The European land and inland water CO2, CO, CH4 and N2O balance between 2001 and 2005

Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic greenhouse gas emissions over the period 2000–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balances of Europe following a dual constraint approach in which (1) a landbased balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are compared to (3) the atmospheric data-based balance derived from inversions constrained by measurements of atmospheric GHG (greenhouse gas) concentrations. Good agreement between the GHG balances based on fluxes (1294±545 Tg C in CO2-eq yr−1), inventories (1299±200 Tg C in CO2-eq yr−1) and inversions (1210±405 Tg C in CO2-eq yr−1) increases our confidence that the processes underlying the European GHG budget are well understood and reasonably sampled. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land to atmosphere exchanges are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The net land-to-atmosphere flux is a net source for CO2, CO, CH4 and N2O, because the anthropogenic emissions by far exceed the biogenic sink strength. The dual-constraint approach confirmed that the European biogenic sink removes as much as 205±72 Tg C yr−1 from fossil fuel burning from the atmosphere. However, This C is being sequestered in both terrestrial and inland aquatic ecosystems. If the C-cost for ecosystem management is taken into account, the net uptake of ecosystems is estimated to decrease by 45% but still indicates substantial C-sequestration. However, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.JRC.H.2-Air and Climat

Three decades of simulated global terrestrial carbon fluxes from a data assimilation system confronted with different periods of observations

During the last decade, carbon cycle data assimilation systems (CCDAS) have focused on improving the simulation of seasonal and mean global carbon fluxes over a few years by simultaneous assimilation of multiple data streams. However, the ability of a CCDAS to predict longer-term trends and variability of the global carbon cycle and the constraint provided by the observations have not yet been assessed. Here, we evaluate two near-decade-long assimilation experiments of the Max Planck Institute-Carbon Cycle Data Assimilation System (MPI-CCDAS v1) using spaceborne estimates of the fraction of absorbed photosynthetic active radiation (FAPAR) and atmospheric CO2 concentrations from the global network of flask measurement sites from either 1982 to 1990 or 1990 to 2000. We contrast these simulations with independent observations from the period 1982-2010, as well as a third MPI-CCDAS assimilation run using data from the full 1982-2010 period, and an atmospheric inversion covering the same data and time. With 30 years of data, MPI-CCDAS is capable of representing land uptake to a sufficient degree to make it compatible with the atmospheric CO2 record. The long-term trend and seasonal amplitude of atmospheric CO2 concentrations at station level over the period 1982 to 2010 is considerably improved after assimilating only the first decade (1982-1990) of observations. After 15-19 years of prognostic simulation, the simulated CO2 mixing ratio in 2007-2010 diverges by only 2 +/- 1.3 ppm from the observations, the atmospheric inversion, and the MPI-CCDAS assimilation run using observations from the full period. The long-term trend, phenological seasonality, and interannual variability (IAV) of FAPAR in the Northern Hemisphere over the last 1 to 2 decades after the assimilation were also improved. Despite imperfections in the representation of the IAV in atmospheric CO2, model-data fusion for a decade of data can already contribute to the prognostic capacity of land carbon cycle models at relevant timescales.Peer reviewe

Evaluation of model-data mismatch errors in the CarboScope-Regional Inversion System

&amp;lt;p&amp;gt;With an increasing network of atmospheric stations that produce a constant data stream, top-down inverse transport modelling of GHGs in a quasi-operational way becomes feasible. The CarboScope-Regional inversion system embeds the regional inversion, within a global inversion using the two-step approach. The regional inversion consists of Lagrangian mesoscale transport from STILT, prior fluxes from the diagnostic VPRM biosphere model, and anthropogenic emissions from a combination of EDGAR v4.3 with the annually updated BP statistical report. Regional ocean fluxes were derived from the CarboScope ocean flux product based on SOCATv2019 data. The inversion uses atmospheric observations from 44 stations to infer biosphere-atmosphere exchange. The regional domain covers most of Europe (33 &amp;amp;#8211; 73N, 15W &amp;amp;#8211; 35E) with a spatial resolution of 0.25 degree for fluxes and 0.5 degree for flux corrections inferred by the inversion (i.e. the state space).&amp;lt;br&amp;gt;One of the critical parameters is the assumed uncertainty of the observations, and the major contribution to this is the model-data mismatch error, or representation error. Within CarboScope-Regional, this model-data mismatch error is specified differently for different station types, such as tall towers, mountain or coastal stations, etc. To evaluate the validity and appropriateness of these assumed uncertainties, a leave-one-out cross-validation is applied for a single year, using all stations except one for the inversion, and comparing posterior concentrations predicted for the omitted station with the observed concentrations. Results of this cross-validation will be presented separately for the different station types, and will be used to evaluate the magnitude of the assumed model-data mismatch errors.&amp;lt;/p&amp;gt; </jats:p

