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Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Thawing Arctic permafrost has been assigned increasing importance as a key element in the global climate system over the past decades. One quarter of land surface of the northern hemisphere are permafrost regions, containing about 50% of the global below-ground carbon pool. Permafrost degradation and the associated climate feedback pose a potential tipping element that might be reached even within 1.5 °C global warming. Besides the potential release of additional carbon, permafrost degradation also holds the potential to significantly alter the surface characteristics of affected landscapes, resulting in further feedback processes that are poorly understood so far.In the presented study, we investigate the impact of permafrost degradation onto the structure of the atmospheric boundary layer (ABL) as a first feedback link to the global circulation. High-resolution Large Eddy Simulations (LES) are used to quantify the role of surface heterogeneity as a particular driver for boundary layer characteristics. Our virtual experiments simulate the structural changes of the ABL linked to long-term enhanced permafrost thaw, including e.g. the formation of new ponds and lakes, or increased spatial heterogeneity in vegetation structure with the establishment of different grass and shrubs species. Such changes may result in shifted fingerprints of heat and momentum fluxes into the atmosphere. Through this connection, ongoing climate change may lead to permanently altered influences of thawed permafrost on temperature and moisture profiles within the Arctic atmosphere, including changes in the boundary layer height. A particular focus of our study will be placed on the potential loss of water being drained away from the ecosystem after permafrost degradation, where the dried out soil not only changes the carbon cycle processes but also exhibits new surface characteristics. We quantify how the ABL reacts to those changes in idealized LES experiments, and investigate how atmospheric changes may further affect permafrost degradation.

In the context of global climate change, permafrost thaw in northern high-latitude territories is becoming a major concern due to the vast amount of organic carbon that is stored within this region. To accurately predict the feedback between Arctic permafrost carbon pools and future climate change, detailed insight into current carbon cycle processes and their environmental controls is imperative. A highly valuable data source for this purpose are continuous observations of turbulent exchange fluxes of carbon (e.g. CO2 and CH4 fluxes) and energy (e.g. fluxes of sensible and latent heat) with the eddy-covariance technique, in combination with the monitoring of environmental parameters such as e.g. air or soil temperature and moisture, radiation, atmospheric turbulence, water table levels, precipitation, and snow depth.In this study, we evaluate the effect of drainage on vertical carbon fluxes and environmental parameters within a Northeast Siberian wet tundra permafrost ecosystem. Our experiment includes two co-located eddy-covariance sites, one reflecting disturbed conditions affected by a drainage system which was built in 2004, and the other as an undisturbed control site. Both towers were identically outfitted with eddy covariance instruments mounted on 5 m tall towers on the floodplain of the Kolyma River near Chersky (68.75 º N, 161.33º E) in Northeast Siberia, Russia. The dataset analyzed here covers the period from July 2013 to December 2021, including continuous coverage throughout the winter seasons. We present a statistical analysis of the long-term trends in the environmental parameters and surface-atmosphere exchange fluxes at both sites. In addition, we relate the carbon and heat fluxes at both sites in the spectral and temporal domain to the inter-annual variability in climate conditions, which include extremes in both summer (temperature, precipitation) and winter (snow cover) conditions. Finally, we show the annual carbon budget of both sites, with a specific focus on the long-term impact of the drainage on carbon cycle process.

