Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, ...and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001–2015 was 0. 17 ± 0. 11 PgC yr−1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.
The decadal state of the terrestrial carbon cycle Bloom, A. Anthony; Exbrayat, Jean-François; van der Velde, Ivar R. ...
Proceedings of the National Academy of Sciences - PNAS,
02/2016, Volume:
113, Issue:
5
Journal Article
Peer reviewed
Open access
The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence ...times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%),where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types.
Record-high CO2 emissions from boreal fires in 2021 Zheng, Bo; Ciais, Philippe; Chevallier, Frederic ...
Science (American Association for the Advancement of Science),
03/2023, Volume:
379, Issue:
6635
Journal Article
Peer reviewed
Emission emergencyCarbon dioxide emissions from boreal forest fires have been increasing since at least the year 2000, reaching a new high in 2021, Zheng et al. report. Although boreal fires ...typically produce about 10% of global carbon dioxide emissions from wildfires, in 2021 they produced nearly one quarter of the total. This abnormally high total resulted from the concurrence of water deficits in North America and Eurasia, which was an unusual situation. The increasing number of extreme wildfires that is accompanying global warming presents a real challenge to global climate change mitigation efforts. —HJS
Southeast Australia experienced intensive and geographically extensive wildfires during the 2019-2020 summer season. The fires released substantial amounts of carbon dioxide into the atmosphere. ...However, existing emission estimates based on fire inventories are uncertain, and vary by up to a factor of four for this event. Here we constrain emission estimates with the help of satellite observations of carbon monoxide, an analytical Bayesian inversion and observed ratios between emitted carbon dioxide and carbon monoxide. We estimate emissions of carbon dioxide to be 715 teragrams (range 517-867) from November 2019 to January 2020. This is more than twice the estimate derived by five different fire inventories, and broadly consistent with estimates based on a bottom-up bootstrap analysis ofthis fire episode. Although fires occur regularly in the savannas in northern Australia, the recent episodes were extremely large in scale and intensity, burning unusually large areas of eucalyptus forest in the southeast. The fires were driven partly by climate change, making better-constrained emission estimates particularly important. This is because the build-up of atmospheric carbon dioxide may become increasingly dependent on fire-driven climate-carbon feedbacks, as highlighted by this event.
Understanding tropical rainforest carbon exchange and its response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate ...carbon feedbacks. Of particular importance for the global carbon budget is net biome exchange of CO2 with the atmosphere (NBE), which represents nonfire carbon fluxes into and out of biomass and soils. Subannual and sub-Basin Amazon NBE estimates have relied heavily on process-based biosphere models, despite lack of model agreement with plot-scale observations. We present a new analysis of airborne measurements that reveals monthly, regional-scale (Approx.1-8 x 10(exp -6) km2) NBE variations. We develop a regional atmospheric CO2 inversion that provides the first analysis of geographic and temporal variability in Amazon biosphere-atmosphere carbon exchange and that is minimally influenced by biosphere model-based first guesses of seasonal and annual mean fluxes. We find little evidence for a clear seasonal cycle in Amazon NBE but do find NBE sensitivity to aberrations from long-term mean climate. In particular, we observe increased NBE (more carbon emitted to the atmosphere) associated with heat and drought in 2010, and correlations between wet season NBE and precipitation (negative correlation) and temperature (positive correlation). In the eastern Amazon, pulses of increased NBE persisted through 2011, suggesting legacy effects of 2010 heat and drought. We also identify regional differences in postdrought NBE that appear related to long-term water availability. We examine satellite proxies and find evidence for higher gross primary productivity (GPP) during a pulse of increased carbon uptake in 2011, and lower GPP during a period of increased NBE in the 2010 dry season drought, but links between GPP and NBE changes are not conclusive. These results provide novel evidence of NBE sensitivity to short-term temperature and moisture extremes in the Amazon, where monthly and sub-Basin estimates have not been previously available.
The global fire emission inventories depend on ground and airborne measurements of species-specific emission factors (EFs), which translate dry matter losses due to fires to actual trace gas and ...aerosol emissions. The EFs of nitrogen oxides (NOx) and carbon monoxide (CO) can function as a proxy for combustion efficiency to distinguish flaming from smoldering combustion. The uncertainties in these EFs remain large as they are limited by the spatial and temporal representativeness of the measurements. The global coverage of satellite observations has the advantage of filling this gap, making these measurements highly complementary to ground-based or airborne data. We present a new analysis of biomass burning pollutants using space-borne data to investigate the spatiotemporal efficiency of fire combustion. Column measurements of nitrogen dioxide and carbon monoxide (XNO2 and XCO) from the TROPOspheric Monitoring Instrument (TROPOMI) are used to quantify the relative atmospheric enhancements of these species over different fire-prone regions around the world. We find spatial and temporal patterns in the ΔXNO2 / ΔXCO ratio that point to distinct differences in biomass burning behavior. Such differences are induced by the burning phase of the fire (e.g., high-temperature flaming vs. low-temperature smoldering combustion) and burning practice (e.g., the combustion of logs, coarse woody debris and soil organic matter vs. the combustion of fine fuels such as savanna grasses). The sampling techniques and the signal-to-noise ratio of the retrieved ΔXNO2 / ΔXCO signals were quantified with WRF-Chem experiments and showed similar distinct differences in combustion types. The TROPOMI measurements show that the fraction of surface smoldering combustion is much larger for the boreal forest fires in the upper Northern Hemisphere and peatland fires in Indonesia. These types of fires cause a much larger increase (3 to 6 times) in ΔXCO relative to ΔXNO2 than elsewhere in the world. The high spatial and temporal resolution of TROPOMI also enables the detection of spatial gradients in combustion efficiency at smaller regional scales. For instance, in the Amazon, we found higher combustion efficiency (up to 3-fold) for savanna fires than for the nearby tropical deforestation fires. Out of two investigated fire emission products, the TROPOMI measurements support the broad spatial pattern of combustion efficiency rooted in GFED4s. Meanwhile, TROPOMI data also add new insights into regional variability in combustion characteristics that are not well represented in the different emission inventories, which can help the fire modeling community to improve their representation of the spatiotemporal variability in EFs.
