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The carbon budget concept states that the global mean temperature (GMT) increase is roughly linearly dependent on cumulative emissions of CO 2. The proportionality is measured as the transient climate response to cumulative emissions of carbon dioxide (TCRE). In this paper, the deviations of the carbon budget from the strict linear relationship implied by the TCRE are examined through the lens of a temperature response to an emission pulse (i.e., pulse response) and its relationship with a nonlinear TCRE. Hereby, two sources of deviation are distinguished: emission scenario and climate state dependence. The former stems from the scenario choice, i.e., the specific emission pathway for a given level of cumulative emissions and the latter from the change in TCRE with changing climatic conditions. Previous literature argues for scenario independence using a stylized set of emission scenarios, and offers a way to fit a nonlinear carbon budget equation. This paper shows how the pulse response, viewed as a Green's function, gives a unifying perspective on both scenario and state dependence. Moreover, it provides an optimization program that tests the scenario independence under the full range of emission pathways for a given set of constraints. In a setup chosen in this paper, the deviations stemming from emission pathway choices are less than 10 % of the overall temperature increase and gradually diminish. Moreover, using the pulse response as a Green's function, the scenario-dependent effects of a reduced-complexity climate model were replicated to a high degree, confirming that the behavior of scenario-dependent deviations can be explained and predicted by the shape of the pulse response. Additionally, it is shown that the pulse response changes with climatic conditions, through which the carbon budget state dependency is explained. Using a pulse response as an approximation for a state-dependent TCRE, an alternative method to derive a nonlinear carbon budget equation is provided. Finally, it is shown how different calibrations of a model can lead to different degrees of carbon budget nonlinearities. The analysis is done using FaIRv2.0.0, a simple climate emulator model that includes climate feedback modifying the carbon cycle, along with a one-box model used for comparison purposes. The Green's function approach can be used to diagnose both models' carbon budget scenario dependency, paving the way for future investigations and applications with other and more complex models. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, the differences in carbon sequestration microbial communities in different wetland types and their main influencing factors were investigated. It was found that the alpha diversity of cbbM carbon-sequestering microorganisms was consistent with the change trend in the total carbon content. Acidithiobacillus was used as a biomarker in lakeside wetlands, and Thiothrix and Thiodictyon were used as biomarkers in marsh wetlands. The diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. The increase in soil temperature and humidity was conducive to the carbon-sequestering process of Thiomicrospira, Thiomonas, Polaromonas and Acidithiobacillus. The changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration. Carbon-sequestering microorganisms play an important role in the carbon cycle of wetland ecosystems. However, the response mechanism of carbon-sequestering microbial communities to wetland type changes and their relationship with soil carbon remain unclear. To explore these differences and identify the main influencing factors, this study selected marsh wetlands, river wetlands and lakeside wetlands around Qinghai Lake as research subjects. High-throughput sequencing was employed to analyze the functional gene cbbM of carbon-sequestering microorganisms. The results revealed that the alpha diversity of cbbM carbon-sequestering microorganisms mirrored the trend in total carbon content, with the highest diversity observed in marsh wetlands and the lowest in lakeside wetlands. The dominant bacterial phylum was Proteobacteria, with prevalent genera including Thiothrix, Acidithiobacillus, and Thiodictyon. Acidithiobacillus served as a biomarker in lakeside wetlands, while two other genera were indicative of marsh wetlands. The hierarchical partitioning analysis indicated that the diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. Moreover, an increased soil temperature and humidity were found to favor the carbon fixation processes of Thiomicrospira, Thiomonas, Polaromonas, and Acidithiobacillus. In summary, changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration. [ABSTRACT FROM AUTHOR]

Nature-based Solutions (NbS) are integral to efforts to keep global warming below 2°C in accordance with the United Nations' 2015 Paris Agreement on Climate Change. Yet the transboundary governance dimensions of NbS remain unclear and largely undocumented. In Southeast Asia, NbS have emphasised the conservation and/ or sustainable commodification of carbon sinks found in terrestrial and mangrove forests, seagrass meadows, peatlands and agricultural soils. Mostly project-driven and fixed-term, these "solutions" have often failed to meet their social and ecological objectives. Increasingly, they have added to cross-border problems of: (1) displaced carbon emissions; and (2) economic migration and societal dispossession. This perspective paper delineates a transboundary governance research agenda to mitigate these trade-offs and enhance the co-benefits of NbS in carbon sinks. Building on NbS literature, it identifies cross-sector, multi-scalar and interdisciplinary pathways to improve transboundary cooperation, inclusion and equity in carbon sink governance in varying Southeast Asian contexts. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, the differences in carbon sequestration microbial communities in different wetland types and their main influencing factors are investigated. It was found that Proteobacteria was the dominant group of carbon sequestration microorganisms in the marsh wetland and river source wetland, and Cyanobacteria was the dominant group of carbon sequestration microorganisms in the lakeside wetland. The α diversity, relative abundance of Proteobacteria and total carbon content of the marsh wetland were the highest, followed by the river source wetland and lakeside wetland. The soil temperature and moisture and the total carbon content were the most important factors affecting the structures of carbon-sequestering microbial communities. Compared with the riverhead and lakeside wetlands, the marsh wetland has the highest carbon storage. The soil carbon storage in the Qinghai–Tibet Plateau wetlands is affected by microbiota and wetland types, but the response mechanisms of carbon sequestration microorganisms on the Qinghai–Tibet Plateau to different wetland types are still poorly described. To explore the differences in carbon sequestration microbial communities in different wetlands and the main influencing factors, this study took a marsh wetland, river source wetland and lakeside wetland of Qinghai Lake as the research objects and used high-throughput sequencing to study the functional gene, cbbL, of carbon sequestration microorganisms. The results showed that the dominant bacterial group of carbon sequestration microorganisms in marsh and river source wetlands was Proteobacteria, and the dominant bacterial group in the lakeside wetland was Cyanobacteria. The alpha diversity, relative abundance of Proteobacteria and total carbon content were the highest in the marsh wetland, followed by the river source wetland, and they were the lowest in the lakeside wetland. In addition, the physical and chemical characteristics of the three wetland types were significantly different, and the soil temperature and moisture and total carbon content were the most important factors affecting the community structures of carbon-sequestering microorganisms. There was little difference in the total nitrogen contents between the marsh wetland and river source wetland. However, the total nitrogen content was also an important factor affecting the diversity of the carbon sequestration microbial community. In summary, the wetland type significantly affects the process of soil carbon sequestration. Compared with the riverhead and lakeside wetlands, the marsh wetland has the highest carbon storage. [ABSTRACT FROM AUTHOR]

Earth has a prolonged history characterized by substantial cycling of matter and energy between multiple spheres. The production of organic carbon can be traced back to as early as ∼4.0 Ga, but the frequency and scale of organic-rich shales have varied markedly over geological time. In this paper, we discuss the organic carbon cycle and the development of black shale from the perspective of Earth System Science. We propose that black shale depositions are the results of interactions among lithospheric evolution, orbital forcing, weathering, photosynthesis and degradation. Black shales can record Earth's oxygenation process, provide petroleum and metallic mineral resources and reveal information about the driver, direction and magnitude of climate change. Future research on black shales should be expanded to encompass a more extensive and more multidimensional perspective. [ABSTRACT FROM AUTHOR]

The SSS (sea surface salinity) is an important factor affecting global climate changes, sea dynamic environments, global water cycles, marine ecological environments, and ocean carbon cycles. Satellite remote sensing is a practical way to observe SSS from space, and the key to retrieving SSS satellite products is to establish an accurate sea surface brightness temperature forward model. However, the calculation results of different forward models, which are composed of different relative permittivity models and SSR (sea surface roughness) brightness temperature increment models, are different, and the impact of this calculation difference has exceeded the accuracy requirement of the SSS inversion, and the existing SSR brightness temperature increment models, which primarily include empirical models and theoretical models, cannot match all the relative permittivity models. In order to address this problem, this paper proposes a universal DNN (deep neural network) model architecture and corresponding training scheme, and provides different SSR brightness temperature increment models for different relative permittivity models utilizing DNN based on offshore experiment data, and compares them with the existing models. The results show that the DNN models perform significantly better than the existing models, and that their calculation accuracy is close to the detection accuracy of a radiometer. Therefore, this study effectively solves the problem of SSR brightness temperature correction under different relative permittivity models, and provides a theoretical support for high-precision SSS inversion research. [ABSTRACT FROM AUTHOR]