The constraint of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; measurements made onboard passenger aircraft on surface-atmosphere fluxes: the impact of transport model errors in vertical mixing

Abstract. Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network with those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height as compared to the ground- based network. This highlights the benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-Service Aircraft for a Global Observing System) project in future, in constraining the regional carbon budget. Our results show that the regions tropical Africa and temperate Eurasia, that are under constrained by the existing surface based network, will benefit the most from these measurements, the reduction of posterior flux uncertainty being about 7 to 10 %. </jats:p

Coupling bottom-up process modeling to atmospheric inversions to constrain the Siberian methane budget

&amp;lt;p&amp;gt;Methane (CH4) is one of the most important greenhouse gases, but unexpected changes in atmospheric&amp;amp;#160;CH4 budgets over the past decades emphasize that many aspects regarding the role of this gas in the global climate system remain unexplained to date. With emissions and concentrations likely to continue increasing in the future, quantitative and qualitative insights into processes governing CH4 sources and sinks need to be improved in order to better predict feedbacks with a changing climate. Particularly the high northern latitudes have been identified as a potential future hotspot for global CH4 emissions, but the effective impact of rapid climate change on the mobilization of the enormous carbon reservoir currently stored in northern soils remains unclear.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Process-based modelling frameworks are the most promising tool for predicting CH4 emission trajectories under future climate scenarios. In order to improve the insights into CH4 emissions and their controls, the land-surface component of the Max Planck Earth System model, JSBACH, has been upgraded in recent years. In this context, a particular focus has been placed on refining important processes in permafrost landscapes, including freeze-thaw processes, high-resolution vertical gradients in transport and transformation of carbon in soils, and a dynamic coupling between carbon, water and energy cycles. Evaluating the performance of this model, however, remains a challenge because of the limited observational database for high Northern latitude regions.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In the presented study, we couple methane flux fields simulated by JSBACH to an atmospheric inversion scheme to evaluate model performance within the Siberian domain. Optimization of the surface-atmosphere exchange processes against an atmospheric methane mixing-ratio database will allow to identify the large-scale representativeness of JSBACH simulations, including its spatio-temporal variability in the chosen domain. We will test the impact of selected model parameter settings on the agreement between bottom-up and top-down techniques, therefore highlighting how sensitive regional scale methane budgets are to dominant processes and controls within this region.&amp;lt;/p&amp;gt; </jats:p

Comparing CO 2 retrieved from Atmospheric Infrared Sounder with model predictions: Implications for constraining surface fluxes and lower-to-upper troposphere transport

International audienc

Recent Warming Has Resulted in Smaller Gains in Net Carbon Uptake in Northern High Latitudes

International audienceCarbon balance of terrestrial ecosystems in the northern high latitudes (NHL) is sensitive to climate change. It remains uncertain whether current regional carbon uptake capacity can be sustained under future warming. Here the atmospheric CO2 drawdown rate (CDR) between 1974 and 2014, defined as the CO2 decrease in ppm over the number of days in spring or summer, is estimated using atmospheric CO2 observations at Barrow (now known as Utqiaġvik), Alaska. We found that the sensitivity of CDR to interannual seasonal air temperature anomalies has trended toward less carbon uptake for a given amount of warming over this period. Changes in interannual temperature sensitivity of CDR suggest that relatively warm springs now result in less of a carbon uptake enhancement. Similarly, relatively warm summers now result in greater carbon release. These results generally agree with the sensitivity of net carbon exchange (NCE) estimated by atmospheric CO2 inversion. When NCE was aggregated over North America (NA) and Eurasia (EA), separately, the temperature sensitivity of NCE in NA has changed more than in EA. To explore potential mechanisms of this signal, we also examine trends in interannual variability of other climate variables (soil temperature and precipitation), satellite-derived gross primary production (GPP), and Trends in Net Land–Atmosphere Carbon Exchanges (TRENDY) model ensemble results. Our analysis suggests that the weakened spring sensitivity of CDR may be related to the slowdown in seasonal soil thawing rate, while the summer sensitivity change may be caused by the temporally coincident decrease in temperature sensitivity of photosynthesis. This study suggests that the current NHL carbon sink may become unsustainable as temperatures warm further. We also found that current carbon cycle models do not represent the decrease in temperature sensitivity of net carbon flux. We argue that current carbon–climate models misrepresent important aspect of the carbon–climate feedback and bias the estimation of warming influence on NHL carbon balanc