Sönke Zaehle’s research while affiliated with Max Planck Institute for Biogeochemistry and other places

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Publications (218)


Soil nitrous oxide emissions across the northern high latitudes estimated by an ensemble of terrestrial biosphere models
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February 2025

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41 Reads

Environment International

Naiqing Pan

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Sönke Zaehle

Plant phenology evaluation of CRESCENDO land surface models. Part II: Trough, peak, and amplitude of growing season
  • Preprint
  • File available

January 2025

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16 Reads

Leaf area index is an important metric for characterising the structure of vegetation canopies and scaling up leaf and plant processes to assess their influence on regional and global climate. Earth observation estimates of leaf area index have increased in recent decades, providing a valuable resource for monitoring vegetation changes and evaluating their representation in land surface and earth system models. The study presented here uses satellite leaf area index products to quantify regional to global variations in the seasonal timing and value of the leaf area index trough, peak, and amplitude, and evaluate how well these variations are simulated by seven land surface models, which are the land components of state-of-the-art earth system models. Results show that the models simulate widespread delays, of up to three months, in the timing of leaf area index troughs and peaks compared to satellite products. These delays are most prominent across the Northern Hemisphere and support the findings of previous studies that have shown similar delays in the timing of spring leaf out simulated by some of these land surface models. The modelled seasonal amplitude differs by less than 1 m2/m2 compared to the satellite-derived amplitude across more than half of the vegetated land area. This study highlights the relevance of vegetation phenology as an indicator of climate, hydrology, soil, and plant interactions, and the need for further improvements in the modelling of phenology in land surface models in order to capture the correct seasonal cycles, and potentially also the long-term trends, of carbon, water and energy within global earth system models.

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Fire emissions in the Amazon and the Cerrado in 2020
a, Total DMB in 2020 and aboveground biomass (background map from grey = 0 to black = 40 kg m⁻²) from the TUD.S4F approach. The yellow polygon indicates the extent of the Amazon and Cerrado biomes, which were used to create the time series and aggregated statistics in c and the text. b, Uncertainty in DMB is defined as the normalized root mean squared difference across six EO-based estimates for the period August–October 2020. c, Time series of regional total cumulative DMB, CO and NOx emissions from different EO approaches (violet lines), three dynamic global vegetation–fire models (yellow), the TUD.S4F satellite data model fusion approach (red line, default model run) and the top-down constraint from KNMI.S5p (blue, default estimate). Red and blue bands show uncertainties for the TUD.S4F and KNMI.S5p approaches, respectively (Methods). Vertical dashed lines indicate the fire season for which totals are calculated. Results for different groups of approaches are summarized in Table 1 and for individual approaches in Extended Data Table 1.
Fire emissions for different fire types and fuels in the Amazon and the Cerrado in the period 1 August to 31 October 2020
a, Map of fire types in 2020 based on the GFA.S4F approach⁸. Savannah, savannah and grassland fires. Clearing, small agricultural fires in areas with >50% forest cover (for example, forest edges). Forest, understorey forest fires, and Deforest., fires clearing materials after deforestation. b, Regional DMB and CO and NOx emissions by fire type. Error bars for TUD.S4F and KNMI.S5p show uncertainty estimates around default estimates, whereas ‘all’ EO approaches display ranges across five (for DMB) and six (for CO and NOx) methods (Table 1 and Extended Data Table 1). c, Contribution of woody debris to DMB via TUD.S4F. d, Contribution of woody debris, litter, herbaceous vegetation and live biomass to DMB by fire type.
Evaluation of estimated surface woody debris and litter fuel loads
a–c, Comparison of woody debris and litter from three approaches: TUD-S4F (a), GFED500m¹⁷ (b) and L22.GEDI-based estimates²⁸ (c), available for the Cerrado biome only. Field measurements are from Leite et al. 2022 (L22)²⁸, van Wees et al. 2022 (W22)¹⁷ and Scaranello et al. 2019 (S19)²⁷. d, Comparison of the three approaches with field measurements in the Amazon and Cerrado and for the Cerrado alone. Numbers above boxes show RMSE (kg m⁻²) relative to field measurements. Boxplots display medians (lines), 0.25–0.75 quantiles (boxes), 1.5× interquartile range (IQR, whiskers) and outliers (beyond 1.5× IQR). e, Scatterplot of TUD.S4F surface fuel loads versus field measurements.
Variation of the EFCO and of combustion efficiency with fire types and woody debris
a, Map of EFCO averaged for the year 2020 from TUD.S4F with dynamic emission factors. A high EFCO indicates incomplete burning (smouldering combustion); whereas a low value indicates more complete burning (flaming combustion). b, Variability of EFCO for different fire types from the TUD.S4F approach and in comparison with field and laboratory values reported for tropical forests (For) and savannahs and grasslands (Sav) by Andreae 2019 (A19)²³. Horizontal lines are mean values, boxes are highest density intervals and grey points in A19 are individual reported values. c, Spatial patterns of woody debris from TUD.S4F for 2020. d,e, Emerging relationships between woody debris and the modified combustion efficiency (MCE) and EFCO, respectively.
Burning of woody debris dominates fire emissions in the Amazon and Cerrado