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin‐up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi‐Analytical Spin‐Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin‐up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin‐up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin‐up on site and globally in comparison with other spin‐up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change. Plain Language Summary: Land carbon cycle models, a critical component of earth system models, have been developed to investigate and understand ecological responses to global changes. However, the model spin‐up process to achieve steady state are usually time‐consuming and pose great computational burden. The spin‐up problem hinders our ability to study some key issues in land carbon cycle modeling, such as sensitivity analysis. This paper applies a new SASU framework to accelerate spin‐up of Community Land Model matrix version 5. Compared with traditional native dynamic approach, SASU speeds up the spin‐up by approximately 50 times, achieving the fastest spin‐up speed than all the previously recorded methods. Our SASU method is applicable to biogeochemical models and, therefore, liberates the models for computationally costly studies, such as parameter perturbation ensemble analysis and data assimilation. Key Points: A new semi‐analytical spin‐up (SASU) framework combines the default accelerated spin‐up method and matrix analytical algorithmSASU accelerates CLIM5 spin‐up by tens of times, becoming the fastest method to our knowledgeSASU is applicable to most biogeochemical models and enables computationally costly study, for example, sensitivity analysis [ABSTRACT FROM AUTHOR]

In this paper, recent research on terrestrial ecosystem predictability using the conditional nonlinear optimal parameter perturbation (CNOP-P) method is summarized. The main findings include the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, the identification of key physical parameters that lead to large uncertainties in terrestrial ecosystem modeling and prediction, and the evaluation of the simulation ability and prediction skill of terrestrial ecosystems by reducing key physical parameter errors. The study areas included the Inner Mongolia region, north–south transect of eastern China, and Qinghai–Tibet Plateau region. The periods of the studies were from 1961 to 1970 for the impacts of uncertainties in climate change on uncertainties in simulated terrestrial ecosystems, and from 1951 to 2000 for the identification of the most sensitive combinations of physical parameters. Climatic Research Unit (CRU) data were employed. The numerical results indicate the important role of nonlinear changes in climate variability due to the occurrences of extreme events characterized by CNOP-P in the abrupt grassland ecosystem equilibrium state and formation of carbon sinks in China. Second, the most sensitive combinations of physical parameters to the uncertainties in simulations and predictions of terrestrial ecosystems identified by the CNOP-P method were more sensitive than those obtained by traditional methods (e.g., one-at-a-time (OAT) and stochastic methods). Furthermore, the improvement extent of the simulation ability and prediction skill of terrestrial ecosystems by reducing the errors of the sensitive physical parameter combinations identified by the CNOP-P method was higher than that by the traditional methods. [ABSTRACT FROM AUTHOR]

The carbon budget concept is based on discoveries made at the end of the 2000s, claiming that global mean temperature (GMT) increase is roughly linearly dependent on cumulative emissions, with a proportionality metric named transient climate response to cumulative carbon emissions (TCRE). Since its emergence in natural science, the carbon budget concept has gained prominence as a tool for policymakers and climate economists alike. However, its usage in economic assessments has been critiqued due to its inability to capture time-delay effects and TCRE changing with climatic conditions. In this paper, we define the "perfect budget" equation as a purely linear relationship between GMT and cumulative emissions. Hereby, we distinguish two sources of deviations from the perfect carbon budget: emission scenario and climate state dependence. The former stems from the scenario choice under the fixed cumulative emissions, the latter from the change in TCRE with increased cumulative emissions. Introducing Green's function formalism in the context of the temperature response to an emission pulse (pulse response), we provide reasoning behind time delay and possible scenario-dependent deviations and connect Green's formalism with the carbon budget equation. Using an optimization program, we show that extreme scenario-dependent deviations are relatively small compared to the overall GMT increase and even smaller when there are no more emissions after the year of optimization. We explain the behaviour of scenario-dependent deviations by the shape of the pulse response. Additionally, we show that the pulse response changes with climatic conditions, through which we further explain carbon budget state dependency. Finally, we derive a generalized analytical carbon budget equation, which captures the state-dependent change of TCRE through a weak exponential GMT increase dependency on cumulative emissions. The analysis is done in FAIRv2.0.0, a simple climate model that includes climate feedback modifying the carbon cycle. [ABSTRACT FROM AUTHOR]

The Earth's oceans serve as vast heat storage reservoirs and the ocean currents, forming a heat transfer zone, act as a buffer for climate change. The oceans play a crucial role in the water cycle, carbon cycle, and nitrogen cycle, interacting with the atmosphere. However, the increasing occurrence of heatwaves in recent years has disrupted the stability of the oceans and affected their function as a global thermostat. This paper examines relevant literature from the Web of Science database spanning from 1996 to 2023. Our analysis reveals the evolving research hotspots regarding the impact of heatwaves on ocean carbon sinks, progressing from "carbon dioxide - carbon emissions - ocean - seawater - organic matter - marine sediment" over the past decades. Keyword frequency and centrality analysis indicate a deepening focus in this field of study. The research areas primarily revolve around climate change, carbon dioxide, ocean variability, the influence of high temperatures on the carbon cycle, the weakening of the ocean carbon sink function, and ocean temperature. This study summarizes research findings on the mechanisms by which high temperature heatwaves affect ocean carbon sinks, alterations in ocean carbon cycle patterns, their impacts on marine ecosystems, and factors influencing seawater temperature and heatwave occurrence. Finally, the paper discusses novel findings in this field and proposes countermeasures to enhance ocean sink capacity amidst the warming trend. • The research hotspots have shifted from "carbon dioxide-carbon emissions-ocean-seawater-organic matter-marine sediment". • The study analyzes mechanisms by which high-temperature heat waves affect ocean carbon sinks and identifies influencing factors. • The research presents novel findings in this area and proposes strategies to enhance the capacity of ocean sinks. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

Sanjiang Plain is the largest marsh distribution area of China, and marshes in this region significantly affect regional carbon cycle and biodiversity protection. The vegetation phenology of marsh significantly affects the energy exchange and carbon cycle in that region. Under the influence of global climatic change, identifying the changes in phenology and their responses to climatic variation in marshes of Sanjiang Plain is essential for predicting the carbon stocks of marsh ecosystem in that region. Using climate and NDVI data, this paper analyzed the spatiotemporal variations in the start (SOS), end (EOS), and length (LOS) of vegetation growing season and explored the impacts of climatic variation on vegetation phenology in marshes of Sanjiang Plain. Results showed that the SOS advanced by 0.30 days/a, and EOS delayed by 0.23 days/a, causing LOS to increase significantly (p <.05) by 0.53 days/a over marshes of Sanjiang Plain. Spatially, the large SOS advance and EOS delay resulted in an obvious increasing trend for LOS in northern Sanjiang Plain. The rise of spring and winter temperatures advanced the SOS and increased the LOS, and the rise in temperature in autumn delayed the EOS in marshes of Sanjiang Plain. Our findings highlight the necessity of considering seasonal climatic conditions in simulating marsh vegetation phenology and indicate that the different influences of climatic variation on marsh vegetation phenology in different regions should be fully considered to assess the marsh ecosystem response to climatic change in Sanjiang Plain. [ABSTRACT FROM AUTHOR]