Record-high CO 2 emissions from boreal fires in 2021 Zheng, Bo; Ciais, Philippe; Chevallier, Frederic ...
Science (American Association for the Advancement of Science),
2023-Mar-03, 2023-03-03, Volume:
379, Issue:
6635
Journal Article
Peer reviewed
Open access
Extreme wildfires are becoming more common and increasingly affecting Earth's climate. Wildfires in boreal forests have attracted much less attention than those in tropical forests, although boreal ...forests are one of the most extensive biomes on Earth and are experiencing the fastest warming. We used a satellite-based atmospheric inversion system to monitor fire emissions in boreal forests. Wildfires are rapidly expanding into boreal forests with emerging warmer and drier fire seasons. Boreal fires, typically accounting for 10% of global fire carbon dioxide emissions, contributed 23% (0.48 billion metric tons of carbon) in 2021, by far the highest fraction since 2000. 2021 was an abnormal year because North American and Eurasian boreal forests synchronously experienced their greatest water deficit. Increasing numbers of extreme boreal fires and stronger climate-fire feedbacks challenge climate mitigation efforts.
We have implemented a regional carbon dioxide data assimilation system based
on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution
Lagrangian transport model, the Stochastic ...Time-Inverted Lagrangian
Transport model driven by the Weather Forecast and Research meteorological
fields (WRF-STILT). With this system, named CTDAS-Lagrange, we
simultaneously optimize terrestrial biosphere fluxes and four parameters
that adjust the lateral boundary conditions (BCs) against CO2
observations from the NOAA ESRL North America tall tower and aircraft
programmable flask packages (PFPs) sampling program. Least-squares
optimization is performed with a time-stepping ensemble Kalman smoother,
over a time window of 10 days and assimilating sequentially a time series of
observations. Because the WRF-STILT footprints are pre-computed, it is
computationally efficient to run the CTDAS-Lagrange system. To estimate the uncertainties in the optimized fluxes from the system, we
performed sensitivity tests with various a priori biosphere fluxes (SiBCASA,
SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and
CTE2014, and an empirical dataset derived from aircraft observations), as
well as with a variety of choices on the ways that fluxes are adjusted
(additive or multiplicative), covariance length scales, biosphere flux
covariances, BC parameter uncertainties, and model–data mismatches. In
pseudo-data experiments, we show that in our implementation the additive
flux adjustment method is more flexible in optimizing net ecosystem exchange (NEE) than the
multiplicative flux adjustment method, and our sensitivity tests with real
observations show that the CTDAS-Lagrange system has the ability to correct
for the potential biases in the lateral BCs and to resolve
large biases in the prior biosphere fluxes. Using real observations, we have derived a range of estimates for the
optimized carbon fluxes from a series of sensitivity tests, which places the
North American carbon sink for the year 2010 in a range from −0.92 to
−1.26 PgC yr−1. This is comparable to the TM5-based estimates of CarbonTracker
(version CT2016, -0.91±1.10 PgC yr−1) and CarbonTracker Europe
(version CTE2016, -0.91±0.31 PgC yr−1). We conclude that
CTDAS-Lagrange can offer a versatile and computationally attractive
alternative to these global systems for regional estimates of carbon fluxes,
which can take advantage of high-resolution Lagrangian footprints that are
increasingly easy to obtain.
The triple oxygen isotope signature Δ17O in atmospheric CO2, also known as its “17O excess,” has been proposed as a tracer for gross primary production (the gross uptake of CO2 by vegetation through ...photosynthesis). We present the first global 3‐D model simulations for Δ17O in atmospheric CO2 together with a detailed model description and sensitivity analyses. In our 3‐D model framework we include the stratospheric source of Δ17O in CO2 and the surface sinks from vegetation, soils, ocean, biomass burning, and fossil fuel combustion. The effect of oxidation of atmospheric CO on Δ17O in CO2 is also included in our model. We estimate that the global mean Δ17O (defined as
Δ17O=ln(δ17O+1)−λRL·ln(δ18O+1) with λRL = 0.5229) of CO2 in the lowest 500 m of the atmosphere is 39.6 per meg, which is ∼20 per meg lower than estimates from existing box models. We compare our model results with a measured stratospheric Δ17O in CO2 profile from Sodankylä (Finland), which shows good agreement. In addition, we compare our model results with tropospheric measurements of Δ17O in CO2 from Göttingen (Germany) and Taipei (Taiwan), which shows some agreement but we also find substantial discrepancies that are subsequently discussed. Finally, we show model results for Zotino (Russia), Mauna Loa (United States), Manaus (Brazil), and South Pole, which we propose as possible locations for future measurements of Δ17O in tropospheric CO2 that can help to further increase our understanding of the global budget of Δ17O in atmospheric CO2.
Key Points
This work presents a first view on possible spatial and temporal gradients of Δ17O in CO2 across the globe
Tropical, boreal, and Southern Hemisphere observations of Δ17O in CO2 could be of great interest
We implemented spatially and temporally explicit sources and sinks of Δ17O in CO2 in a 3‐D model framework
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