Seasonal Cycle Of Atmospheric CO2 Research Articles

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa.

Changing amplitude of the seasonal cycle of atmospheric CO2 (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO2 record, shows an increasing SCA before the 1980s (p<.01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO2 fertilization. This challenges the view that CO2 fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO2 flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

Non-uniform seasonal warming regulates vegetation greening and atmospheric CO2 amplification over northern lands

The enhanced vegetation growth by climate warming plays a pivotal role in amplifying the seasonal cycle of atmospheric CO2 at northern lands (>50° N) since 1960s. However, the correlation between vegetation growth, temperature and seasonal amplitude of atmospheric CO2 concentration have become elusive with the slowed increasing trend of vegetation growth and weakened temperature control on CO2 uptake since late 1990s. Here, based on in situ atmospheric CO2 concentration records from the Barrow observatory site, we found a slowdown in the increasing trend of the atmospheric CO2 amplitude from 1990s to mid-2000s. This phenomenon was associated with the paused decrease in the minimum CO2 concentration ([CO2]min), which was significantly correlated with the slowdown of vegetation greening and growing-season length extension. We then showed that both the vegetation greenness and growing-season length were positively correlated with spring but not autumn temperature over the northern lands. Furthermore, such asymmetric dependences of vegetation growth upon spring and autumn temperature cannot be captured by the state-of-art terrestrial biosphere models. These findings indicate that the responses of vegetation growth to spring and autumn warming are asymmetric, and highlight the need of improving autumn phenology in the models for predicting seasonal cycle of atmospheric CO2 concentration.

Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2.

Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate-carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate-carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments with the Earth System Model CESM1(BGC)

Abstract Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon–nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO2 tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO2 fluxes contribute to the increase of atmospheric CO2 in the twentieth century, analyze how atmospheric CO2 and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO2 and its surface fluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO2 over the twentieth century and too small of a seasonal cycle of atmospheric CO2 in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO2, land-use change, and atmospheric deposition of nitrogen.

A comprehensive benchmarking system for evaluating global vegetation models

Abstract. We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

Impacts of Seasonal Fossil and Ocean Emissions on the Seasonal Cycle of Atmospheric CO2

The seasonal cycle of atmospheric CO2 at surface observation stations in the northern hemisphere is driven primarily by net ecosystem production (NEP) fluxes from terrestrial ecosystems. In additio...

An estimate of monthly global emissions of anthropogenic CO2: Impact on the seasonal cycle of atmospheric CO2

Monthly estimates of the global emissions of anthropogenic CO2 are presented. Approximating the seasonal CO2 emission cycle using a 2‐harmonic Fourier series with coefficients as a function of latitude, the annual fluxes are decomposed into monthly flux estimates based on data for the United States and applied globally. These monthly anthropogenic CO2 flux estimates are then used to model atmospheric CO2 concentrations using meteorological fields from the NASA GEOS‐4 data assimilation system. We find that the use of monthly resolved fluxes makes a significant difference in the seasonal cycle of atmospheric CO2 in and near those regions where anthropogenic CO2 is released to the atmosphere. Local variations of 2–6 ppmv CO2 in the seasonal cycle amplitude are simulated; larger variations would be expected if smaller source‐receptor distances could be more precisely specified using a more refined spatial resolution. We also find that in the midlatitudes near the sources, synoptic scale atmospheric circulations are important in the winter and that boundary layer venting and diurnal rectifier effects are more important in the summer. These findings have implications for inverse‐modeling efforts that attempt to estimate surface source/sink regions especially when the surface sinks are colocated with regions of strong anthropogenic CO2 emissions.

Three years of aircraft-based trace gas measurements over the Fyodorovskoye southern taiga forest, 300 km north-west of Moscow