We describe the approach taken to develop the United Kingdom's first community Earth system model, UKESM1. This is a joint effort involving the Met Office and the Natural Environment Research Council (NERC), representing the U.K. academic community. We document our model development procedure and the subsequent U.K. submission to CMIP6, based on a traceable hierarchy of coupled physical and Earth system models. UKESM1 builds on the well‐established, world‐leading HadGEM models of the physical climate system and incorporates cutting‐edge new representations of aerosols, atmospheric chemistry, terrestrial carbon, and nitrogen cycles and an advanced model of ocean biogeochemistry. A high‐level metric of overall performance shows that both models, HadGEM3‐GC3.1 and UKESM1, perform better than most other CMIP6 models so far submitted for a broad range of variables. We point to much more extensive evaluation performed in other papers in this special issue. The merits of not using any forced climate change simulations within our model development process are discussed. First results from HadGEM3‐GC3.1 and UKESM1 include the emergent climate sensitivity (5.5 and 5.4 K, respectively) which is high relative to the current range of CMIP5 models. The role of cloud microphysics and cloud‐aerosol interactions in driving the climate sensitivity, and the systematic approach taken to understand this role, is highlighted in other papers in this special issue. We place our findings within the broader modeling landscape indicating how our understanding of key processes driving higher sensitivity in the two U.K. models seems to align with results from a number of other CMIP6 models. Plain Language Summary: The United Kingdom has taken a community approach to model development and delivery of simulations to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The papers in this special issue characterize and evaluate the U.K. models and highlight emerging properties of the models, such as the climate sensitivity. Understanding of the reasons for an increase in sensitivity in these new models is highlighted here, and similarities to our findings from other modeling centers are discussed. Key Points: The United Kingdom has developed its first community Earth system model and delivered a traceable hierarchy of models to CMIP6We applied a process‐based evaluation strategy in model development but chose not to use historic trends or measures of climate responseThe U.K. models exhibit higher climate sensitivity than seen in CMIP5 arising in part from more positive cloud feedbacks [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 retrospective decadal forecasts (or hindcasts) is integrated for 10 years from realistic initial states once a year during 1961 to the present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from pre-industrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skillfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be potentially skillful on decadal timescales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land. [ABSTRACT FROM AUTHOR]

Wetlands are the single largest natural source of methane (CH 4), a powerful greenhouse gas affecting the global climate. In turn, wetland CH 4 emissions are sensitive to changes in climate conditions such as temperature and precipitation shifts. However, biogeochemical processes regulating wetland CH 4 emissions (namely microbial production and oxidation of CH 4) are not routinely included in fully coupled Earth system models that simulate feedbacks between the physical climate, the carbon cycle, and other biogeochemical cycles. This paper introduces a process-based wetland CH 4 model (WETMETH) developed for implementation in Earth system models and currently embedded in an Earth system model of intermediate complexity. Here, we (i) describe the wetland CH 4 model, (ii) evaluate the model performance against available datasets and estimates from the literature, and (iii) analyze the model sensitivity to perturbations of poorly constrained parameters. Historical simulations show that WETMETH is capable of reproducing mean annual emissions consistent with present-day estimates across spatial scales. For the 2008–2017 decade, the model simulates global mean wetland emissions of 158.6 Tg CH 4 yr -1 , of which 33.1 Tg CH 4 yr -1 is from wetlands north of 45 ∘ N. WETMETH is highly sensitive to parameters for the microbial oxidation of CH 4 , which is the least constrained process in the literature. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 historical decadal forecasts (or hindcasts) is integrated for ten years from realistic initial states during 1961 to present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from preindustrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skilfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be skilful on decadal time scales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land. [ABSTRACT FROM AUTHOR]

Biogeochemical cycling in the extensive shelf seas and in the interior basins of the semi-enclosed Arctic Ocean are strongly influenced by land-ocean transport of carbon and other elements. The Arctic carbon cycle system is also inherently connected with the climate, and thus vulnerable to environmental and climate changes. Sediments of the Arctic Ocean are an active and integral part in Arctic biogeochemical cycling, and provide the opportunity to study present and historical input and fate of organic matter (e.g., through permafrost thawing). To compare differences between the Arctic regions and to study Arctic biogeochemical budgets, comprehensive sedimentary records are required. To this end, the Circum-Arctic Sediment CArbon DatabasE (CASCADE) was established to curate data primarily on concentrations of organic carbon (OC) and OC isotopes (d13C, Δ14C), yet also on total N (TN) as well as of terrigenous biomarkers and other sediment geochemical and physical properties drawn both from the published literature and from earlier unpublished records through an extensive international community collaboration. This paper describes the establishment, structure and current status of CASCADE. This first public version includes OC concentrations in surface sediments at 4244 oceanographic stations including 2317 with TN concentrations, 1555 with d13C-OC values, 268 with Δ14C-OC values and 653 records with quantified terrigenous biomarkers (high molecular weight n-alkanes, n-alkanoic acids and lignin phenols) distributed over the shelves and the central basins of the Arctic Ocean. CASCADE also includes data from 326 sediment cores, retrieved by shallow box- or multi-coring and deep gravity/piston coring, as well as sea-bottom drilling. The comprehensive dataset reveals several large-scale features, including clear differences in both OC content and isotope-based diagnostics of OC sources between the shelf sea recipients. This indicates, for instance, the release of strongly pre-aged terrigenous OC to the East Siberian Arctic shelf and younger terrigenous OC to the Kara Sea and thus provides clues about land-ocean transport of material released by thawing permafrost. CASCADE enables synoptic analysis of OC in Arctic Ocean sediments and facilitates a wide array of future empirical and modelling studies of the Arctic carbon cycle. CASCADE is openly and freely available online (https://doi.org/10.17043/cascade; Martens et al., 2020b), is provided in various machine-readable data formats (data tables, GIS shapefile, GIS raster), and also provides ways for contributing data for future CASCADE versions. CASCADE will be continuously updated with newly published and contributed data over the foreseeable future as part of the database management of the Bolin Centre for Climate Research at Stockholm University. [ABSTRACT FROM AUTHOR]

Wetlands are the single largest natural source of methane (CH4), a powerful greenhouse gas affecting the global climate. In turn, wetland CH4 emissions are sensitive to changes in climate conditions such as temperature and precipitation shifts. However, biogeochemical processes regulating wetland CH4 emissions (namely microbial production and oxidation of CH4) are not routinely included in fully coupled Earth system models that simulate feedbacks between the physical climate, the carbon cycle, and other biogeochemical cycles. This paper introduces a process-based wetland CH4 model (WETMETH) developed for implementation in Earth system models and currently embedded in an Earth system model of intermediate complexity. Here we: (i) describe the wetland CH4 model; (ii) evaluate the model performance against available datasets and estimates from the literature; (iii) analyze the model sensitivity to perturbations of poorly constrained parameters. Historical simulations show that WETMETH is capable of reproducing mean annual emissions consistent with present-day estimates across spatial scales. For the 2008-2017 decade the model simulates global mean wetland emissions of 158.6 Tg CH4 yr<->1, of which 33.1 Tg CH4 yr<->1 are from wetlands north of 45° N. WETMETH is highly sensitive to parameters for the microbial oxidation of CH4, which is the least constrained process in the literature. [ABSTRACT FROM AUTHOR]

This contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation of GFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2 increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2 yr−1 simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments. Plain Language Summary: This paper describes and evaluates the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1). GFDL‐ESM4.1 was developed to study the past, present, and future evolution of the Earth system under scenarios for natural and anthropogenic drivers of Earth system change, including greenhouse gases and aerosols. The response of the ocean's vast carbon and heat reservoirs to accumulating greenhouse gases greatly reduces their atmospheric and terrestrial impacts, but also puts ocean environments and the marine resources they support at risk. Relative to previous models, GFDL‐ESM4.1 improves the representation of (a) ocean food webs connecting plankton and fish; (b) biological processes influencing the sequestration of carbon in the deep ocean; and (c) land‐atmosphere‐ocean nutrient exchanges. While simulations have biases, they capture many critical aspects of the global ocean carbon cycle and ocean ecosystem, including the observed uptake of anthropogenic carbon over the last ~150 yr. Projections suggest that continued CO2 increases could significantly decrease ocean productivity and the ocean's capacity to sequester atmospheric carbon. Key Points: Enhanced plankton food webs, remineralization, and Earth system linkages yield skillful global carbon cycle and ecosystem simulationsOcean productivity estimates improved, but phosphate limitation and hypoxia overestimated in some areasHigh CO2 and associated warming substantially reduce the biological pump and ocean productivity across trophic levels [ABSTRACT FROM AUTHOR]

The Earth System Model Evaluation Tool (ESMValTool), a community diagnostics and performance metrics tool for evaluation and analysis of Earth system models (ESMs), is designed to facilitate a more comprehensive and rapid comparison of single or multiple models participating in the Coupled Model Intercomparison Project (CMIP). The ESM results can be compared against observations or reanalysis data as well as against other models including predecessor versions of the same model. The updated and extended version (v2.0) of the ESMValTool includes several new analysis scripts such as large-scale diagnostics for evaluation of ESMs as well as diagnostics for extreme events, regional model and impact evaluation. In this paper, the newly implemented climate metrics such as effective climate sensitivity (ECS) and transient climate response (TCR) as well as emergent constraints for various climate-relevant feedbacks and diagnostics for future projections from ESMs are described and illustrated with examples using results from the well-established model ensemble CMIP5. The emergent constraints implemented include constraints on ECS, snow-albedo effect, climate–carbon cycle feedback, hydrologic cycle intensification, future Indian summer monsoon precipitation and year of disappearance of summer Arctic sea ice. The diagnostics included in ESMValTool v2.0 to analyze future climate projections from ESMs further include analysis scripts to reproduce selected figures of chapter 12 of the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5) and various multi-model statistics. [ABSTRACT FROM AUTHOR]