January 2025

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202 Reads

The Amazon forest is fire sensitive, but, where fires were uncommon as a natural disturbance, deforestation and drought are accelerating fire occurrences, which threaten the integrity of the tropical forest, the carbon cycle and air quality. Fire emissions depend on fuel amount and type, moisture conditions and burning behaviour. Higher-resolution satellite data have helped more accurately map global burnt areas; however, the effects of fuels on the combustion process and on the composition of fire emissions remain uncertain in current fire emissions inventories. By using multiple Earth observation-based approaches, here we show that total fire emissions in the Amazon and Cerrado biomes are dominated by smouldering combustion of woody debris. The representation of woody debris and surface litter presents a critical uncertainty in fire emissions inventories and global vegetation models. For the fire season 1 August to 31 October 2020, for which all approaches are available, we found 372277605Tg372^{605}_{277}\,\mathrm{Tg} (median and range across approaches) of dry matter burnt, corresponding to carbon monoxide emissions of 39.12759Tg39.1^{59}_{27}\,\mathrm{Tg}. Our results emphasize how Earth observation approaches for fuel and fire dynamics and of atmospheric trace gases reduce uncertainties of fire emission estimates. The findings enable diagnosing the representation of fuels, wildfire combustion and its effects on atmospheric composition and the carbon cycle in global vegetation–fire models.


Reduced vegetation uptake during the extreme 2023 drought turns the Amazon into a weak carbon source

January 2025

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110 Reads

In 2023, the biogeographic Amazon experienced temperature anomalies of 1.5°C above the 1991-2020 average from September to November. These conditions were driven by high sea surface temperature in the Atlantic and Pacific oceans, together with reduced moisture advection from the Atlantic, causing large vapor pressure and water deficits in the second semester of 2023. Here, we evaluate the response of the Amazon carbon cycle to this extreme event across different spatial scales. We combined atmospheric CO2 mole fractions and eddy covariance flux data from the Amazon Tall Tower Observatory (ATTO), near-real- time simulations by Dynamic Global Vegetation Models (DGVMs), an atmospheric inversion, and remote sensing data. We find that in 2023 the Amazon region was, including fires, a net carbon source of 0.01 to 0.17 PgC. Fire emissions (0.15 [0.13-0.17] PgC) were within typical variability of the 2003-2023 period, thus we attribute the weak carbon source to reduced vegetation uptake during the dry season. A stronger-than-normal vegetation uptake early in the year (January to April), consistent across data streams and spatial scales, mitigated the total carbon losses by the end of the year. We find a shift from carbon sink to source in May and a peak source in October. Our findings show a reduced vegetation carbon uptake over the Amazon region, leading to a weak carbon source that contributed 30% of the net carbon loss in the tropical land in 2023.