Climate warming can influence a variety of landscape processes, including the transformation and transfer of water, carbon and nutrients. In the Northern Hemisphere, permafrost underlays large parts of the land surface and represents a large reservoir of organic carbon that is extremely vulnerable to changing climate conditions. Accelerated thaw can decompose permafrost carbon, and lead to modified exchange processes with the atmosphere (vertical pathway) and hydrosphere (lateral pathways). These carbon export rates are highly dependent on soil water conditions, suprapermafrost groundwater table location, and vegetation community. Depending on depth of thaw and dry or wet soil conditions, changes in the production and availability patterns of dissolved organic carbon (DOC), particulate organic carbon (POC) and dissolved inorganic carbon (DIC), the three main carbon components in water, are expected. Shifts in lateral carbon export become more relevant for quantifying the total local carbon budget with predicted future permafrost degradation due to climate warming and resulting drier soil conditions. This study focuses on carbon distribution patterns of the three main carbon components (DOC, POC, DIC) within a floodplain tundra site near Chersky, Northeast Siberia. We compared a wet control site with a dry site affected by a drainage ring built in 2004. A network of piezometers was established to continuously monitor water table trends during the summer season (July to September) in 2017. On several key locations within that network, water was sampled to determine carbon concentrations (DOC, POC, DIC) and carbon isotopes (∆14C-DOC, δ13C-DOC, δ13C-DIC) in 2017. Here, we analyze and discuss the spatio-temporal carbon distribution on both sites with linkages to hydrological conditions (e.g. saturated zone) and carbon isotopic observations. The highest concentrations throughout both sites were found for DOC, followed by DIC and POC. DIC is relatively higher at wet sites compared to dry sites. Reversely, the organic carbon components, DOC and POC, were higher at dry sites. ∆14C-DOC can be associated with fresh material and decreased at all measurement sites with time of the season. Within that range, ∆14C-DOC decreased more at dry sites, when thaw depths were deepest within that site and where water tables were lower compared to wet sites, indicating the release of older carbon. Our results show that the distribution of carbon and the respective carbon isotopes are directly related to hydrological flow patterns. Understanding the carbon redistribution processes in these ecosystems is of relevance for assessing the carbon budget in disturbed permafrost areas. These findings will therefore be used to compare climate warming induced permafrost degradation at the dry (drained) site with the wet (control) site.

Changes in the net carbon sink of boreal forests constitute a major source of uncertainty in the future global carbon budget and hence climate change projections1. The annual net ecosystem exchange of carbon dioxide (CO2) controlling the terrestrial carbon stock is the result of the small difference between respiratory CO2 release and the photosynthetic CO2 uptake by vegetation2. The boreal forest, and the boreal biome in general, is regarded as a persistent and even an increasing net carbon sink3,4. However, decreases in photosynthetic CO2 uptake and/or concurrent increases in respiratory CO2 release under a changing climate may turn boreal forests from a net sink to a net source of CO21. Here, we assessed the dynamics of boreal forest net CO2 sink-source strength and its components from 1981 to 2018. Our remote sensing approach - trained by net CO2 flux observations at eddy covariance sites across the circumpolar boreal forests - employs satellite-derived retrievals of snow melt timing, landscape freeze-thaw status, and yearly maximum estimates of the normalized difference vegetation index as a proxy for peak vegetation productivity. Our results for the period 1981-2018 suggest that the mean annual evergreen boreal forest CO2 sink was 0.4 Pg C y-1 (0.3 Pg C y-1 for Eurasia and 0.2 Pg C y-1 for North America). In contrast to earlier investigations3,4 our results do not indicate an increasing trend in the circumpolar evergreen boreal forest CO2 sink, as the increase in CO2 uptake is compensated by increasing respiratory releases with both components of CO2 sink-source strength showing considerable interannual variabilities.

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Winter CO2 fluxes in Central Siberian ecosystems have been measured using different methodological approaches: dynamic chamber measurements at the soil surface under snowpack (Fsoil) and at the upper snowpack surface (Fsnow), static estimates based on measured CO2 concentrations and conductance properties of the snowpack (Fdiff), and calculations of CO2 efflux rates based on the eddy covariance technique (Fec). The results of measurements are analyzed and discussed with respect to the significance of differences between them and the applicability and limitations of the corresponding methods. The data are presented on winter CO2 efflux rates in five major ecosystem types of Central Siberia: lichen pine forest, lichen–moss pine forest, mixed forest, dark conifer forest, and raised pine bog.