This paper compares the traditional vs carbon-oriented forest management of two coniferous stands in the Alpine environment, quantifying the carbon sink, the carbon credit generated and the economic results. The results show the economic feasibility of the transition from current forest management strategies to a carbon-oriented method in the considered context. Carbon-oriented management provides relevant environmental benefits, combatting climate change, even though some elements of uncertainty still persist, particularly in relation to achieving a profitable management, specifically due to the volatile voluntary carbon credit market. [ABSTRACT FROM AUTHOR]

Peatlands are poorly represented in global Earth system modeling frameworks. Here we add a peatland‐specific land surface hydrology module (PEAT‐CLSM) to the Catchment Land Surface Model (CLSM) of the NASA Goddard Earth Observing System (GEOS) framework. The amended TOPMODEL approach of the original CLSM that uses topography characteristics to model catchment processes is discarded, and a peatland‐specific model concept is realized in its place. To facilitate its utilization in operational GEOS efforts, PEAT‐CLSM uses the basic structure of CLSM and the same global input data. Parameters used in PEAT‐CLSM are based on literature data. A suite of CLSM and PEAT‐CLSM simulations for peatland areas between 40°N and 75°N is presented and evaluated against a newly compiled data set of groundwater table depth and eddy covariance observations of latent and sensible heat fluxes in natural and seminatural peatlands. CLSM's simulated groundwater tables are too deep and variable, whereas PEAT‐CLSM simulates a mean groundwater table depth of −0.20 m (snow‐free unfrozen period) with moderate temporal fluctuations (standard deviation of 0.10 m), in significantly better agreement with in situ observations. Relative to an operational CLSM version that simply includes peat as a soil class, the temporal correlation coefficient is increased on average by 0.16 and reaches 0.64 for bogs and 0.66 for fens when driven with global atmospheric forcing data. In PEAT‐CLSM, runoff is increased on average by 38% and evapotranspiration is reduced by 19%. The evapotranspiration reduction constitutes a significant improvement relative to eddy covariance measurements. Plain Language Summary: Peatlands are wetlands in which plant matter has accumulated over thousands of years under almost permanently water‐logged conditions. Alterations in these conditions as a result of global climate change can lead to the release of the huge peatland carbon pool as carbon dioxide over much shorter timescales than were required for accumulation. The additional emissions would amplify global warming. A better representation of the peatland hydrology in global Earth system models can help quantify how peatlands respond to a changing climate. In this paper, we add a peatland‐specific land surface hydrology module to the land surface model used in NASA's GEOS Earth system modeling framework. Comparisons of numerical simulations encompassing northern peatlands against field observations show that the new model version significantly improves our ability to capture the hydrological dynamics of peatlands. The new peatland representation in GEOS offers new opportunities, including the potential for merging model information and remote sensing observations in a way that improves our understanding of the overall role played by peatlands in the global water and carbon cycles. Key Points: A peatland‐specific land surface hydrology was added to an Earth system model and constrained by literature data, without parameter tuningSimulations were evaluated with a data set of groundwater table depth and evapotranspiration with unprecedented coverage in high latitudesThe peatland model version performs significantly better in terms of hydrological variables over peatlands than the operational model [ABSTRACT FROM AUTHOR]

To achieve the targets in the Paris Climate Change Agreement, carbon capture, utilization and storage (CCUS) will be one of the critical carbon mitigation technologies. For China, the biggest carbon emitter with coal-dominated energy structure, CCUS is expected to play more and more important roles for carbon emissions reduction. This paper looks at a method for designing a pipeline network system for large-scale CO2 capture, utilization, and storage (CCUS) in China. On the basis of performing a moderately significant literature review of past papers and models dating back to the early 2000’s, a updated multi-stage mixed integer programming (MIP) model for carbon source and sink matching (SSM) in ChinaCCUS DSS (Decision Support System) is developed. The Jing-Jin-Ji (Beijing–Tianjin–Hebei) region suffering from increasingly serious air pollution is chose as a case study to address the SSM issue with application of the updated model. The modeling results show that around 2200 km pipeline with investment of around $1.6 billion needed to be built to transport the cumulative sequestrated emissions of 1620 Mt CO 2 in the planning period of 2020–2050. Compared to the single-stage programming, the multi-stage programming could result to better pipeline connectivity. [ABSTRACT FROM AUTHOR]

Peatlands are poorly represented in global Earth system modeling frameworks. Here we add a peatland‐specific land surface hydrology module (PEAT‐CLSM) to the Catchment Land Surface Model (CLSM) of the NASA Goddard Earth Observing System (GEOS) framework. The amended TOPMODEL approach of the original CLSM that uses topography characteristics to model catchment processes is discarded, and a peatland‐specific model concept is realized in its place. To facilitate its utilization in operational GEOS efforts, PEAT‐CLSM uses the basic structure of CLSM and the same global input data. Parameters used in PEAT‐CLSM are based on literature data. A suite of CLSM and PEAT‐CLSM simulations for peatland areas between 40°N and 75°N is presented and evaluated against a newly compiled data set of groundwater table depth and eddy covariance observations of latent and sensible heat fluxes in natural and seminatural peatlands. CLSM's simulated groundwater tables are too deep and variable, whereas PEAT‐CLSM simulates a mean groundwater table depth of −0.20 m (snow‐free unfrozen period) with moderate temporal fluctuations (standard deviation of 0.10 m), in significantly better agreement with in situ observations. Relative to an operational CLSM version that simply includes peat as a soil class, the temporal correlation coefficient is increased on average by 0.16 and reaches 0.64 for bogs and 0.66 for fens when driven with global atmospheric forcing data. In PEAT‐CLSM, runoff is increased on average by 38% and evapotranspiration is reduced by 19%. The evapotranspiration reduction constitutes a significant improvement relative to eddy covariance measurements. Plain Language Summary: Peatlands are wetlands in which plant matter has accumulated over thousands of years under almost permanently water‐logged conditions. Alterations in these conditions as a result of global climate change can lead to the release of the huge peatland carbon pool as carbon dioxide over much shorter timescales than were required for accumulation. The additional emissions would amplify global warming. A better representation of the peatland hydrology in global Earth system models can help quantify how peatlands respond to a changing climate. In this paper, we add a peatland‐specific land surface hydrology module to the land surface model used in NASA's GEOS Earth system modeling framework. Comparisons of numerical simulations encompassing northern peatlands against field observations show that the new model version significantly improves our ability to capture the hydrological dynamics of peatlands. The new peatland representation in GEOS offers new opportunities, including the potential for merging model information and remote sensing observations in a way that improves our understanding of the overall role played by peatlands in the global water and carbon cycles. Key Points: A peatland‐specific land surface hydrology was added to an Earth system model and constrained by literature data, without parameter tuningSimulations were evaluated with a data set of groundwater table depth and evapotranspiration with unprecedented coverage in high latitudesThe peatland model version performs significantly better in terms of hydrological variables over peatlands than the operational model [ABSTRACT FROM AUTHOR]

A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g., 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multimillennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speed-up is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean–sea ice horizontal grid configuration that allows an increase of the ocean–sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasizes model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain. [ABSTRACT FROM AUTHOR]

Sparse data coverage in the Arctic hampers our understanding of its carbon cycle dynamics and our predictions of the fate of its vast carbon reservoirs in a changing climate. In this paper, we present accurate measurements of atmospheric CO2 and CH4 dry air mole fractions at the new atmospheric carbon observation station Ambarchik, which closes a large gap in the atmospheric trace gas monitoring network in northeastern Siberia. The site, operational since August 2014, is located near the delta of the Kolyma River at the coast of the Arctic Ocean. Data quality control of CO2 and CH4 measurements includes frequent calibrations traced to WMO scales, employment of a novel water vapor correction, an algorithm to detect influence of local polluters, and meteorological measurements that enable data selection. The available CO2 and CH4 record was characterized in comparison with in situ data from Barrow, Alaska. A footprint analysis reveals that the station is sensitive to signals from the East Siberian Sea, as well as northeast Siberian tundra and taiga regions. This makes data from Ambarchik highly valuable for inverse modeling studies aimed at constraining carbon budgets within the pan-Arctic domain, as well as for regional studies focusing on Siberia and the adjacent shelf areas of the Arctic Ocean. [ABSTRACT FROM AUTHOR]

