBM), the Frankfurt Biosphere Model (FBM), and the box-type biosphere of the Bern model. Storage by CO 2 fertilization is described by combining analytical representations of (1) net primary productivity (NPP) as a function of atmospheric CO 2 and (2) a decay impulse response function to characterize the timescales of biospheric carbon turnover. Storage in response to global warming is investigated for the HRBM/CTBM. The relation between the evolution of radiative forcing and climate change is expressed by a combination of impulse response functions and empirical orthogonal functions extracted from results of the European Center/Hamburg (ECHAM3) coupled atmosphere-ocean general circulation model. A box-type, differential-analogue substitute model is developed to represent global carbon storage of the HRBM/CTBM in response to regional changes in Temperature, Precepitation and cloud cover. The substitute models represent the spatially resolved models accurately and cost-efficiently for carbon sequestration in response to changes in CO 2 or in CO 2 and climate and for simulations of the global isotopic signals. Deviations in carbon uptake simulated by the spatially resolved models and their substitutes are less than a few percent.