Short summary We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

Decreasing trends of Arctic Seas ice areas, recorded growth of sea surface temperatures, and the increasing influx of Atlantic water into the Arctic Ocean demonstrate progressing warming. According to the current knowledge, the Kara Sea is characterized by a presence of subsea permafrost only in the nearshore area west of the Yamal peninsula. Limited summertime data on dissolved methane (CH4) dynamics indicate its low-moderate values in the shallow zone. In contrast to the deep subsea locations where CH4 is mostly oxidized in the water column, an essential part of CH4 that is released at the seafloor in the shallow Kara Sea emits into the atmosphere. Hence, accurate stationery and mobile observations of atmospheric methane over the above-sea layer might capture a portion of CH4 signals that are related to specific patches of such emissions. This study was accomplished during/after fall convection which fully mixed the shallow water column characterized by the near background concentration of dissolved CH4. Then to explain the “empty” dissolved CH4 pool we suggested effective extraction of dissolved methane into the atmosphere during fall water mixing. Such a “dissolved methane ventilation phenomenon” caused by wind-driven mixing has been discovered in the shallow part of the Laptev Sea.Accurate continuous observations of atmospheric CH4 dry mole fractions and δ13C-CH4 were made during the beginning of the freeze-up period - on October, 02 – November, 05 2021 onboard the research vessel "Academician Mstislav Keldysh" (AMK-86). Atmospheric measurements at 15 m of the above-sea layer were performed by a CRDS analyzer Picarro G2201-I (Picarro Inc., USA) that passed a regular calibration against WMO-traceable reference gases. Associated meteorological and geospatial records permitted screening and interpreting trace gas data series. Additionally, analysis of specific source regions of atmospheric air parcels moving downwind to the research vessel was based on the ARL NOAA HYSPLIT model. Here we give an overview of CH4 and δ13C-CH4 fluctuations over the above-sea layer of the Kara Sea observed within longitudinal (60 – 84о E) and latitudinal (70 – 82о N) transects, summarize spatial features, and provide analysis of source regions contributed into the accurate continuous measurements. This study was funded by the Russian Foundation for Basic Research, Krasnoyarsk Territory, and Krasnoyarsk Regional Fund of Science, project number 20-45-242908, Russian Science Foundation (RSF) project 21-17-00163, and by the Max Planck Society (Germany). Fieldwork was funded by the RSF project 21-77-30001. IS and DK acknowledge the Ministry of Science and High Education (grant ID: 075-15-2020-928).

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014–2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal (urn:x-wiley:13541013:media:gcb15905:gcb15905-math-1802) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between urn:x-wiley:13541013:media:gcb15905:gcb15905-math-0001 and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of urn:x-wiley:13541013:media:gcb15905:gcb15905-math-0002. In addition, we present how the 2015–2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of urn:x-wiley:13541013:media:gcb15905:gcb15905-math-0004 together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET). ISSN:0168-1923 ISSN:1873-2240

High-quality atmospheric CO

The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for sustainable development in the Artic-boreal region. Air quality in China and long-range transport of the atmospheric pollutants was also indicated as one of the most crucial topics of the research agenda. This paper summarizes results obtained during the last five years in the Northern Eurasian region. It also introduces recent observations on the air quality in the urban environments in China. The main regions of interest are the Russian Arctic, Northern Eurasian boreal forests (Siberia) and peatlands and on the mega cities in China. We frame our analysis against research themes introduced in 2015. We summarize recent progress in the understanding of the land – atmosphere – ocean systems feedbacks. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, such as enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate the climate change and the socio-economic development to tackle air quality issues.

A crucial issue in atmospheric studies on greenhouse gas content involves assessing the representativeness (footprint) having influence on their concentrations measured by tall towers. In this study, the Stochastic Time-Inverted Lagrangian Transport (STILT) model was used to estimate seasonal cumulative footprint climatology for greenhouse gases measurements obtained on the 301-meter-high Zotino Tall Tower Observation Facility (ZOTTO) for the growing seasons (May-September) from 2008 to 2012 (with the exception of 2011). Results showed that the ZOTTO seasonal concentration cumulative footprint climatology for four years reached 6.9×106 km2 and the 75% cumulative footprints varied from 1.9 to 2.3×106 km2. For the same period, the Russian Land Cover map based on MODIS data for 2014 was used to estimate the impact of land cover surrounding the ZOTTO tower on concentration measurements. The analysis showed that in the 75% seasonal cumulative footprint the largest area is occupied by bogs, followed (in decreasing order) by larch, mixed, light-coniferous evergreen forests, grassland, and by other classes. Furthermore, analysis of the contributions from individual cells making up a footprint showed that the largest influence on formation of greenhouse gas concentrations as recorded by ZOTTO comes from the types of vegetation growing in the immediate vicinity of the tall tower, namely bogs, mixed forests, and light and dark coniferous forest stands.

Warming temperatures are likely to accelerate permafrost thaw in the Arctic, potentially leading to the release of old carbon previously stored in deep frozen soil layers. Deeper thaw depths in combination with geomorphological changes due to the loss of ice structures in permafrost, may modify soil water distribution, creating wetter or drier soil conditions. Previous studies revealed higher ecosystem respiration rates under drier conditions, and this study investigated the cause of the increased ecosystem respiration rates using radiocarbon signatures of respired CO2 from two drying manipulation experiments: one in moist and the other in wet tundra. We demonstrate that higher contributions of CO2 from shallow soil layers (0-15 cm; modern soil carbon) drive the increased ecosystem respiration rates, while contributions from deeper soil (below 15 cm from surface and down to the permafrost table; old soil carbon) decreased. These changes can be attributed to more aerobic conditions in shallow soil layers, but also the soil temperature increases in shallow layers but decreases in deep layers, due to the altered thermal properties of organic soils. Decreased abundance of aerenchymatous plant species following drainage in wet tundra reduced old carbon release but increased aboveground plant biomass elevated contributions of autotrophic respiration to ecosystem respiration. The results of this study suggest that drier soils following drainage may accelerate decomposition of modern soil carbon in shallow layers but slow down decomposition of old soil carbon in deep layers, which may offset some of the old soil carbon loss from thawing permafrost.