Massive production and spread application of plastics have led to the accumulation of numerous plastics in the global environment so that the proportion of carbon storage in these polymers also increases. Carbon cycle is of fundamental significance to global climate change and human survival and development. With the continuous increase of microplastics, undoubtedly, there carbons will continue to be introduced into the global carbon cycle. In this paper, the impact of microplastics on microorganisms involved in carbon transformation is reviewed. Micro/nanoplastics affect carbon conversion and carbon cycle by interfering with biological fixation of CO 2 , microbial structure and community, functional enzymes activity, the expression of related genes, and the change of local environment. Micro/nanoplastic abundance, concentration and size could significantly lead to difference in carbon conversion. In addition, plastic pollution can further affect the blue carbon ecosystem reduce its ability to store CO 2 and marine carbon fixation capacity. Nevertheless, problematically, limited information is seriously insufficient in understanding the relevant mechanisms. Accordingly, it is required to further explore the effect of micro/nanoplastics and derived organic carbon on carbon cycle under multiple impacts. Under the influence of global change, migration and transformation of these carbon substances may cause new ecological and environmental problems. Additionally, the relationship between plastic pollution and blue carbon ecosystem and global climate change should be timely established. This work provides a better perspective for the follow-up study of the impact of micro/nanoplastics on carbon cycle. [Display omitted] • Research progress on impact of micro/nanoplastics on carbon cycle is reviewed. • Mechanisms of MPs affecting carbon cycle were systematically reviewed. • Impact of MPs on blue carbon ecosystem reduce its ability to store CO 2. • Plastic pollution affect marine carbon fixation capacity and global carbon cycle. • Knowledge gaps and challenges of relevant research are proposed. [ABSTRACT FROM AUTHOR]

The European Reanalysis of Global Climate Observations 2 (ERA-CLIM2) is a European Union Seventh Framework Project started in January 2014 and due to be completed in December 2017. It aims to produce coupled reanalyses, which are physically consistent datasets describing the evolution of the global atmosphere, ocean, land surface, cryosphere, and the carbon cycle. ERA-CLIM2 has contributed to advancing the capacity for producing state-of-the-art climate reanalyses that extend back to the early twentieth century. ERA-CLIM2 has led to the generation of the first European ensemble of coupled ocean, sea ice, land, and atmosphere reanalyses of the twentieth century. The project has funded work to rescue and prepare observations and to advance the data-assimilation systems required to generate operational reanalyses, such as the ones planned by the European Union Copernicus Climate Change Service. This paper summarizes the main goals of the project, discusses some of its main areas of activities, and presents some of its key results. [ABSTRACT FROM AUTHOR]

[Display omitted] • Landscape of blue carbon research from the perspective of bibliometrics. • Blue carbon ecosystem was the main research area, but macroalgae deserve attention. • Artificial intervention and methods are potential hotspots in the future research. • Statistics, co-occurrence analysis and thematic evolution are main used methods. Blue carbon sequestration is a nature-based solution to environmental problems caused by climate change and has a significant positive impact on the planet and human well-being. This paper bibliometrically and systematically analyzed 2,613 studies found in the Web of Science Core Collection (WoSCC) from 2003 to 2021 to explore the hotspots and trends of blue carbon research using the Bibliometrix package in R studio and VOSviewer software. The results based on network co-occurrence analysis indicated that mangroves, seagrasses, and salt marshes were the major blue carbon ecosystems (BCEs), and mangrove carbon sinks were the most popular central research area. Furthermore, phytoplankton and microalgae have essential roles in the marine carbon cycle and bioenergy utilization, as revealed by the high proportion of published literature, while the carbon transport mechanisms of seagrass and macroalgae was understudied. Thematic evolution analysis revealed that remote sensing was the most commonly used technology as an emerging research field for ecological monitoring and ecological investigation in blue carbon research in recent years. In addition, increasing carbon sinks by artificial approaches, fishery carbon sinks, and carbon sequestration by macroalgae have been potential hotspots for blue carbon research development. The findings from this study shed light on the trends of blue carbon in the past eighteen years, current research points in the field, and areas that need more research investment going forward. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive description of OSCAR v2.2, a simple Earth system model. The general philosophy of development is first explained, followed by a complete description of the model's drivers and various modules. All components of the Earth system necessary to simulate future climate change are represented in the model: the oceanic and terrestrial carbon cycles – including a book-keeping module to endogenously estimate land-use change emissions – so as to simulate the change in atmospheric carbon dioxide; the tropospheric chemistry and the natural wetlands, to simulate that of methane; the stratospheric chemistry, for nitrous oxide; 37 halogenated compounds; changing tropospheric and stratospheric ozone; the direct and indirect effects of aerosols; changes in surface albedo caused by black carbon deposition on snow and land-cover change; and the global and regional response of climate – in terms of temperature and precipitation – to all these climate forcers. Following the probabilistic framework of the model, an ensemble of simulations is made over the historical period (1750–2010). We show that the model performs well in reproducing observed past changes in the Earth system such as increased atmospheric concentration of greenhouse gases or increased global mean surface temperature. [ABSTRACT FROM AUTHOR]

The seasonal and interannual dynamics of tropical rainforests play a critical role in the global carbon cycle and climate change. This paper retrieved and compared land surface phenology from observations acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard geostationary satellites and the Moderate Resolution Imaging Spectroradiometer (MODIS) on polar-orbiting satellites over the Congo Basin. To achieve this, we first retrieved canopy greenness cycles (CGCs) and their transition timing from two-band enhanced vegetation index (EVI2) derived from SEVIRI and MODIS data between 2006 and 2013. We then assessed the influences of SEVIRI and MODIS data quality on the reconstruction of the EVI2 temporal trajectory, the detection of the CGC onset and end timing, and the total number of successful CGC retrievals. The significance of influences was determined using the one-tailed two-sample Kolmogorov–Smirnov test. The results indicate that diurnal SEVIRI observations greatly increased the probability of capturing cloud-free daily EVI2 in the rainforest-dominated region of the Congo Basin, where the proportion of good quality (PGQ) observations during a CGC was up to 80% higher than that from MODIS. As a result, the double annual CGCs of the Congo Basin rainforests were well identified from SEVIRI but sparsely detected from MODIS, whereas the single annual CGC in the savanna-dominated northern and southern Congo Basin was successfully retrieved from both SEVIRI and MODIS. Moreover, the decreases of PGQ in an EVI2 time series were found to significantly increase the uncertainties of retrieved phenological timings and increase the probabilities of CGC retrieval failures. [ABSTRACT FROM PUBLISHER]

Forest fires are one of the most important factors in environmental risk assessment and it is the main cause of forest destruction in the Mediterranean region. Forestlands have a number of known benefits such as decreasing soil erosion, containing wild life habitats, etc. Additionally, forests are also important player in carbon cycle and decreasing the climate change impacts. This paper discusses forest fire probability mapping of a Mediterranean forestland using a multiple data assessment technique. An artificial neural network (ANN) method was used to map forest fire probability in Upper Seyhan Basin (USB) in Turkey. Multi-layer perceptron (MLP) approach based on back propagation algorithm was applied in respect to physical, anthropogenic, climate and fire occurrence datasets. Result was validated using relative operating characteristic (ROC) analysis. Coefficient of accuracy of the MLP was 0.83. Landscape features input to the model were assessed statistically to identify the most descriptive factors on forest fire probability mapping using the Pearson correlation coefficient. Landscape features like elevation (R= −0.43), tree cover (R= 0.93) and temperature (R= 0.42) were strongly correlated with forest fire probability in the USB region. [ABSTRACT FROM AUTHOR]