Air temperature and precipitation constraining the modelled wetland methane emissions in a boreal region in northern Europe

January 2025

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47 Reads

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1 Citation

Wetland methane responses to temperature and precipitation are studied in a boreal wetland-rich region in northern Europe using ecosystem process models. Six ecosystem models (JSBACH-HIMMELI, LPX-Bern, LPJ-GUESS, JULES, CLM4.5, and CLM5) are compared to multi-model means of ecosystem models and atmospheric inversions from the Global Carbon Project and upscaled eddy covariance flux results for their temperature and precipitation responses and seasonal cycles of the regional fluxes. Two models with contrasting response patterns, LPX-Bern and JSBACH-HIMMELI, are used as priors in atmospheric inversions with Carbon Tracker Europe–CH4 (CTE-CH4) in order to find out how the assimilation of atmospheric concentration data changes the flux estimates and how this alters the interpretation of the flux responses to temperature and precipitation. Inversion moves wetland emissions of both models towards co-limitation by temperature and precipitation. Between 2000 and 2018, periods of high temperature and/or high precipitation often resulted in increased emissions. However, the dry summer of 2018 did not result in increased emissions despite the high temperatures. The process models show strong temperature and strong precipitation responses for the region (51 %–91 % of the variance explained by both). The month with the highest emissions varies from May to September among the models. However, multi-model means, inversions, and upscaled eddy covariance flux observations agree on the month of maximum emissions and are co-limited by temperature and precipitation. The setup of different emission components (peatland emissions, mineral land fluxes) has an important role in building up the response patterns. Considering the significant differences among the models, it is essential to pay more attention to the regional representation of wet and dry mineral soils and periodic flooding which contribute to the seasonality and magnitude of methane fluxes. The realistic representation of temperature dependence of the peat soil fluxes is also important. Furthermore, it is important to use process-based descriptions for both mineral and peat soil fluxes to simulate the flux responses to climate drivers.


Net seasonal atmosphere-to-surface fluxes. Fluxes are for (a, c, e) carbon and (b, d, f) the δ13C-weighted carbon flux, δ13fas,net* (see Sect. ), from the standard simulation (Estandard) and are averaged over 1982–2012 for (a, b) June, July, and August (JJA); (c, d) December, January, and February (DJF); and (e, f) JJA minus DJF. Note the non-linear color bars with blue colors in panels (a) to (d) indicating a lowering in atmospheric CO2 and δ13C.
The simulated (red) seasonal cycle of atmospheric Ca (left, a, d, g) and its signature δ13Ca (middle, b, e, h) compared to observations (black dots). In the rightmost panels (c, f, i) the seasonal anomalies (Δ) of Ca are plotted against those of δ13Ca, with lines connecting the monthly values (dots) fading from January to December. Results are for Alert, northern Canada (a, b, c); Mauna Loa, Hawaii (d, e, f); and the South Pole (g, h, i). Simulated values are from transporting net TM3 fluxes of the Bern3D-LPX Estandard simulation from all (red, Estandard), terrestrial (green, dashed), oceanic (blue, dashed), and fossil fuel sources (brown, dashed). The observational and model anomalies are computed from monthly values between 1982 and 2012 if both the measurements and transport matrices are available. Error bars and shading correspond to the standard deviation from the interannual variability in monthly values.
Temporal evolution of δ13Ca (a) and its seasonal amplitude (b) from data of the Scripps network . Gap-filled data provided by Scripps are used for the eight sites. The slope and its standard error from a linear regression through the seasonal amplitude data (dotted) are given in ‰ per century. Trends are not different from zero based on a two-sided t test and a significance level of 5 %, except at Christmas Island (CHR) and the South Pole (SPO). Sites are ordered according to latitude (Alert (ALT, 82° N), Nuvuk (formerly Point Barrow) (PTB, 71° N), La Jolla (LJO, 33° N), Mauna Loa Observatory (MLO, 20° N), Cape Kumukahi (KUM, 20° N), Christmas Island (CHR, 2° N), Samoa (SAM, 14° S), and the South Pole (SPO, 90° S)).
The seasonal amplitude per 2.5° latitude band of the signature-weighted, detrended net atmosphere–land flux, δ13fal,net*, in the period of 1982–2012 is shown in (a) in red (see Eq. ). This quantity is the sum of three constituent seasonal amplitudes (Eq. and Appendix ): net land–atmosphere flux weighted with photosynthetic fractionation (fal,net⋅εNPP, green) plus release fluxes weighted with the disequilibrium signature (R⋅δdis,la, blue) plus the contribution to the seasonal amplitude by the underlying trend of δ13fal,net* (Δtrend, orange) (sign convention – green + blue + orange = red). In (b), the seasonal amplitudes of (non-detrended) net carbon fluxes are shown. The net atmosphere–land flux (fal,net, red) is split into net primary productivity (NPP, olive) and release flux (R, blue). In (c) the corresponding fractionation of photosynthesis εNPP and the disequilibrium signature δdis,la are shown. All values are for the period with δ13fal,net* smaller than zero (∼ growing season). The results from the standard simulation (Estandard, solid lines) are compared to the preindustrial control simulation (Econtrol, dashed lines).
No increase is detected and modeled for the seasonal cycle amplitude of δ13C of atmospheric carbon dioxide

