Global Terrestrial Ecosystem Carbon Flux Inferred from TanSat XCO2 Retrievals

TanSat is China’s first greenhouse gases observing satellite. In recent years, substantial progresses have been achieved on retrieving column-averaged CO2 dry air mole fraction (XCO2). However, relatively few attempts have been made to estimate terrestrial net ecosystem exchange (NEE) using TanSat XCO2 retrievals. In this study, based on the GEOS-Chem 4D-Var data assimilation system, we infer the global NEE from April 2017 to March 2018 using TanSat XCO2. The inversion estimates global NEE at −3.46 PgC yr-1, evidently higher than prior estimate and giving rise to an improved estimate of global atmospheric CO2 growth rate. Regionally, our inversion greatly increases the carbon uptakes in northern mid-to-high latitudes and significantly enhances the carbon releases in tropical and southern lands, especially in Africa and India peninsula. The increase of posterior sinks in northern lands is mainly attributed to the decreased carbon release during the nongrowing season, and the decrease of carbon uptakes in tropical and southern lands basically occurs throughout the year. Evaluations against independent CO2 observations and comparison with previous estimates indicate that although the land sinks in the northern middle latitudes and southern temperate regions are improved to a certain extent, they are obviously overestimated in northern high latitudes and underestimated in tropical lands (mainly northern Africa), respectively. These results suggest that TanSat XCO2 retrievals may have systematic negative biases in northern high latitudes and large positive biases over northern Africa, and further efforts are required to remove bias in these regions for better estimates of global and regional NEE.

Spatiotemporal Dynamics of the Carbon Budget and the Response to Grazing in Qinghai Grasslands

Estimating the grassland carbon budget is critically important for ensuring that grassland resources are used sustainably. However, the spatiotemporal dynamics of the carbon budget and the response to grazing have not yet been characterized in Qinghai grasslands. Here, we estimated the gross primary productivity (GPP) and net ecosystem exchange (NEE) in Qinghai grasslands using the improved Biome-BGCMuSo model to characterize the spatiotemporal dynamics of the carbon budget and the response to grazing in this region from 1979 to 2018. The GPP of Qinghai grasslands fluctuated during the study period, with an average annual value of 118.78 gC/m2. The NEE of Qinghai grasslands fluctuated from 1979 to 2018, with an average value of −5.16 gC/m2. After 2,000, GPP increased, and NEE decreased in a fluctuating manner. There were clear regional differences in GPP and NEE. GPP was low in most areas of Qinghai, and GPP was high in eastern and southern Qinghai. The southern, southeastern, and northeastern parts of Qinghai were mainly carbon sinks, and the northwestern part of Qinghai and the region between the southeastern and northeastern parts of Qinghai were mainly carbon sources. Grazing generally decreased GPP and increased NEE in Qinghai grasslands from 1979 to 2018. There was spatial heterogeneity in the effect of grazing on GPP and NEE. Under grazing, GPP and NEE were significantly decreased mainly in eastern Qinghai, and GPP and NEE were significantly increased mainly in southern and eastern Qinghai. NEE was most affected by grazing in eastern Qinghai. The results of this study aid our understanding of the mechanism driving variation in the grassland carbon budget and provide new data that could be used to support local grassland management.

Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model

As vegetation regulates water, carbon, and energy cycles from the local to the global scale, its accurate representation in land surface models is crucial. The assimilation of satellite-based vegetation observations in a land surface model has the potential to improve the estimation of global carbon and energy cycles, which in turn can enhance our ability to monitor and forecast extreme hydroclimatic events, ecosystem dynamics, and crop production. This work proposes the assimilation of a remotely sensed vegetation product (Leaf Area Index, LAI) within the Noah Multi-Parameterization land surface model using an Ensemble Kalman Filter technique. The impact of updating leaf mass along with LAI is also investigated. Results show that assimilating LAI data improves the estimation of transpiration and net ecosystem exchange, which is further enhanced by also updating the leaf mass. Specifically, transpiration anomaly correlation coefficients improve in about 77 and 66% of the global land area thanks to the assimilation of leaf area index with and without updating leaf mass, respectively. Random errors in transpiration are also reduced, with an improvement of the unbiased root mean square error in 70% (74%) of the total area without the update of leaf mass (with the update of leaf mass). Similarly, net ecosystem exchange anomaly correlation coefficients improve from 52 to 75% and random errors improve from 49 to 62% of the total pixels after the update of leaf mass. Better performances for both transpiration and net ecosystem exchange are observed across croplands, but the largest improvement is shown over forests and woodland. The global scope of this work makes it particularly important in data poor regions (e.g., Africa, South Asia), where ground observations are sparse or not available altogether but where an accurate estimation of carbon and energy variables can be critical to improve ecosystem and crop management.