As a major reservoir for organic carbon, permafrost areas play a pivotal role in global climate change. Vertical carbon fluxes as well as lateral transport from land to groundwaters and surface waters towards the ocean are highly dependent on various abiotic and biotic factors. These include for example temperature, groundwater depth, or vegetation community. During summer months, when soils thaw and lateral carbon transport within suprapermafrost groundwater bodies and surface waters occurs, flow patterns and therefore carbon redistribution may differ significantly between dry and wet conditions. Since dry soil conditions are expected to become more frequent in the future, associated shifts in carbon transport patterns play an important role in quantifying the carbon input into the water body linked to permafrost degradation.This study focuses on hydrological and carbon transport patterns within a floodplain tundra site near Chersky, Northeast Siberia. We compared a wet control site with a site affected by a drainage ring built in 2004 to study the effect of water availability on carbon production and transport. Water table depths at both sites were continuously monitored with a distributed sensor network over the summer seasons 2016-2020. At several locations, water samples were collected in 2016 and 2017 to determine organic carbon concentrations (DOC) as well as carbon isotopes (e.g. ∆14C-DOC). Suprapermafrost groundwater and surface water from the drainage ditch and the nearby Ambolikha river were included in the analysis.Our results focus on the physical hydrological conditions as well as on DOC and ∆14C-DOC observations. The spatio-temporal dynamics of water table depth revealed systematic differences between control and drained sites. The drained area showed a stronger decrease in water tables towards peak summer season in July and stronger reactions to precipitation events. The control area responded less pronounced to short-term changes. At the drained site, the main groundwater flow direction was stable throughout the measurement period. The control site was characterized by a shift in water flow confluence depending on increasing and decreasing water levels. DOC and ∆14C-DOC data showed that the highest concentrations of organic carbon and oldest DOC can be found in late summer. DOC concentrations were higher at the drained site compared to the wet site. We will show that the distribution of dissolved carbon can be directly related to hydrological flow patterns, and that understanding of these redistribution processes is essential for interpreting the carbon budget in disturbed permafrost.

Measurements of the atmospheric sources and sinks of carbon dioxide (CO2) and methane (CH4) in the pan-Arctic domain are extremely sparse that limits our knowledge of carbon cycling over this dramatically sensitive environment and making predictions about a fate of carbon conserved in currently frozen ground. Especially critical are the gaps in the arctic latitudes of Siberia, covered by the vast permafrost underlain tundra, where only few continuous atmospheric observation stations are currently operational. We present the first two years of accurate continuous observations of atmospheric CO2 and CH4 dry mole fractions at the new atmospheric carbon observation station located near the Dikson settlement (73.33° N, 80.34° E) on the seashore of the western part of the Taimyr Peninsula in Siberia. Data quality control of trace gas measurements is achieved by regular calibrations against WMO-traceable reference gases from pressurized dry air tanks filled at the Max Planck Institute for Biogeochemistry (Jena, Germany). Associated meteorological variables permit evaluation of the climate variability of the local environment and provide a background for screening and interpreting the greenhouse gases (GHG) data records. Here we summarize the scientific rationale of the new site, give technical details of the instrumental setup, analyse the local environments and present CO2 and CH4 fluctuations in the arctic atmosphere. Along with the temporal variability of GHG’s, we provide an overview of the angular distribution of detected GHG signals in the region and their input to the atmospheric fluctuations on the measurement site. Observation records deal with the daytime mixed layer and may be considered as representative throughout the vast area (~500–1000 km), and cover the period from September 2018 to September 2020. The reported study was funded by Russian Foundation for Basic Research, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, project number 20-45-242908, RFBR project 18-05-60203 and by the Max Planck Society (Germany)