[Display omitted] • Visualization and quantitative analysis of the global ecological carbon sinks and sources. • Enhance the prediction of carbon sequestration dynamics under climate change. • Climate change potentially affecting the carbon-climate feedback. • Research content is becoming clearer and more systematic. • Keyword clustering the classification of the research into six relatively independent subtopics. Climate change is extensively affecting the global ecosystem, especially the ecosystem carbon sequestration and sequestration potential, which are issues of global concern. The proposed concept of "carbon neutrality" in 2020 has brought ecological carbon sequestration to the forefront. Therefore, the research on climate change and ecosystem carbon sequestration need to be systematically reviewed, summarized, and examined. Based on the Web of Science database, this paper analyzed 4005 articles (1992–2022 year) after rigorous screening via a bibliometrics analysis and then presented the research trends and future research focus of ecological carbon sequestration. The following conclusions are drawn: (1) the research over the last 30 years has steadily improved, and the annual number of publications has increased in a cubic polynomial fashion (R 2 = 0.9937), with 87.57 % of the total publications appearing after 2009. Global Change Biology and Science of the Total Environment are the most influential journals in the field; (2) participation in such research is becoming increasingly common with expanding research areas covering Eurasia, America, Oceania, and Africa. The United States and China are the most productive and influential countries; (3) the diversity of this research is increasing, and the research content is becoming more explicit and systematic. Most research focuses on climate change, carbon sequestration, management, land-use changes, and nitrogen and soil organic carbon; (4) although traditional ecological evaluation techniques were essential early on, remote sensing and modeling have become the primary methods for assessment; (5) keyword clustering allows the classification of the research into six relatively independent subtopics: climate change and terrestrial ecosystems, sequestration and organic-carbon, ecosystem services, nitrogen and carbon cycling, biomass and forest, and blue carbon, which provides a reference for further research on ecological carbon sequestration and carbon neutrality. [ABSTRACT FROM AUTHOR]

To cope with global warming, China has promulgated Enhanced actions on climate change : China ’ s intended nationally determined contributions and will start the national carbon emissions trading market in 2017. Carbon emissions are distributed by the form of free quota and paid quota. However, few literatures have focused on how the economy and the environment would be changed by the change of free quota ratio. This paper establishes the 10 scenarios of different free quota ratio of carbon emissions rights and uses a dynamic, recursive computable general equilibrium (CGE) model to simulate the carbon emissions trading market, to explore the relationship between free quota ratio and carbon trading price, and the impact of carbon trading scheme (ETS) on China’s economy and environment. The results show that free quota ratio will not have a direct impact on gross domestic product (GDP) and other economic and environment indicators but carbon trading prices. The prices and the rate of free payment in the current pilot cities in China are still relatively conservative. It is possible to reach emission peak, 8.21 billion ton, in 2025 and accumulative CO 2 reduction from 2017 to 2030 is 20.02 billion tons, or 59.60% of 2010 world’s total CO 2 emission. Cement, minerals, electricity and nonferrous metals under ETS will suffer great losses, so subsidy should be considered. Finally, we suggested that China should reduce the total carbon rights to increase the carbon price in 2017, and gradually reducing the proportion of free quota, from 90% in 2017 to 50% or less in 2030, by which the peak year of CO 2 emission can meet in 2025. We also suggest that ETS is an effective strategy for CO 2 reduction and the ratio should be gradually reduced in ETS to prevent violent fluctuation of carbon price in China. [ABSTRACT FROM AUTHOR]

Monitoring changes in the terrestrial carbon cycle and vegetation health can only be undertaken over large areas and on a regular basis using ecological indicators derived from satellite-based sensors. Climate conditions in Mediterranean ecosystems have undergone, and are projected to undergo, significant change in the future with marked impacts on forest and shrubland vegetation. In the southwest of Australia (SWAU), endemic tree species have experienced significant declines in health and mortality since the early 1990s primarily due to these climatic changes. In this paper we examine trends in Net Primary Production (NPP) from 2000 to 2011 as an indicator of productivity and health condition of the woody vegetation across the SWAU region. To do so, we examine NPP estimates derived from satellite imagery and climate data to answer the questions: (1) what is the extent and rate of change in NPP for the SWAU region over the study period, and (2) how important is fire as a contributing factor in the observed trends? Our results suggest that, similar to the global trend in Mediterranean ecosystems, between 2000 and 2011, overall NPP declined across the study region, with the majority of declines occurring in the ecological transition zone between trees and shrubs. Twenty-six percent of the 37,042 square kilometre of woody vegetation that showed a declining NPP trend, was affected by fire. The overall rate of NPP decline for the region was estimated to be −0.38 megaton C per year since 2000, indicating a reduction in the capacity of the region to act as a carbon sink. Under climate change projections, the observed decline trends are likely to continue and our results suggest that the carbon storage potential in this region is gradually decreasing following an ecological shift from tall tree-dominated to lower shrub-dominated vegetation. [ABSTRACT FROM AUTHOR]

An improved representation of the carbon cycle in permafrost regions will enable more realistic projections of the future climate-carbon system. Currently JULES (the Joint UK Land Environment Simulator) – the land surface model of the UK Earth System Model (UKESM) – uses the standard 4-pool RothC soil carbon model. This paper describes a new version of JULES (vn4.3_permafrost) in which the soil vertical dimension is added to the soil carbon model, with a set of four pools in every soil layer. The respiration rate in each soil layer depends on the temperature and moisture conditions in that layer. Cryoturbation/bioturbation processes, which transfer soil carbon between layers, are represented by diffusive mixing. The litter inputs and the soil respiration are both parameterised to decrease with increasing depth. The model now includes a tracer so that selected soil carbon can be labelled and tracked through a simulation. Simulations show an improvement in the large-scale horizontal and vertical distribution of soil carbon over the standard version of JULES (vn4.3). Like the standard version of JULES, the vertically discretised model is still unable to simulate enough soil carbon in the tundra regions. This is in part because JULES underestimates the plant productivity over the tundra, but also because not all of the processes relevant for the accumulation of permafrost carbon are included in the model. In comparison with the standard model, the vertically discretised model shows a delay in the onset of soil respiration in the spring, resulting in an increased net uptake of carbon during this time. In order to provide a more suitable representation of permafrost carbon for quantifying the permafrost carbon feedback within UKESM, the deep soil carbon in the permafrost region (below 1?m) was initialised using the observed soil carbon. There is now a slight drift in the soil carbon (

Aim This paper presents a new global burned area (BA) product developed within the framework of the European Space Agency's Climate Change Initiative (CCI) programme, along with a first assessment of its potentials for atmospheric and carbon cycle modelling. Innovation Methods are presented for generating a new global BA product, along with a comparison with existing BA products, in terms of BA extension, fire size and shapes and emissions derived from biomass burnings. Main conclusions Three years of the global BA product were produced, accounting for a total BA of between 360 and 380 Mha year−1. General omission and commission errors for BA were 0.76 and 0.64, but they decreased to 0.51 and 0.52, respectively, for sites with more than 10% BA. Intercomparison with other existing BA datasets found similar spatial and temporal trends, mainly with the BA included in the Global Fire Emissions Database (GFED4), although regional differences were found (particularly in the 2006 fires of eastern Europe). The simulated carbon emissions from biomass burning averaged 2.1 Pg C year−1. [ABSTRACT FROM AUTHOR]

Changes in Earth's temperature have significant impacts on the global carbon cycle that vary at different time scales, yet to quantify such impacts with a simple scheme is traditionally deemed difficult. Here, we show that, by incorporating a temperature sensitivity parameter (1.64 ppm yr °C) into a simple linear carbon-cycle model, we can accurately characterize the dynamic responses of atmospheric carbon dioxide (CO) concentration to anthropogenic carbon emissions and global temperature changes between 1850 and 2010 ( r > 0.96 and the root-mean-square error < 1 ppm for the period from 1960 onward). Analytical analysis also indicates that the multiplication of the parameter with the response time of the atmospheric carbon reservoir (~12 year) approximates the long-term temperature sensitivity of global atmospheric CO concentration (~15 ppm °C), generally consistent with previous estimates based on reconstructed CO and climate records over the Little Ice Age. Our results suggest that recent increases in global surface temperatures, which accelerate the release of carbon from the surface reservoirs into the atmosphere, have partially offset surface carbon uptakes enhanced by the elevated atmospheric CO concentration and slowed the net rate of atmospheric CO sequestration by global land and oceans by ~30% since the 1960s. The linear modeling framework outlined in this paper thus provides a useful tool to diagnose the observed atmospheric CO dynamics and monitor their future changes. [ABSTRACT FROM AUTHOR]

