Anders Ahlström

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.

The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink

The difference is found at the margins The terrestrial biosphere absorbs about a quarter of all anthropogenic carbon dioxide emissions, but the amount that they take up varies from year to year. Why? Combining models and observations, Ahlström et al. found that marginal ecosystems—semiarid savannas and low-latitude shrublands—are responsible for most of the variability. Biological productivity in these semiarid regions is water-limited and strongly associated with variations in precipitation, unlike wetter tropical areas. Understanding carbon uptake by these marginal lands may help to improve predictions of variations in the global carbon cycle. Science, this issue p. 895 Semi-arid regions cause most of the interannual variability of the terrestrial carbon dioxide sink. The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections

We have investigated the spatio-temporal carbon balance patterns resulting from forcing a dynamic global vegetation model with output from 18 climate models of the CMIP5 (Coupled Model Intercomparison Project Phase 5) ensemble. We found robust patterns in terms of an extra-tropical loss of carbon, except for a temperature induced shift in phenology, leading to an increased spring uptake of carbon. There are less robust patterns in the tropics, a result of disagreement in projections of precipitation and temperature. Although the simulations generally agree well in terms of the sign of the carbon balance change in the middle to high latitudes, there are large differences in the magnitude of the loss between simulations. Together with tropical uncertainties these discrepancies accumulate over time, resulting in large differences in total carbon uptake over the coming century (−0.97–2.27 Pg C yr −1 during 2006–2100). The terrestrial biosphere becomes a net source of carbon in ten of the 18 simulations adding to the atmospheric CO 2 concentrations, while the remaining eight simulations indicate an increased sink of carbon. (Less)

Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity.

Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Compensatory water effects link yearly global land CO2 sink changes to temperature.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Evaluation of land surface models in reproducing satellite-derived LAI over the high-latitude northern hemisphere. Part I: Uncoupled DGVMs

Leaf Area Index (LAI) represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades.

African tropical rainforest net carbon dioxide fluxes in the twentieth century.

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO2 fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (−0.02 kg C m−2 yr−1 or −0.04 Pg C yr−1, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO2 flux at the beginning of the century (σ1901 = 0.02 kg C m−2 yr−1), but diverged exponentially throughout the century (σ2010 = 0.03 kg C m−2 yr−1). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO2, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO2 fluxes with increasing atmospheric CO2 concentrations and extreme climatic events, as the uncertainties will only amplify in the next century.

Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management

It is over three decades since a large terrestrial carbon sink (S-T) was first reported. The magnitude of the net sink is now relatively well known, and its importance for dampening atmospheric CO2 accumulation, and hence climate change, widely recognised. But the contributions of underlying processes are not well defined, particularly the role of emissions from land-use change (E-LUC) versus the biospheric carbon uptake (S-L; S-T. = S-L - E-LUC). One key aspect of the interplay of E-LUC and SL is the role of agricultural processes in land-use change emissions, which has not yet been clearly quantified at the global scale. Here we assess the effect of representing agricultural land management in a dynamic global vegetation model. Accounting for harvest, grazing and tillage resulted in cumulative E-LUC since 1850 ca. 70% larger than in simulations ignoring these processes, but also changed the timescale over which these emissions occurred and led to underestimations of the carbon sequestered by possible future reforestation actions. The vast majority of Earth system models in the recent IPCC Fifth Assessment Report omit these processes, suggesting either an overestimation in their present-day ST, or an underestimation of SL, of up to 1.0 Pg Ca-1. Management processes influencing crop productivity per se are important for food supply, but were found to have little influence on E-LUC. (Less)

Too early to infer a global NPP decline since 2000

The global terrestrial carbon cycle plays a pivotal role in regulating the atmospheric composition of greenhouse gases. It has recently been suggested that the upward trend in net primary production (NPP) seen during the 1980s and 90s has been replaced by a negative trend since 2000 induced by severe droughts mainly on the southern hemisphere. Here we compare results from an individual-based global vegetation model to satellite-based estimates of NPP and top-down reconstructions of net biome production (NBP) based on inverse modelling of observed CO2 concentrations and CO2 growth rates. We find that simulated NBP exhibits considerable covariation on a global scale with interannual fluctuations in atmospheric CO2. Our simulations also suggest that droughts in the southern hemisphere may have been a major driver of NPP variations during the past decade. The results, however, do not support conjecture that global terrestrial NPP has entered a period of drought-induced decline. Citation: Ahlstrom, A., P. A. Miller, and B. Smith (2012), Too early to infer a global NPP decline since 2000, Geophys. Res. Lett., 39, L15403, doi:10.1029/2012GL052336. (Less)