As part of the EUROSIBERIAN CARBONFLUX project, regular measurements have been performed in the lower troposphere over a southern taiga forest area in Fyodorovskoye, Western Russia (56°28′N, 32°56′E). Up to 70 flights have been made between May 1998 and December 2000, plus additional intensive campaigns to study the diurnal variability of atmospheric trace gases within the boundary layer. We sampled flasks between 100 and 3000 m for analysis of CO2, δ13C and δ18O in CO2, CH4 and CO. In addition, in-situ CO2, relative humidity, pressure and temperature were performed for a better description of the vertical variability and accurate determination of the boundary layer height. The peak-to-peak amplitude of the seasonal cycle of atmospheric CO2 within the boundary layer of 26.5 ppm is about twice the one observed in the free troposphere (14.6 ppm). The spring draw down of CO2 also occurs one month earlier than in the free troposphere aloft. There is also an increase by factor of two in the vertical variability of CO2 within the free troposphere between summer and winter, which may be related to the variability of advection and mixing. Linear regression analysis applied to flask measurements of CO, CH4 and δ13C versus CO2 in the free troposphere indicates that industrial emissions over Europe are a dominant source of synoptic variability in wintertime in air masses reaching Fyodorovskoye. On the other hand, the variability of trace gases in the boundary layer observed during intensive campaigns is consistent with the patterns of proximate sources over the underlying southern taiga landscape at Fyodorovskoye.

Three years of aircraft-based trace gas measurements over the Fyodorovskoye southern taiga forest, 300 km north-west of Moscow

As part of the EUROSIBERIAN CARBONFLUX project, regular measurements have been performed in the lower troposphere over a southern taiga forest area in Fyodorovskoye, Western Russia (56 ◦ 28 � N, 32 ◦ 56 � E). Up to 70 flights have been made between May 1998 and December 2000, plus additional intensive campaigns to study the diurnal variability of atmospheric trace gases within the boundary layer. We sampled flasks between 100 and 3000 m for analysis of CO2, δ 13 C and δ 18 Oi n CO 2 ,C H 4 and CO. In addition, in-situ CO2, relative humidity, pressure and temperature were performed for a better description of the vertical variability and accurate determination of the boundary layer height. The peak-to-peak amplitude of the seasonal cycle of atmospheric CO2 within the boundary layer of 26.5 ppm is about twice the one observed in the free troposphere (14.6 ppm). The spring draw down of CO2 also occurs one month earlier than in the free troposphere aloft. There is also an increase by factor of two in the vertical variability of CO2 within the free troposphere between summer and winter, which may be related to the variability of advection and mixing. Linear regression analysis applied to flask measurements of CO, CH4 and δ 13 C versus CO2 in the free troposphere indicates that industrial emissions over Europe are a dominant source of synoptic variability in wintertime in air masses reaching Fyodorovskoye. On the other hand, the variability of trace gases in the boundary layer observed during intensive campaigns is consistent with the patterns of proximate sources over the underlying southern taiga landscape at Fyodorovskoye.

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 O2 budgets. Three of the four models indicated (in accordance with O2 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 Niño/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.

Modeling the effects of snowpack on heterotrophic respiration across northern temperate and high latitude regions: Comparison with measurements of atmospheric carbon dioxide in high latitudes

Simulations by global terrestrial biogeochemical models (TBMs) consistently underestimate the concentration of atmospheric carbon dioxide (CO2 at high latitude monitoring stations during the non-growing season. We hypothesized that heterotrophic respiration is underestimated during the nongrowing season primarily because TBMs do not generally consider the insulative effects of snowpack on soil temperature. To evaluate this hypothesis, we compared the performance of baseline and modified versions of three TBMs in simulating the seasonal cycle of atmospheric CO2 at high latitude CO2 monitoring stations; the modified version maintained soil temperature at 0 °C when modeled snowpack was present. The three TBMs include the Carnegie-Ames-Stanford Approach (CASA), Century, and the Terrestrial Ecosystem Model (TEM). In comparison with the baseline simulation of each model, the snowpack simulations caused higher releases of CO2 between November and March and greater uptake of CO2 between June and August for latitudes north of 30° N. We coupled the monthly estimates of CO2 exchange, the seasonal carbon dioxide flux fields generated by the HAMOCC3 seasonal ocean carbon cycle model, and fossil fuel source fields derived from standard sources to the three-dimensional atmospheric transport model TM2 forced by observed winds to simulate the seasonal cycle of atmospheric CO2 at each of seven high latitude monitoring stations. In comparison to the CO2 concentrations simulated with the baseline fluxes of each TBM, concentrations simulated using the snowpack fluxes are generally in better agreement with observed concentrations between August and March at each of the monitoring stations. Thus, representation of the insulative effects of snowpack in TBMs generally improves simulation of atmospheric CO2 concentrations in high latitudes during both the late growing season and nongrowing season. These simulations highlight the global importance of biogeochemical processes during the nongrowing season in estimating carbon balance of ecosystems in northern high and temperate latitudes.