The transient climate response to cumulative CO2 emissions (TCRE) is a useful metric of climate warming that directly relates the cause of climate change (cumulative carbon emissions) to the most used index of climate change (global mean near-surface temperature change). In this paper, analytical reasoning is used to investigate why TCRE is near constant over a range of cumulative emissions up to 2000 Pg of carbon. In addition, a climate model of intermediate complexity, forced with a constant flux of CO2 emissions, is used to explore the effect of terrestrial carbon cycle feedback strength on TCRE. The analysis reveals that TCRE emerges from the diminishing radiative forcing from CO2 per unit mass being compensated for by the diminishing ability of the ocean to take up heat and carbon. The relationship is maintained as long as the ocean uptake of carbon, which is simulated to be a function of the CO2 emissions rate, dominates changes in the airborne fraction of carbon. Strong terrestrial carbon cycle feedbacks have a dependence on the rate of carbon emission and, when present, lead to TRCE becoming rate dependent. Despite these feedbacks, TCRE remains roughly constant over the range of the representative concentration pathways and therefore maintains its primary utility as a metric of climate change. [ABSTRACT FROM AUTHOR]

Peatlands contain large amount of carbon stock that is vulnerable to release into the atmosphere. Mostly because of human impact, the peatlands at Zoige Wetlands face severe degradation, and the groundwater table is now lower than before, which has increased the population of the plateau zokor, a burrowing rodent. However, the impact of these changes on ecosystem carbon flows has not been studied. To investigate how the plateau zokor and the groundwater level alter the ecosystem respiration of the Zoige peatlands, we sampled the CO2 flux of hummocks shaped by the zokors and compared it with the CO2 flux of undisturbed sites with different groundwater table levels. The soil organic carbon (SOC), soil water content (SWC) and soil temperature at 5 cm (T5) were measured. SOC showed no significant difference among the four sampling sites and did not correlate with the CO2 flux, while SWC was found to partly determine the CO2 flux. A linear equation could adequately describe the relationship between the natural logarithm of the ecosystem respiration and the soil temperature. It is demonstrated that descending groundwater table might accelerate ecosystem respiration and the CO2 flux from hummocks was higher than the CO2 flux from the control site in the non-growing season. With rising temperature, the CO2 flux from the control site accelerated faster than that from the hummocks. Our results show that ecosystem respiration was significantly lower from hummocks than at the control site in the growing season. The results on the impact of zokors on greenhouse gas emissions presented in this paper provide a useful reference to help properly manage not only this, but other litter-burrowing mammals at peatland sites. [ABSTRACT FROM AUTHOR]

Climate change has been a burning issue since quite a long time and its effects can be perceived around the world. Carbon dioxide (CO 2 ) is the main driver of climate change among other greenhouse gases (GHGs). Despite increasing emissions, CO 2 is fortunately also absorbed or sequestered by plants and other biotic media which form the carbon sinks. These sinks have been diminishing, for instance due to deforestation. Therefore no effort should be spared to assess CO 2 emissions and sequestrations. In this paper, we down-scaled the conventional Inter-Governmental Panel on Climate Change (IPCC) methods, to calculate CO 2 emissions and removals, and we developed a carbon budget index as a case study for Mauritius. Emissions and sequestrations for different land categories (ecosystems) have been assessed for each district. The index revealed important carbon sinks and emission sources from the mappings. Index values for districts ranged from −1.988 metric tonnes (−1998 kg) of CO 2 per km 2 to over 288 metric tonnes (288,000 kg) of CO 2 km −2 . Negative values indicated areas that were net carbon sinks where more carbon was sequestered than emitted. The index can be used to measure national or regional achievements in meeting set targets to reduce emissions. In the context of the Millennium Developments Goals (MDGs), we found that some areas were above the target of 1.4 tonnes per capita for reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystem models are employed to calculate the sources and sinks of carbon dioxide between land and atmosphere. These models may be heavily parameterised. Where reliable estimates are unavailable for a parameter, it remains highly uncertain; uncertainty of parameters can substantially contribute to overall model output uncertainty. This paper builds on the work of the terrestrial Carbon Cycle Data Assimilation System (CCDAS), which, here, assimilates atmospheric CO2 concentrations to optimise 19 parameters of the underlying terrestrial ecosystem model (Biosphere Energy Transfer and Hydrology scheme, BETHY). Previous experiments have shown that the identified minimum may contain non-physical parameter values. One way to combat this problem is to use constrained optimisation and so avoid the optimiser searching non-physical regions. Another technique is to use penalty terms in the cost function, which are added when the optimisation searches outside of a specified region. The use of parameter transformations is a further method of avoiding this problem, where the optimisation is carried out in a transformed parameter space, thus ensuring that the optimal parameters at the minimum are in the physical domain. We compare these different methods of achieving meaningful parameter values, finding that the parameter transformation method shows consistent results and that the other two provide no useful results. [ABSTRACT FROM AUTHOR]

The main components of climate change are carbon dioxide from the atmosphere, air temperature and drought. Considering the major changes of these parameters over time, nowadays especially, but also in the future, in order to cope properly with the new conditions, it is necessary to adjust the photosynthesis process in the sense of increasing its intensity and improving of water use efficiency. Because the stomata are formations of the epidermis involved in the process of carbon dioxide absorption (raw material in photosynthesis) and in its release (in the case of the respiration process), as well as in the release of water vapor during the transpiration, their behavior become defining for what it means not only the plants existence and their good functioning, but stomata influence is also extended and is not limited to just that. Besides the special importance for the physiological processes of plants, for plants own existence and good functioning, stomata also have significant effects for what the concentration of gases in the lower troposphere means and more than that, they can represent risks for vegetation or for human health. In view of the above, the purpose of this mini-synthesis is to present some new information on the central role played by stomata and especially their conductance property, under the conditions of climate change, in relation to the impact on plant productivity, on the carbon cycle in nature, as well as on water flow, but also on human health, with special reference to the conditions specific to the urban environment. [ABSTRACT FROM AUTHOR]

• The net primary productivity (NPP) significantly increased in marshes of study area. • Summer daytime and nighttime temperatures had an asymmetric effect on marsh NPP. • Increased precipitation in summer and autumn can enhance the NPP of marsh vegetation. The western Songnen Plain has a large area of marshes that are able to modulate the regional carbon cycle. Net primary productivity (NPP) is an important ecological indicator of carbon storage within the marsh ecosystems. Although climate change could have significantly changed marsh vegetation NPP during the past decades, the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh vegetation NPP remain unclear in the western Songnen Plain. In this paper, we assessed the spatiotemporal variation in the NPP of marshes at the western Songnen Plain and evaluated its response to climate change from 2000 to 2020. The NPP of marshes over the western Songnen Plain increased significantly at a rate of 5.69 g C/m2/a during 2000 to 2020, with an average value of about 273.62 g C/m2/a. The largest increase of the NPP of marshes was mainly distributed in the northwest part of the Songnen Plain. Correlation analysis results showed that the increased precipitation in summer and autumn could enhance the NPP of marsh vegetation. By contrast, the increase of mean temperature in summer reduced the NPP of marshes. In addition, we first found the asymmetric impacts of summer minimum temperature (T min) and maximum temperature (T max) on marsh vegetation NPP. Notably, the increase in summer T max could significantly reduce NPP, while the increase in T min could increase NPP. Under the background of global asymmetric warming of daytime and nighttime temperatures, more attention should be paid to the different effects of T max and T min on marsh NPP in the western Sonegnen Plain. The findings of this study can provide theoretical guidance for ecological protection and the adaptive management of marsh vegetation at the western Songnen Plain. [ABSTRACT FROM AUTHOR]