Ecosystems play a fundamental role in climate change mitigation by photosynthetically fixing carbon from the atmosphere and storing it for a period of time in organic matter. Although climate impacts of carbon emissions by sources can be quantified by global warming potentials, the appropriate formal metrics to assess climate benefits of carbon removals by sinks are unclear. We introduce here the climate benefit of sequestration (CBS), a metric that quantifies the radiative effect of fixing carbon dioxide from the atmosphere and retaining it for a period of time in an ecosystem before releasing it back as the result of respiratory processes and disturbances. In order to quantify CBS, we present a formal definition of carbon sequestration (CS) as the integral of an amount of carbon removed from the atmosphere stored over the time horizon it remains within an ecosystem. Both metrics incorporate the separate effects of (i) inputs (amount of atmospheric carbon removal) and (ii) transit time (time of carbon retention) on carbon sinks, which can vary largely for different ecosystems or forms of management. These metrics can be useful for comparing the climate impacts of carbon removals by different sinks over specific time horizons, to assess the climate impacts of ecosystem management, and to obtain direct quantifications of climate impacts as the net effect of carbon emissions by sources versus removals by sinks.

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions, including their seasonality, due to quasi-continuous and high temporal resolution of flux measurements, coincident measurements of carbon, water, and energy fluxes, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we 1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4- community-product/). FLUXNET-CH4 includes half-hourly and daily gap-filled and non gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we 2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally, because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands and because freshwater wetlands are a substantial source of total atmospheric CH4 emissions; and 3) provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions, but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH4 emissions starts three days earlier, and the CH4 emission season lasts 4 days longer, for each degree C increase in mean annual air temperature. On average, the onset of increasing CH4 emissions lags soil warming by one month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling, and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). The FLUXNET-CH4 dataset provides an open-access resource for CH4 flux synthesis, has a range of applications, and is unique in that it includes coupled measurements of important CH4 drivers such as GPP and temperature. Although FLUXNET-CH4 could certainly be improved by adding more sites in tropical ecosystems and by increasing the number of site-years at existing sites, it is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4408468. Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/, and a complete list of the 79 individual site data DOIs is provided in Table 2 in the Data Availability section of this document., Earth System Science Data Discussions, ISSN:1866-3591

International audience; Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2] (iCO 2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plantmortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

In 2018, central and northern parts of Europe experienced heat and drought conditions over many months from spring to autumn, strongly affecting both natural ecosystems and crops. Besides their impact on nature and society, events like this can be used to study the impact of climate variations on the terrestrial carbon cycle, which is an important determinant of the future climate trajectory. Here, variations in the regional net ecosystem exchange (NEE) of CO 2 between terrestrial ecosystems and the atmosphere were quantified from measurements of atmospheric CO 2 mole fractions. Over Europe, several observational records have been maintained since at least 1999, giving us the opportunity to assess the 2018 anomaly in the context of at least two decades of variations, including the strong climate anomaly in 2003. In addition to an atmospheric inversion with temporally explicitly estimated anomalies, we use an inversion based on empirical statistical relations between anomalies in the local NEE and anomalies in local climate conditions. For our analysis period 1999–2018, we find that higher-than-usual NEE in hot and dry summers may tend to arise in Central Europe from enhanced ecosystem respiration due to the elevated temperatures, and in Southern Europe from reduced photosynthesis due to the reduced water availability. Despite concerns in the literature, the level of agreement between regression-based NEE anomalies and temporally explicitly estimated anomalies indicates that the atmospheric CO 2 measurements from the relatively dense European station network do provide information about the year-to-year variations of Europe’s carbon sources and sinks, at least in summer. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

Eastern Boundary Upwelling Systems (EBUSs) are coastal hotspots of the potent greenhouse gas nitrous oxide (N2O). However, estimates of their emissions suffer from large uncertainties due to their significant spatial and temporal heterogeneity. Here, we derive the first multiyear, monthly resolution N2O emissions from three of the four major EBUSs using high-frequency coastal atmospheric measurements and an inverse method. We find average combined N2O emissions from the northern California, Benguela, and southern Canary upwelling systems to be 57.7 (51.4-63.9) Gg-N yr(-1). We also find an offshore region near the Benguela EBUS that exhibits large pulses of emissions with emissions that reach 677 Gg-N yr(-1) in 1 month. Our findings highlight that atmospheric measurements coupled with inverse modeling can capture the large variability in EBUS emissions by quantifying emissions over large spatial distances and over long time periods compared to previous methods using traditional oceanographic measurements. Plain Language Summary Eastern Boundary Upwelling Systems (EBUSs) are important emissions hotspots of marine nitrous oxide to the atmosphere, where it acts as a greenhouse gas and ozone depleting substance. Emissions from the EBUSs are highly episodic, and most previous estimates are snapshots derived from ship-based measurements. The variability in emissions combined with the sparsity of measurements makes EBUS emission estimates highly uncertain. Here, we use multiyear, near-continuous atmospheric measurements from coastal stations and an inverse modeling framework to derive emissions from three of the four major EBUSs. Our results quantify the significant spatial and temporal variability in emissions, which is not well-represented in global studies of marine nitrous oxide emissions.