January 2025

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27 Reads

Measurements of the seasonal cycle of δ13C of atmospheric CO2 (δ13Ca) provide information on the global carbon cycle and the regulation of carbon and water fluxes by leaf stomatal openings on ecosystem and decadal scales. Land biosphere carbon exchange is the primary driver of δ13Ca seasonality in the Northern Hemisphere (NH). We use isotope-enabled simulations of the Bern3D-LPX (Land surface Processes and eXchanges) Earth system model of intermediate complexity and fossil fuel emission estimates with a model of atmospheric transport to simulate atmospheric δ13Ca at globally distributed monitoring sites. Unlike the observed growth of the seasonal amplitude of CO2 at northern sites, no significant temporal trend in the seasonal amplitude of δ13Ca was detected at most sites, consistent with the insignificant model trends. Comparing the preindustrial (1700) and modern (1982–2012) periods, the modeled small-amplitude changes at northern sites are linked to the near-equal increase in background atmospheric CO2 and the seasonal signal of the net atmosphere–land δ13C flux in the northern extratropical region, with no long-term temporal changes in the isotopic fractionation in these ecosystems dominated by C3 plants. The good data–model agreement in the seasonal amplitude of δ13Ca and in its decadal trend provides implicit support for the regulation of stomatal conductance by C3 plants towards intrinsic water use efficiency growing proportionally to atmospheric CO2 over recent decades. Disequilibrium fluxes contribute little to the seasonal amplitude of the net land isotope flux north of 40° N but contribute near equally to the isotopic flux associated with growing season net carbon uptake in tropical and Southern Hemisphere (SH) ecosystems, pointing to the importance of monitoring δ13Ca over these ecosystems. We propose applying seasonally resolved δ13Ca observations as an additional constraint for land biosphere models and underlying processes for improved projections of the anthropogenic carbon sink.


Representation of the terrestrial carbon cycle in CMIP6

November 2024

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170 Reads

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3 Citations

Simulation of the carbon cycle in climate models is important due to its impact on climate change, but many weaknesses in its reproduction were found in previous models. Improvements in the representation of the land carbon cycle in Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) include the interactive treatment of both the carbon and nitrogen cycles, improved photosynthesis, and soil hydrology. To assess the impact of these model developments on aspects of the global carbon cycle, the Earth System Model Evaluation Tool (ESMValTool) is expanded to compare CO2-concentration- and CO2-emission-driven historical simulations from CMIP5 and CMIP6 to observational data sets. A particular focus is on the differences in models with and without an interactive terrestrial nitrogen cycle. Overestimations of photosynthesis (gross primary productivity (GPP)) in CMIP5 were largely resolved in CMIP6 for participating models with an interactive nitrogen cycle but remaining for models without one. This points to the importance of including nutrient limitation. Simulating the leaf area index (LAI) remains challenging, with a large model spread in both CMIP5 and CMIP6. In ESMs, the global mean land carbon uptake (net biome productivity (NBP)) is well reproduced in the CMIP5 and CMIP6 multi-model means. However, this is the result of an underestimation of NBP in the Northern Hemisphere, which is compensated by an overestimation in the Southern Hemisphere and the tropics. Carbon stocks remain a large uncertainty in the models. While vegetation carbon content is slightly better represented in CMIP6, the inter-model range of soil carbon content remains the same between CMIP5 and CMIP6. Overall, a slight improvement in the simulation of land carbon cycle parameters is found in CMIP6 compared to CMIP5, but with many biases remaining, further improvements of models in particular for LAI and NBP is required. Models from modeling groups participating in both CMIP phases generally perform similarly or better in their CMIP6 compared to their CMIP5 models. This improvement is not as significant in the multi-model means due to more new models in CMIP6, especially those using older versions of the Community Land Model (CLM). Emission-driven simulations perform just as well as the concentration-driven models, despite the added process realism. Due to this, we recommend that ESMs in future Coupled Model Intercomparison Project (CMIP) phases perform emission-driven simulations as the standard so that climate–carbon cycle feedbacks are fully active. The inclusion of the nitrogen limitation led to a large improvement in photosynthesis compared to models not including this process, suggesting the need to view the nitrogen cycle as a necessary part of all future carbon cycle models. Possible benefits when including further limiting nutrients such as phosphorus should also be considered.