Simulation of Carbon Exchange from a Permafrost Peatland in the Great Hing’an Mountains Based on CoupModel

Climate change is accelerating its impact on northern ecosystems. Northern peatlands store a considerable amount of C, but their response to climate change remains highly uncertain. In order to explore the feedback of a peatland in the Great Hing’an Mountains to future climate change, we simulated the response of the overall net ecosystem exchange (NEE), ecosystem respiration (ER), and gross primary production (GPP) during 2020–2100 under three representative concentration pathways (RCP2.6, RCP6.0, and RCP8.5). Under the RCP2.6 and RCP6.0 scenarios, the carbon sink will increase slightly until 2100. Under the RCP8.5 scenario, the carbon sink will follow a trend of gradual decrease after 2053. These results show that when meteorological factors, especially temperature, reach a certain degree, the carbon source/sink of the peatland ecosystem will be converted. In general, although the peatland will remain a carbon sink until the end of the 21st century, carbon sinks will decrease under the influence of climate change. Our results indicate that in the case of future climate warming, with the growing seasons experiencing overall dryer and warmer environments and changes in vegetation communities, peatland NEE, ER, and GPP will increase and lead to the increase in ecosystem carbon accumulation.

Environmental Control of Inter-annual Variability of Net Ecosystem Exchange in Rice-rice Cropping System

Consecutive five-year long eddy covariance measurements in a lowland tropical rice-rice system were used to investigate the impacts of gross primary productivity (GPP), climate drivers and ecosystem responses (i.e. ecosystem respiration, RE) on the inter-annual variability (IAV) of the net ecosystem exchange (NEE), which is directly related to the agricultural productivity and climate change. The IAV of carbon dioxide fluxes in two crop growing phases i.e. dry and wet season along with fallow period were analysed. The respiratory fluxes build up during the non-growing season were lower by net uptake in growing season. Annual cumulative value of NEE was negative (sink) in both the crop growing season. The variability of climate drivers and changes in the ecosystem responses to drivers revealed a large intra-annual as well as inter-annual variability of net ecosystem fluxes. NEE was found to be strongly correlated with GPP and RE and also with other metrological variables such as photosynthetically active radiation (PAR), precipitation, air temperature and soil temperature. The anomalies of NEE, GPP and RE were observed to be less in 2017 and 2018 which may be due to lower temperature anomalies recorded in these years. Further understanding of biological mechanisms is needed which is involved in the variation of climatological variables to improve our ability to predict future IAV of NEE.

Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska

Seasonal variations in high-latitude terrestrial carbon (C) fluxes are predominantly driven by air temperature and radiation. At present, high-latitude net C uptake is largest during the summer. Recent observations and modeling studies have demonstrated that ongoing and projected climate change will increase plant productivity, microbial respiration, and growing season lengths at high-latitudes, but impacts on high-latitude C cycle seasonality (and potential feedbacks to the climate system) remain uncertain. Here we use ecosys, a well-tested and process-rich mechanistic ecosystem model that we evaluate further in this study, to explore how climate warming under an RCP8.5 scenario will shift C cycle seasonality in Alaska throughout the 21st century. The model successfully reproduced recently reported large high-latitude C losses during the fall and winter and yet still predicts a high-latitude C sink, pointing to a resolution of the current conflict between process-model and observation-based estimates of high-latitude C balance. We find that warming will result in surprisingly large changes in net ecosystem exchange (NEE; defined as negative for uptake) seasonality, with spring net C uptake overtaking summer net C uptake by year 2100. This shift is driven by a factor of 3 relaxation of spring temperature limitation to plant productivity that results in earlier C uptake and a corresponding increase in magnitude of spring NEE from -19 to -144 gC m-2 season-1 by the end of the century. Although a similar relaxation of temperature limitation will occur in the fall, radiation limitation during those months will limit increases in C fixation. Additionally, warmer soil temperatures and increased carbon inputs from plants lead to combined fall and winter C losses (163 gC m-2) that are larger than summer net uptake (123 gC m-2 season-1) by year 2100. However, this increase in microbial activity leads to more rapid N cycling and increased plant N uptake during the fall and winter months that supports large increases in spring NPP. Due to the large increases in spring net C uptake, the high-latitude atmospheric C sink is projected to sustain throughout this century. Our analysis disentangles the effects of key environmental drivers of high-latitude seasonal C balances as climate changes over the 21st century.