The boreal and arctic zone of Siberia represents a «hot spot» area in the global Earth climate system, containing large and potentially vulnerable carbon stocks as well as considerable carbon dioxide (CO2) and methane (CH4) exchange fluxes with the atmosphere. Up to the recent time Siberian region was only sparsely covered by carbon flux measurements. Solely in the frame of EU-funded projects «Eurosiberian Carbonflux» and «Terrestrial Carbon Observing System – Siberia» (TCOS-Siberia) between 1998 and 2005 several atmospheric and terrestrial ecosystem stations were operational in European Russia and Siberia.Since 2006, in order to monitor long-term biogeochemical changes, the Zotino Tall Tower Observatory (ZOTTO; www.zottoproject.org), a research platform for large-scale climatic observations, is operational in Central Siberia (60°48' N, 89°21' E) about 20 km west of the Yenisei river. Observatory consists of a 304-m tall mast for continuous high-precision measurements of greenhouse gases, meteorology and multitude of aerosol properties in the planetary boundary layer (PBL). Sampling of the PBL is essential for the «top-down» approach in observation strategy, since it minimizes local effects and permits to capture regional concentration signals. Such measurements are used in atmospheric inversion modelling to estimate sinks/sources at the surface over the large Siberian territory. In turn, the tall tower observations are linked with eddy covariance measurements of exchange carbon fluxes, introducing a «bottom-up» observational approach, over locally representative ecosystems: pine forest–bog complexes (60°48'N; 89°22'E); a mid-taiga dark coniferous forest (60°01'N; 89°49'E); a northern taiga mature larch forest (64°12'N; 100°27'E) and a forest-tundra ecotone (67°28'N; 86°29'E). This meridional observation network captures exchange fluxes of CO2 and CH4 in ecosystems of the main biogeochemical provinces for the Yenisey river basin of 2580 thousand km², that can be scaled up to the region using vegetation maps, forest biomass inventories and remote sensing information. Since 2018 observation network was expanded and a new coastal station for continuous atmospheric measurements of GHG (СО2/СН4/Н2О) and meteorology is operational on the shore of the Arctic ocean (73°33'N; 80°34'E) near the Dikson settlement. Such coastal station enhances the atmospheric signal derived at «ZOTTO» regarding the budget of trace gases in Central Siberia, permits tracing ocean-continent transport of GHG and also extends the circum-Arctic observation network.Here we summarize the scientific rationale of the observation network, infrastructure details of the stations, the local environments and provide some exemplary results obtained from measurements. The reported study was funded by the Max Planck Society (Germany), RSF project № 14-24-00113 and the RFBR projects № 18-05-00235 and 18-05-60203.

Atmospheric carbon dioxide concentration ([CO

International audience; 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

Changing amplitude of the seasonal cycle of atmospheric CO

The interannual variations in the characteristics of the seasonal cycle (annual and seasonal amplitudes, winter emission, dates of annual minimum and maximum, and phase) and in the growth rate of atmospheric carbon dioxide concentration over Central Siberia are analyzed for the period from May 2009 to January 2016. The results are based on the continuous monitoring of CO2 concentration at the Zotino Tall Tower Observatory (ZOTTO, www.zottoproject.org). It is found that the seasonal amplitude of CO2 concentration in the atmo spheric surface layer over Western Siberia is 26.4 ± 0.8 μmol/mol (no long-term trend toward its increase was revealed), the annual mean growth rate of CO2 is 2.34 μmol/mol per year, its variations range from 1 to 4 μmol/mol per year.