The need for carbon-emissions-driven climate projections in CMIP7

November 2024

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347 Reads

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11 Citations

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), for both idealized model experiments and climate projections of different emissions scenarios. We argue that although this approach was practical to allow parallel development of Earth system model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth system models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy, and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently calculated in integrated assessment models (IAMs) during scenario development with only the net carbon emissions passed to the ESM. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use and projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon–climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular, sources and sinks of methane and nitrous oxide) and process-based representation of carbon removal options. These developments will allow three primary benefits: (1) resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts, (2) scenario modeling of the range of possible future climate states including Earth system processes and feedbacks that are increasingly well-represented in ESMs, and (3) optimal utilization of the strengths of ESMs in the wider context of climate modeling infrastructure (which includes simple climate models, machine learning approaches and kilometer-scale climate models).


Large discrepancy in northern carbon sink between bottom-up and top-down estimates can be explained by disturbance processes
a Mean net carbon flux for North America, Europe, Russia, and China combined for dynamic global vegetation models (DGVMs) (grey), atmospheric inversions (purple), and the two demography-enabled DGVMs; CABLE-POP (green) and LPJ-GUESS (orange). Positive values are a net uptake by land. Dashed lines show mean values over the study period and shading represents 1σ model spread. b Wildfire carbon emissions for the four regions as estimated by the DGVMs (grey), and by two remote-sensing products; GFAS (red) and GFED4.1 s (orange). c Net ecosystem production (NEP) estimates from DGVMs (grey) and upscaled eddy covariance data (EC-Age), which has been adjusted for tree age (blue). The NEP fluxes are partitioned into forest age classes. Here we show gridbox mean NEP for the DGVMs, which includes non-forest fluxes. However, in general, forest NEP has a dominant control on gridbox NEP in the regions considered in this study (Supplementary Fig. 1).
Satellite-derived regrowth curves for northern forests
a–d Panels show the effect of forest age (years) on aboveground biomass (MgC ha⁻¹ yr⁻¹) in a subset of the four regions; a Boreal Eurasia, b North America, c Temperate Europe, and d China. Points indicate the 25th, 50th, and 75th percentile of satellite-based biomass values across all pixels for each year. Best fit lines (dashed and shading) are shown and are used to calculate annual growth increment. e–h Panels depict the annual growth increment for the four regions. Dashed lines and shading represent the 25th, 50th, and 75th percentile estimates. The solid green horizontal line is the mean growth for the first 30 years. The black point and range show in situ observations (ref. ³⁷) of growth rates for trees younger than 30 years. Note, we have truncated the y-axis in (h), the upper limit for in situ growth rates in China is 4.9 MgC ha⁻¹ yr⁻¹.
Substantial regional carbon uptake due to forest regrowth over the last two decades
Maps depict the cumulative carbon sink due to forest regrowth over 2001–2021 based on satellite-derived regrowth curves (MgC ha⁻¹). For each pixel, the growth depends on regional growth curves (Fig. 2) and the inferred forest age²⁵ starting in 2001. Each year, the forest age increases and a new growth value is calculated. In the years 2010–2021, the age of a pixel is set to 1 if disturbance is detected. Non-forest pixels are removed from the analysis.
Reconciliation and attribution of the northern land carbon sink
a Mean carbon flux over the period 2001–2021 for individual components, for all four regions combined. The carbon sink from rising atmospheric CO2, nitrogen deposition, and climate change is estimated by the DGVMs (only using fire-enabled DGVMs) from the S2 simulation (grey bar). NEP for non-fire-enabled DGVMs is shown as a cross. Land-use and land cover change gross losses (including peat drainage) are estimated from three bookkeeping models, BLUE, OSCAR, and HN (orange bar). Fire carbon losses are estimated by two satellite-derived products; GFAS and GFED4.1s, for the period 2003–2021 (red bar). The forest regrowth carbon flux is estimated from this study (green). The sum of the four components (DGVM NEP, Regrowth, LULCC losses, and fire losses) represents our new estimate of the net land sink (light blue bar). The cross on top of the blue bar shows the sum of four components but with NEP from the non-fire enabled models. The net land sink as estimated by atmospheric inversions is also shown (purple). b, c Annual mean carbon fluxes for b the four component fluxes; NEP (fire-enabled DGVMs only), Regrowth, LULCC losses, and fire losses (positive values mean flux from atmosphere to land), and c the sum of the four components (blue), and the net land sink as estimated by the inversions (purple). Shading in all panels represents 1σ uncertainty across the models or inversion datasets, respectively.
The key role of forest disturbance in reconciling estimates of the northern carbon sink