• The specific contribution of GUAs to the SDGs has been analysed. • Green urban areas contribute directly to the achievement of SDG11, SDG15 and SDG13. • Equity in sustainable development has been assessed at a sub-neighbourhood level. • Equity requires an adequate location, size, quantity and quality of GUA. The Agenda for Sustainable Development 2030 of United Nations is made up of the 17 Sustainable Development Goals (SDGs) that humanity will have to meet by 2030. In achieving the SDGs, green urban areas (GUA) play a fundamental role at the local level as they provide recreational and bioclimatic regulatory functions and act as a carbon sink, as well. Specifically, the GUAs contribute directly to three SDGs: SDG 11 Sustainable cities and communities, SDG 13 Climate Action and SDG 15 Life on land. This paper evaluates direct contribution of GUA to this SDGs with high spatial resolution in the case study of the city of Valencia (Spain). The evaluation carried out has made it possible to make a diagnosis of the quantity and accessibility of GUA at sub-neighbourhood level. The results for SDG 11 show that only 9.23% of the population do not have desirable access to GUA and 2.73% live in areas without easy walking distance access to GUA. On the other hand, the evaluation of SDG 15 shows that each inhabitant has at their disposal 10 m2 of GUA, below the average of cities of more than 250,000 inhabitants in Spain. The high spatial resolution of the evaluation has also made it possible to identify the city areas with the worst access to GUA and the least amount of GUA per inhabitant. In consequence, the results allow determining zones with high potential to improve. Additionally, the quantification of the CO 2 fixed by the GUA carried out for the evaluation of SDG 13, shows that the fixed carbon is equivalent to 0.04% of total gross GHG emissions of the city and is 36% higher than the total GHG emissions of the annual fuel consumption of the total fleet in the city. Finally, the monitoring of the indicators applied allows evaluating the evolution of the GUA to improve the sustainable development of the city. [ABSTRACT FROM AUTHOR]

• China's water use efficiency showed an increasing trend from 2001 to 2017. • The water use efficiency of forest land is higher than that of low vegetation. • Human activities have a greater contribution to the increase in water use efficiency. • China has more areas with positive correlation between water use efficiency and meteorology. In the context of increasing global carbon emissions, and the relative shortage of water resources, research on the relationships between climate change, human activities and the carbon–water coupling response of China's ecosystems is crucial. Water use efficiency (WUE) is an important indicator reflecting the coupling of ecosystem carbon and water cycles. Based on trend analysis, correlation analysis and multiple regression residual analysis, this paper analyzes the spatiotemporal distributions, change trends, correlations with meteorological factors, changes in different vegetation coverage types, and relative contributions of the main driving factors of China's vegetation WUE from 2001 to 2017. The results show the following: (1) For the past 17 years, the multiyear average value of vegetation WUE in China is 1.08 g C m - 2 mm - 1 , the average annual growth rate is 0.003 g C m - 2 mm - 1 a - 1 . The area with increasing trend of WUE accounts for 59.09% of the total area. (2) The seasonal WUE is highest in autumn, followed by summer, spring and winter. (3) The areas in which vegetation WUE is positively correlated with temperature and precipitation account for approximately 50.21% and 66.16% of the total area, respectively. (4) In terms of the relative annual average value of the WUE, the different vegetation cover types, in descending order, are mixed forests > needleleaf forests > broadleaf forests > shrublands > grasslands > croplands > wetlands > barren lands. (5) Human activities and climate change contributed 66.75% and 33.25%, respectively, to the increase in vegetation WUE in China in the past 17 years. The research results have important scientific significance for clarifying the impacts of climate change and human activities on the carbon–water cycle of the terrestrial ecosystems of China and assessing regional differences in the potential of terrestrial ecosystems to increase carbon sinks. [ABSTRACT FROM AUTHOR]

Peatlands play an important role in the global carbon cycle due to the high carbon storage in the substrate. Ecosystem production depends, for example, on the solar energy amount that reaches the vegetation, however the diffuse component of this flux can substantially increase ecosystem net productivity. This phenomenon is observed in different ecosystems, but the study of the atmosphere optical properties on peatland production is lacking. In this paper, the presented methodology allowed us to disentangle the diffuse radiation impact on the net ecosystem production (NEP) of Rzecin peatland, Poland. It allowed us to assess the impact of the atmospheric scattering process determined by the aerosol presence in the air mass. An application of atmospheric radiation transfer (ART) and ecosystem production (EP) models showed that the increase of aerosol optical thickness from 0.09 to 0.17 caused NEP to rise by 3.4–5.7%. An increase of the diffusion index (DI) by 0.1 resulted in an NEP increase of 6.1–42.3%, while a DI decrease of 0.1 determined an NEP reduction of −49.0 to −10.5%. These results show that low peatland vegetation responds to changes in light scattering. This phenomenon should be taken into account when calculating the global CO2 uptake estimation of such ecosystems. [ABSTRACT FROM AUTHOR]

Climate change is identified as a major threat to wetlands. Altered hydrology and rising temperature can change the biogeochemistry and function of a wetland to the degree that some important services might be turned into disservices. This means that they will, for example, no longer provide a water purification service and adversely they may start to decompose and release nutrients to the surface water. Moreover, a higher rate of decomposition than primary production (photosynthesis) may lead to a shift of their function from being a sink of carbon to a source. This review paper assesses the potential response of natural wetlands (peatlands) and constructed wetlands to climate change in terms of gas emission and nutrients release. In addition, the impact of key climatic factors such as temperature and water availability on wetlands has been reviewed. The authors identified the methodological gaps and weaknesses in the literature and then introduced a new framework for conducting a comprehensive mesocosm experiment to address the existing gaps in literature to support future climate change research on wetland ecosystems. In the future, higher temperatures resulting in drought might shift the role of both constructed wetland and peatland from a sink to a source of carbon. However, higher temperatures accompanied by more precipitation can promote photosynthesis to a degree that might exceed the respiration and maintain the carbon sink role of the wetland. There might be a critical water level at which the wetland can preserve most of its services. In order to find that level, a study of the key factors of climate change and their interactions using an appropriate experimental method is necessary. Some contradictory results of past experiments can be associated with different methodologies, designs, time periods, climates, and natural variability. Hence a long-term simulation of climate change for wetlands according to the proposed framework is recommended. This framework provides relatively more accurate and realistic simulations, valid comparative results, comprehensive understanding and supports coordination between researchers. This can help to find a sustainable management strategy for wetlands to be resilient to climate change. [Display omitted] • Drought might shift the role of wetlands from carbon sinks to carbon sources. • Higher temperatures and more rain can maintain the role of wetlands as carbon sinks. • There might be a critical water level at which a wetland can preserve its services. • A new framework for conducting wetland mesocosm experiments has been proposed. • The proposed experiment allows for testing of dynamic process-based model results. [ABSTRACT FROM AUTHOR]

Accurately estimating vegetation productivity is important in the research of terrestrial ecosystems, carbon cycles and climate change. Although several gross primary production (GPP) and net primary production (NPP) products have been generated and many algorithms developed, advances are still needed to exploit multi-scale data streams for producing GPP and NPP with higher spatial and temporal resolution. In this paper, a method to generate high spatial resolution (30 m) GPP and NPP products was developed based on multi-scale remote sensing data and a downscaling method. First, high resolution fraction photosynthetically active radiation (FPAR) and leaf area index (LAI) were obtained by using a regression tree approach and the spatial and temporal adaptive reflectance fusion model (STARFM). Second, the GPP and NPP were estimated from a multi-source data synergized quantitative algorithm. Finally, the vegetation productivity estimates were validated with the ground-based field data, and were compared with MODerate Resolution Imaging Spectroradiometer (MODIS) and estimated Global LAnd Surface Satellite (GLASS) products. Results of this paper indicated that downscaling methods have great potential in generating high resolution GPP and NPP. [ABSTRACT FROM AUTHOR]

• This paper estimates carbon emissions released by household travel demand from 47 Japanese cities. • Carbon footprint generated by private transport is found as 1.4 to 13.9 times higher than public transport. • Gasoline's direct combustion is found as the most significant reason to generate the regional difference. • The highest total carbon footprint is found in cities with fewer population. Considering its substantial and increasing contribution to global climate change, the household sector shows potential for larger carbon reductions. Among different household activities, household individual travel demands due to private or public transportation affect the environment via both direct or indirect emissions. To develop insights from a city-level perspective, carbon emissions released due to household travel demands in 47 Japanese cities were estimated in this study using the most recent available data. Given the differences in traveling preferences, spatial distribution and cluster analyses by city were also conducted. The results indicate that cities with a larger carbon footprint usually had a smaller population, whereas in megacities, less carbon per capita was released. The direct combustion of gasoline and train use were the most important factors influencing regional differences in direct and indirect emissions, respectively. The findings also indicate that customized carbon mitigation strategies that consider individual preferences and city size have a better chance of achieving decarbonization of citizen transportation in Japan. [ABSTRACT FROM AUTHOR]