Atmospheric inversions are widely used in the optimization of surface carbon fluxes on a regional scale using information from atmospheric CO2 dry mole fractions. In many studies the prior flux uncertainty applied to the inversion schemes does not directly reflect the true flux uncertainties but is used to regularize the inverse problem. Here, we aim to implement an inversion scheme using the Jena inversion system and applying a prior flux error structure derived from a model–data residual analysis using high spatial and temporal resolution over a full year period in the European domain. We analyzed the performance of the inversion system with a synthetic experiment, in which the flux constraint is derived following the same residual analysis but applied to the model–model mismatch. The synthetic study showed a quite good agreement between posterior and true fluxes on European, country, annual and monthly scales. Posterior monthly and country-aggregated fluxes improved their correlation coefficient with the known truth by 7 % compared to the prior estimates when compared to the reference, with a mean correlation of 0.92. The ratio of the SD between the posterior and reference and between the prior and reference was also reduced by 33 % with a mean value of 1.15. We identified temporal and spatial scales on which the inversion system maximizes the derived information; monthly temporal scales at around 200 km spatial resolution seem to maximize the information gain.

Permafrost landscapes in northern high latitudes with their massive organic carbon stocks are an important, poorly known, component of the global carbon cycle. However, in light of future Arctic warming, the sustainability of these carbon pools is uncertain. To a large part, this is due to a limited understanding of the carbon cycle processes because of sparse observations in Arctic permafrost ecosystems. Here we present an eddy covariance data set covering more than 3 years of continuous CO2 and CH4 flux observations within a moist tussock tundra ecosystem near Chersky in north-eastern Siberia. Through parallel observations of a disturbed (drained) area and a control area nearby, we aim to evaluate the long-term effects of a persistently lowered water table on the net vertical carbon exchange budgets and the dominating biogeochemical mechanisms. Persistently drier soils trigger systematic shifts in the tundra ecosystem carbon cycle patterns. Both, uptake rates of CO2 and emissions of CH4 decreased. Year-round measurements emphasize the importance of the non-growing season—in particular the “zero-curtain” period in the fall—to the annual budget. Approximately 60% of the CO2 uptake in the growing season is lost during the cold seasons, while CH4 emissions during the non-growing season account for 30% of the annual budget. Year-to-year variability in temperature conditions during the late growing season was identified as the primary control of the interannual variability observed in the CO2 and CH4 fluxes.

This study aimed at quantifying potential negative effects of instrument heating to improve eddy covariance flux data quality in cold environments. Our overarching objective was to minimize heating-related bias in annual CO2 budgets from an Arctic permafrost system. We used continuous eddy-covariance measurements covering three full years within an Arctic permafrost ecosystem with parallel sonic anemometers operation with activated heating and without heating as well as parallel operation of open- and closed-path gas analyzers, the latter serving as a reference. Our results demonstrate that the sonic anemometer heating has a direct effect on temperature measurements while the turbulent wind field is not affected. As a consequence, fluxes of sensible heat are increased by an average 5 W m-2 with activated heating, while no direct effect on other scalar fluxes was observed. However, the biased measurements in sensible heat fluxes can have an indirect effect on the CO2 fluxes in case they are used as input for a density-flux WPL correction of an open-path gas analyzer. Evaluating the self-heating effect of the open-path gas analyzer by comparing CO2 flux measurements between open- and closed-path gas analyzers we found systematically higher CO2 uptake recorded with the open-path sensor, leading to a cumulative annual offset of 96 gC m-2, which was not only the result of the cold winter season but also due to substantial self-heating effects during summer. With an inclined sensor mounting, only a fraction of the self-heating correction for vertically mounted instruments is required.

The aim of this paper is to present an overview of inverse modeling methods that have been developed over the years for estimating the global sources and sinks of CH4. It provides insight into how techniques and estimates have evolved over time and what the remaining shortcomings are. As such, it serves a didactical purpose of introducing apprentices to the field, but it also takes stock of developments so far and reflects on promising new directions. The main focus is on methodological aspects that are particularly relevant for CH4, such as its atmospheric oxidation, the use of methane isotopologues, and specific challenges in atmospheric transport modeling of CH4. The use of satellite retrievals receives special attention as it is an active field of methodological development, with special requirements on the sampling of the model and the treatment of data uncertainty. Regional scale flux estimation and attribution is still a grand challenge, which calls for new methods capable of combining information from multiple data streams of different measured parameters. A process model representation of sources and sinks in atmospheric transport inversion schemes allows the integrated use of such data. These new developments are needed not only to improve our understanding of the main processes driving the observed global trend but also to support international efforts to reduce greenhouse gas emissions.