November 2024

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553 Reads

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2 Citations

Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr⁻¹ over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr⁻¹). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr⁻¹, and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr⁻¹), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr⁻¹), and the DGVM-estimated sink from CO2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr⁻¹). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr⁻¹ agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.


Global Carbon Budget 2024

November 2024

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1,113 Reads

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9 Citations

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC) are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements and Earth System Models. The sum of all sources and sinks results in the carbon budget imbalance (BIM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2023, EFOS increased by 1.3 % relative to 2022, with fossil emissions at 10.1 ± 0.5 GtC yr-1 (10.3 ± 0.5 GtC yr-1 when the cement carbonation sink is not included), ELUC was 1.0 ± 0.7 GtC yr-1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.9 GtC yr-1 (40.6 ± 3.2 GtCO2 yr-1). Also, for 2023, GATM was 5.9 ± 0.2 GtC yr-1 (2.79 ± 0.1 ppm yr-1), SOCEAN was 2.9 ± 0.4 GtC yr-1 and SLAND was 2.3 ± 1.0 GtC yr-1, with a near zero BIM (-0.02 GtC yr-1). The global atmospheric CO2 concentration averaged over 2023 reached 419.3 ± 0.1 ppm. Preliminary data for 2024, suggest an increase in EFOS relative to 2023 of +0.8 % (-0.3 % to 1.9 %) globally, and atmospheric CO2 concentration increased by 2.8 ppm reaching 422.5 ppm, 52 % above pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2023, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2024 (Friedlingstein et al., 2024).


Citations (58)


... One explanation may be a rudimentary representation of biogeochemical constraints on land carbon uptake in ESMs, which are only included in some of the models contributing to the CMIP6 linear feedback experiments (Table S2) and are notoriously difficult to represent in large ESMs (Knox et al., 2024). Some models contributed to the CMIP6 linear feedback analysis have nitrogen dynamics, but only one has phosphorus dynamics (ACCESS-ESM 1.5, Arora et al., 2020, Table S2), which are integral to modeling tropical forest land carbon dynamics, especially in high-biomass wildland tropical forests subject to nutrient limitation (Fleischer & Terrer, 2022;Gier et al., 2024;Yang et al., 2014). A second explanation may be the ability of ESMs to capture the range of soil variability present in wildland tropical forests, and its effect on water and carbon flux from the soil and plants to the atmosphere. ...

Reference:

Anthromes and forest carbon responses to global change
Representation of the terrestrial carbon cycle in CMIP6

... As self-consistent representation of physics, biology, and chemistry on weather to climate time scales, each ESM contributing to past phases of CMIP has represented one combination of choices along the many dimensions of the multiverse of models 55 ( Figure 1). In particular, in addition to representing water and energy cycles and associated dynamics as in physical climate models, ESMs broaden the focus to questions in which the coupling between chemistry and/or the carbon cycle and the physical climate system plays a key role, for example exploring interactions between anthropogenic emissions and climate as mediated by biogeochemical cycles (Sanderson et al., 2024). ...