Increases in early season ecosystem uptake explain recent changes in the seasonal cycle of atmospheric CO2 at high northern latitudes

We report changes in the seasonal cycle of atmospheric CO2 at high northern latitudes from 1980 to 1997 based on NOAA/CMDL observation stations. Using a combination of biogeochemical and atmospheric modeling approaches, we show that increases in early season net ecosystem uptake explain the recent trends in the seasonal cycle. A strong year‐to‐year correlation between spring temperatures and early season uptake further suggests that increased photosynthetic activity is the primary mechanism. At the end of the growing season, a strong correlation between fall temperatures and late season releases provides evidence for a large active pool of decomposing soil carbon. Taken together, our results suggest that the seasonal timing of temperature anomalies may have important consequences for the interannual carbon balance of northern ecosystems.

Atmospheric mixing and the CO2 seasonal cycle

Atmospheric mixing is determined by such factors as advection and diffusion, planetary boundary layer (PBL) depth, and cloud transport‐together they determine an effective ’mixing volume’ to which CO2 is then added or removed. In this study a mathematical model is developed to quantify the key factors determining the local ’mixing volume’ and hence the seasonal cycle of atmospheric CO2. It was found that the seasonal variation in horizontal advection is more important than the seasonal variation in PBL depth in determining the local mean and seasonal variation in atmospheric CO2 and that cloud transport plays a minor role.

The contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric carbon dioxide

We characterized decadal changes in the amplitude and shape of the seasonal cycle of atmospheric CO2 with three kinds of analysis. First, we calculated the trends in the seasonal cycle of measured atmospheric CO2 at observation stations in the National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostic Laboratory network. Second, we assessed the impact of terrestrial ecosystems in various localities on the mean seasonal cycle of CO2 at observation stations using the Carnegie‐Ames‐Stanford Approach terrestrial biosphere model and the Goddard Institute for Space Studies (GISS) atmospheric tracer transport model. Third, we used the GISS tracer model to quantify the contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric CO2 for the period 1961–1990, specifically examining the effects of biomass burning, emissions from fossil fuel combustion, and regional increases in net primary production (NPP). Our analysis supports results from previous studies that indicate a significant positive increase in the amplitude of the seasonal cycle of CO2 at Arctic and subarctic observation stations. For stations north of 55°N the amplitude increased at a mean rate of 0.66% yr−1 from 1981 to 1995. From the analysis of ecosystem impacts on the mean seasonal cycle we find that tundra, boreal forest, and other northern ecosystems are responsible for most of the seasonal variation in CO2 at stations north of 55°N. The effects of tropical biomass burning on trends in the seasonal cycle are minimal at these stations, probably because of strong vertical convection in equatorial regions. From 1981 to 1990, fossil fuel emissions contributed a trend of 0.20% yr−1 to the seasonal cycle amplitude at Mauna Loa and less than 0.10% yr−1 at stations north of 55°N. To match the observed amplitude increases at Arctic and subarctic stations with NPP increases, we find that north of 30°N a 1.7 Pg C yr−1 terrestrial sink would be required. In contrast, over regions south of 30°N, even large NPP increases and accompanying terrestrial sinks would be insufficient to account for the increase in high‐latitude amplitudes.

Increased plant growth in the northern high latitudes from 1981 to 1991

Variations in the amplitude and timing of the seasonal cycle of atmospheric CO2 have shown an association with surface air temperature consistent with the hypothesis that warmer temperatures have promoted increases in plant growth during summer1 and/or plant respiration during winter2 in the northern high latitudes. Here we present evidence from satellite data that the photosynthetic activity of terrestrial vegetation increased from 1981 to 1991 in a manner that is suggestive of an increase in plant growth associated with a lengthening of the active growing season. The regions exhibiting the greatest increase lie between 45°N and 70°N, where marked warming has occurred in the spring time3 due to an early disappearance of snow4. The satellite data are concordant with an increase in the amplitude of the seasonal cycle of atmospheric carbon dioxide exceeding 20% since the early 1970s, and an advance of up to seven days in the timing of the drawdown of CO2 in spring and early summer1. Thus, both the satellite data and the CO2 record indicate that the global carbon cycle has responded to interannual fluctuations in surface air temperature which, although small at the global scale, are regionally highly significant.

Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO2

We examine the sensitivity of the seasonal cycle of heterotrophic respiration to model estimates of litterfall seasonality, herbivory, plant allocation, tissue chemistry, and land use. As a part of this analysis, we compare heterotrophic respiration models based solely on temperature and soil moisture controls (zero‐order models) with models that depend on available substrate as well (first‐order models). As indicators of regional and global CO2 exchange, we use maps of monthly global net ecosystem production, growing season net flux (GSNF), and simulated atmospheric CO2 concentrations from an atmospheric tracer transport model. In one first‐order model, CASA, variations on the representation of the seasonal flow of organic matter from plants to heterotrophs can increase global GSNF as much as 60% (5.7 Pg C yr−1) above estimates obtained from a zero‐order model. Under a new first‐order scheme that includes separate seasonal dynamics for leaf litterfall, fine root mortality, coarse woody debris, and herbivory, we observe an increase in GSNF of 8% (0.7 Pg C yr−1) over that predicted by the zero‐order model. The increase in seasonality of CO2 exchange in first‐order models reflects the dynamics of labile litter fractions; specifically, the rapid decomposition of a pulse of labile leaf and fine root litter that enters the heterotrophic community primarily from the middle to the end of the growing season shifts respiration outside the growing season. From the perspective of a first‐order model, we then explore the consequences of land use change and winter temperature anomalies on the amplitude of the seasonal cycle of atmospheric CO2. Agricultural practices that accelerate decomposition may drive a long‐term increase in the amplitude, independent of human impacts on plant production. Consideration of first‐order litter decomposition dynamics may also help explain year‐to‐year variation in the amplitude.

The seasonal cycle of atmospheric CO2: A study based on the NCAR Community Climate Model (CCM2)

A global three‐dimensional atmospheric model, the NCAR CCM2 general circulation model, has been adapted to study the hourly to yearly variability of CO2 in the atmosphere. Features of this CCM2‐based model include high spatial resolution (2.8° × 2.8° latitude/longitude), 18 vertical levels, a 15‐min time step, and an explicit, nonlocal atmospheric boundary layer parameterization. The surface source/sink relationships used include exchange with the ocean, the terrestrial biosphere, biomass burning, and fossil fuel release of CO2. The timing and magnitude of the model seasonal cycle are compared to observational data for 28 sites. The seasonal cycle of atmospheric CO2 is generally well predicted by the model for most of the northern hemisphere, but estimates of the amplitude of the seasonal cycle in the southern hemisphere are overpredicted. To address this aspect more rigorously, we have used the monthly surface ocean pCO2 maps created by the Max‐Planck‐Hamburg ocean general circulation model to asses the ocean seasonality on the atmospheric surface CO2 seasonality. The globally averaged interhemispheric gradient in atmospheric CO2 concentrations, as computed with the chosen source/sink distributions, is a factor of two too high compared to data, and selected longitudinal bands may be up to 50% higher than the zonal mean. The high temporal resolution of this model allows the infrequent yet real extrema in atmospheric CO2 concentrations to be captured. The vertical attenuation of the seasonal cycle of atmospheric CO2 is well simulated by the boundary layer/free troposphere interaction in the model in the northern hemisphere. Conversely, an increasing amplitude of the seasonal cycle aloft is found in the midlatitude southern hemisphere indicating interhemispheric transport effects from north to south. We use two different models of the terrestrial biosphere to examine the influence on the computed seasonal cycle and find appreciable differences, especially in continental sites. A global three‐dimensional chemical transport model is used to assess the production of CO2 from the oxidation of CO throughout the volume of the atmosphere. We discuss these CO + OH → CO2 + H results within the context of inverse model approaches to ascertaining the global and regional source/sink patterns of CO2. Deficiencies in the model output as compared to observational data are discussed within the context of guiding future research.

Reply to Idso

We agree with Idso that CO2 fertilization of terrestrial ecosystems is of great importance in the understanding of the behaviour of the amplitude of the seasonal cycle of atmospheric CO2 as analyzed in our paper (Kohlmaier et al., 1989, henceforth called II). DOI: 10.1034/j.1600-0889.1991.t01-1-00008.x