Ground-based atmospheric observations of CO2, δ(O2∕N2), N2O, and CH4 were used to make estimates of the air–sea fluxes of these species from the Lüderitz and Walvis Bay upwelling cells in the northern Benguela region, during upwelling events. Average flux densities (±1σ) were 0.65±0.4 µmol m−2 s−1 for CO2, -5.1±2.5 µmol m−2 s−1 for O2 (as APO), 0.61±0.5 nmol m−2 s−1 for N2O, and 4.8±6.3 nmol m−2 s−1 for CH4. A comparison of our top-down (i.e., inferred from atmospheric anomalies) flux estimates with shipboard-based measurements showed that the two approaches agreed within ±55 % on average, though the degree of agreement varied by species and was best for CO2. Since the top-down method overestimated the flux density relative to the shipboard-based approach for all species, we also present flux density estimates that have been tuned to best match the shipboard fluxes. During the study, upwelling events were sources of CO2, N2O, and CH4 to the atmosphere. N2O fluxes were fairly low, in accordance with previous work suggesting that the evasion of this gas from the Benguela is smaller than for other eastern boundary upwelling systems (EBUS). Conversely, CH4 release was quite high for the marine environment, a result that supports studies that indicated a large sedimentary source of CH4 in the Walvis Bay area. These results demonstrate the suitability of atmospheric time series for characterizing the temporal variability of upwelling events and their influence on the overall marine greenhouse gas (GHG) emissions from the northern Benguela region.

Carbon 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 balance.

We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the Boreal zone. The parameter posterior distributions were generated by adaptive population importance sampler and the optimal values by a simple stochastic optimisation algorithm. The observations used to constrain the model are evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. We were able to improve the coefficient of determination and the model bias with all stomatal conductance formulations. There was no clear candidate for the best stomatal conductance model, although certain versions produced better estimates depending on the examined variable (ET, GPP) and the used metric. We were also able to significantly enhance the model behaviour during a drought event in a Finnish Scots pine forest site. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity. This modification enabled the model to correctly time and replicate the springtime increase in GPP (and ET) for conifers throughout the measurements sites used in this study.

This paper presents global land carbon fluxes for the period 1982–2010 (gross primary production, GPP, and net ecosystem exchange, NEE) estimated with the Max Planck Institute – Carbon Cycle Data Assimilation System (MPI-CCDAS v1). The primary aim of this work is to analyze the performance of the MPI-CCDAS when it is confronted with three different time periods for data assimilation (DA), and thereby to assess its prognostic capability. To this extend we assimilated nearly three decades (1982–2010) of space borne measurements of the fraction of absorbed photosynthetic active radiation (FAPAR) and atmospheric CO2 concentrations from the global network of flask and in situ measurements. Both data sets were incorporated with different assimilation windows covering the periods 1982–1990, 1990–2000 and 1982–2010. The assimilation results show a considerable improvement in the long-term trend and seasonality of FAPAR in the Northern Hemisphere, as well as in the long term trend and seasonal amplitude of the atmospheric CO2 concentrations when compared to the observations in sites globally distributed. After the assimilation, the global net land-atmosphere CO2 exchange (NEE) was −1.2 PgC yr−1, in agreement with independent estimates, while gross primary production (GPP; 92.5 PgC yr−1) was somewhat below the magnitude of independent estimates. The NEE in boreal eastern regions (Northeast Asia) increased on average by −0.13 PgC yr−1, which translated into an intensification of the carbon uptake in those regions by nearly 30 % than the contribution to the global annual average in the model before the assimilation. Our results demonstrate that using information only over a decade already yielded a large fraction of the overall model improvement, in particular for the simulation of phenological seasonality, its interannual variability (IAV) and long-term trend. Adding longer than decadal data did only lead to very moderate improvements in the long-term trend of the FAPAR simulated by the model, which may be attributed to the small model-data mismatch at the long timescales compared to the significantly larger observational signal and model-data mismatch error at seasonal cycle time scale. Decadal data also significantly improved the seasonality, IAV and long-term simulated trend in atmospheric CO2. Importantly, when running the MPI-CCDAS v1 with 30 years of data, the results remained in line with observations throughout this period, suggesting that the model can represent land uptake to a sufficient degree to make it compatible with the atmospheric CO2 record. Using data from 1982 to 1990 in the assimilation yielded only a difference to the observations of 2 ± 1.3 ppm for the period 15 to 19 years after the end of the assimilation. This suggests that despite imperfections in the representation of IAV, model-data fusion can increase the prognostic capacity of land carbon cycle models at relevant time-scales.