The need for carbon-emissions-driven climate projections in CMIP7

... By contrast, more than half of the carbon in plant litter is released into the atmosphere during decomposition ( 2 , 4 ). Therefore, litter decomposition rate (k ) not only reflects the turnover time of carbon and nutrients between plant and soil ecosystems, but also serves as a critical parameter for evaluating the atmospheric carbon budget ( 5 ). Although considerable studies have evaluated litter decomposition spanning multiple climatic zones in recent years ( 6 -8 ), the global patterns of litter decomposition rates remain elusive. ...

Global Carbon Budget 2024

... Extensive research shows that nutrient resorption exhibits geographical patterns, e.g., latitudinal and elevational patterns, both of which are expected to be influenced by abiotic and biotic factors (Guo et al. 2024;Hu et al. 2023;Sophia et al. 2024). For instance, Yuan and Chen (2009) observed that at a global scale, NRE increased with latitude due to the decline in MAT and MAP, while PRE decreased with latitude. ...

Leaf habit drives leaf nutrient resorption globally alongside nutrient availability and climate

... Still, some mismatches with reference data remain, such as an overestimation of BNF in the tropics (Fig. 3c). However, the ensemble mean of a recent study evaluating the N cycle of 11 DGVMs shows a similar overestimation in the tropics and a large bias, indicating little agreement between models (Kou-Giesbrecht et al., 2023). They attributed this to the fact that BNF is typically modelled as a function of vegetation activity expressed either through NPP or evapotranspiration. ...

Evaluating nitrogen cycling in terrestrial biosphere models: a disconnect between the carbon and nitrogen cycles

... We use global fire emissions in the 2000s and the 2050s predicted by a fire model that accounts for the interactions between fire, climate, and ecosystem 27,28 . We then apply projected fire emissions to a group of global atmospheric chemistry models which simulates the sensitivity of global OH concentrations to NOx and RCS emissions (Methods and Supplementary Table 1) 25,[29][30][31] . Based on these model results, we calculate the response of global mean OH concentration to projected increases in fires, evaluate its impact on the global methane burden and radiative forcing, and compare the strength of this feedback mechanism with other well-established climate feedback. ...

Global net climate effects of anthropogenic reactive nitrogen

Nature

... Comparison of the observed terrestrial C balance trend in recent decades and the trends simulated by a recent generation of DGVMs corroborates this picture (Fig. 1). These models were used for the model intercomparison activity Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide (TRENDY) (Sitch et al., 2024) v.8, and for the quantification of the Global Carbon Budget . The spread across individual models is much larger for C-N models than for C-only models, both for the mean terrestrial sink between 2011 and 2020 (Fig. 1b) and for the mean trend between 1959 and 2020 (Fig. 1c). ...

Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project

... The omission of the phosphorus cycle in our simulations could have led to an overestimation of carbon uptake. The phosphorus cycle representations in GCMs and TBMs remain an active area of model development (Jiang et al., 2024) and constitute a limitation to the reliability of future carbon cycle projections over Australia. ...

Carbon-phosphorus cycle models overestimate CO2 enrichment response in a mature Eucalyptus forest
  • Citing Article
  • July 2024

Science Advances

... A recently published work simulated global maps of three leaf traits via optimality models based on eco-evolutionary optimality theory 35 . However, the various published global trait maps do not always show consistent global patterns, reflecting differences in data sources and upscaling methods 35,36 . ...

Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches

Remote Sensing of Environment

... The ocean contributes 30%-40% of natural Nitrous Oxide (N 2 O) sources to the atmosphere (Tian et al., 2023) with global N 2 O sea-air fluxes of 5.5-6.6 Tg N 2 O yr 1 (Bange et al., 2024;Yang et al., 2020). Obtaining accurate global estimates remains challenging due to a lack of data, sparse sampling efforts in many coastal and ocean regions, methodological inconsistencies to estimate gas transfer velocities (kω), and the large natural variability in processes regulating N 2 O production and consumption (Fay et al., 2021;Woolf et al., 2016). ...

Global nitrous oxide budget (1980–2020)