Effect of Climate Change on CO2 Flux in Temperate Grassland, Subtropical Artificial Coniferous Forest and Tropical Rain Forest Ecosystems

The interactions between CO2 flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004–2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003–2010), and the tropical rain forest (TRF) of Xishuangbanna (2003–2010). The main factors of climate change affecting ecosystem CO2 flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO2 flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO2 flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.

Moist moss tundra on Kapp Linne, Svalbard is a net source of CO₂ and CH₄ to the atmosphere

We measured CO2 and CH4 fluxes using chambers and eddy covariance (only CO2) from a moist moss tundra in Svalbard. The average net ecosystem exchange (NEE) during the summer (June–August) was −0.40 g C m−2 day−1 or −37 g C m−2 for the whole summer. Including spring and autumn periods the NEE was reduced to −6.8 g C m−2 and the annual NEE became positive, 24.7 gC m−2 due to the losses during the winter. The CH4 flux during the summer period showed a large spatial and temporal variability. The mean value of all 214 samples was 0.000511 ± 0.000315 µmol m−2s−1 which corresponds to a growing season estimate of 0.04 to 0.16 g CH4 m−2. We find that this moss tundra emits about 94–100 g CO2-equivalents m−2 yr−1 of which CH4 is responsible for 3.5–9.3 % using GWP100 of 27.9 respectively GWP20. Air temperature, soil moisture and greenness index contributed significantly to explain the variation in ecosystem respiration (Reco) while active layer depth, soil moisture and greenness index were the variables that best explained CH4 emissions. Estimate of temperature sensitivity of Reco and gross primary productivity showed that a modest increase in air temperature of 1 degree did not significantly change the NEE during the growing season but that the annual NEE would be even more positive adding another 8.5 g C m−2 to the atmosphere. We tentatively suggest that the warming of the Arctic that has already taken place is partly responsible for the fact that the moist moss tundra now is a source of CO2 to the atmosphere.

NEE estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system

3-hourly Net Ecosystem Exchange (NEE) is estimated at spatial scales of 0.25 degrees over the European continent, based on the pre-operational inverse modelling framework CarboScope Regional (CSR) for the years 2006 to 2019. To assess the uncertainty originating from the choice of a-priori flux models and observational data, ensembles of inversions were produced using three terrestrial ecosystem flux models, two ocean flux models, and three sets of atmospheric stations. We find that the station set ensemble accounts for 61 % of the total spread of the annually aggregated fluxes over the full domain when varying all these elements, while the biosphere and ocean ensembles resulted in much smaller contributions to the spread of 28 % and 11 %, respectively. These percentages differ over the specific regions of Europe, based on the availability of atmospheric data. For example, the spread of the biosphere ensemble is prone to be larger in regions that are less constrained by CO2 measurements. We further investigate the unprecedented increase of temperature and simultaneous reduction of Soil Water Content (SWC) observed in 2018 and 2019. We find that NEE estimates during these two years suggest an impact of drought occurrences represented by the reduction of Net Primary Productivity (NPP), which in turn lead to less CO2 uptake across Europe in 2018 and 2019, resulting in anomalies up to 0.13 and 0.07 PgC yr-1 above the climatological mean, respectively. Annual temperature anomalies also exceeded the climatological mean by 0.46 °C in 2018 and by 0.56 °C in 2019, while standardized-precipitation-evaporation-index (SPEI) anomalies declined to −0.20 and −0.05 SPEI units below the climatological mean in both 2018 and 2019, respectively. Therefore, the biogenic fluxes showed a weaker sink of CO2 in both 2018 and 2019 (−0.22±0.05 and −0.28±0.06 PgC yr-1, respectively) in comparison with the mean −0.36±0.07 PgC yr-1 calculated over the full analysed period (i.e., fourteen years). These translate into a continental-wide reduction of the annual sink by 39 % and 22 %, respectively, larger than the typical year-to-year standard deviation of 19 % observed over the full period.