Search

Forestation is a major component of future long-term emissions reduction and CO$_2$ removal strategies, but the viability of carbon stored in vegetation under future climates is highly uncertain. We analyze the results from seven CMIP6 models for a combined scenario with high fossil fuel emissions (from SSP5-8.5) and moderate forest expansion (from SSP1-2.6). This scenario aims to demonstrate the ability of forestation strategies to mitigate climate change under continued increasing CO$_2$ emissions and includes the potential impacts of increased CO$_2$ concentration and a warming climate on vegetation growth. The model intercomparison shows that moderate forestation as a CO$_2$ removal strategy has limited impact on global climate under a high global warming scenario, despite generating a substantial cumulative carbon sink of 10–60 Pg C over the period 2015–2100. Using a single model ensemble, we show that there are local increases in warm extremes in response to forestation associated with decreases in the number of cool days. Furthermore, we find evidence of a shift in the global carbon balance, whereby increased carbon storage on land of $\sim$25 Pg C by 2100 associated with forestation has a concomitant decrease in the carbon uptake by the ocean due to reduced atmospheric CO$_2$ concentrations.

Land cover and land management changes (LCLMCs) play an important role in achieving low-end warming scenarios through land-based mitigation. However, their effects on moisture fluxes and recycling remain uncertain although they have important implications for the future viability of such strategies. Here, we analyse the impact of idealised LCLMC scenarios on atmospheric moisture transport in three different ESMs: the Community Earth System Model (CESM), the Max Planck Institute Earth System Model (MPI-ESM) and the European Consortium Earth System Model (EC-EARTH). The LCLMC scenarios comprise of a full cropland world, a fully afforested world, and a cropland world with unlimited irrigation expansion. The effects of these LCLMCs in the different ESMs are analysed for precipitation, evaporation and vertically integrated moisture flux convergence to understand the LCLMC-induced changes in the atmospheric moisture cycle. Then, a moisture tracking algorithm is applied to assess the effects of LCLMCs on moisture recycling at the local (grid cell level) and the global scale (continental moisture recycling). Our results indicate that LCLMCs are generally inducing consistent feedbacks on moisture fluxes over land in all ESMs. Cropland expansion causes drying and reduced local moisture recycling in all ESMs, while afforestation and irrigation expansion generally cause wetting and increased local moisture recycling. However, the strength of this influence varies in time and space and across the ESMs and shows a strong dependency on the dominant driver: Some ESMs show a dominance of large scale atmospheric circulation changes while other ESMs show a dominance of local to regional changes in the atmospheric water cycle only within the vicinity of the LCLMC. Overall, these results corroborate that LCLMCs can induce large effects on the atmospheric water cycle and moisture recycling, but more research is needed to constrain the uncertainty of these effects within ESMs and better evaluate land-based mitigation strategies.

Land-based mitigation is essential in reducing carbon emissions. Yet, the attribution of land carbon fluxes to their sinks and sources remains highly uncertain, in particular for the forest-rich but data-poor region of Eastern Europe. Here we integrate various data sources (from top-down and bottom-up modelling, earth observation, inventories) to show that Eastern Europe accounted for an annual aboveground biomass (AGB) carbon sink of ~0.49 GtC in 2010‑2019, or about 75% of the entire European carbon uptake. However, we find that the land-based carbon sink is declining. This declining trend is mainly driven by changes in land use and land management, but also by increasing natural disturbances due to ongoing climate change. Despite the high overall importance of environmental factors such as soil moisture, nitrogen and CO2 for enhancing the land-based carbon sink, we find indicators of a saturation effect of the regrowth in abandoned former agricultural areas, combined with an increase in wood harvest, particularly in European Russia. Our results contribute to a better understanding of the regional carbon budget of Eastern Europe and its trend. This study sheds light on land use and management as drivers of the land-based carbon sink and their role for climate mitigation.

The climate mitigation potential of terrestrial carbon dioxide removal (CDR) methods remains highly uncertain depending on the timing and magnitude of climate mitigation but also due to model uncertainty in the underlying Earth System models. In addition to these uncertainties, there are different approaches to measuring the effectiveness of CDR methods for climate change mitigation. In our study, we introduce various measures of effectiveness and evaluate the climate mitigation potential of afforestation and bioenergy plants under the low-emission scenario ssp126. To do this, we use the land component JSBACH3 of the Earth System Model MPI-ESM; afforestation is represented as the spatial increase of four forest plant functional types. Bioenergy plants are represented as highly efficient C4 plants (miscanthus and panicum). There are various assumptions concerning fossil fuel substitution and carbon capture and storage. Measuring effectiveness over time, we show how bioenergy plants become more effective over the long term compared to afforestation. In addition to this temporal measure, the climate mitigation potential of bioenergy plants depends significantly on the rate of fossil fuel substitution. Lastly, the spatial extent that is needed to match a given CDR amount in time by afforestation and BECCS can be quantified. Our study thus asses and compares the potentials of the two CDR methods highlighting the various perspectives of assessment.

Global-scale af-/reforestation (A/R) and deforestation substantially changes the Earth’s energy and water fluxes, thereby affecting the large-scale atmospheric circulation and thus have significant impacts on weather systems. During summer, A/R and deforestation induced changes in the soil moisture are shown to have an impact on the planetary wave response through the jet stream. Such changes might lead to high-amplitude, quasi-stationary circumglobal Rossby waves that have been associated with extreme summer heatwaves and persistent high-impact extremes. In this study we investigate how idealized global land use and land management changes can alter the boreal summer circulation with a focus on the response of the jet stream. For the analysis we conducted model experiments with three fully coupled Earth System Models (EC-EARTH, MPI-ESM and CESM). Each scenario run for 160 years from which we analyze the final 30 years. A control run with constant current land use and land management is compared to a global A/R and a global deforestation (global cropland expansion) simulation. In order to assess clean land-atmosphere interactions, all simulations are kept with constant present-day atmospheric forcings (year 2014). We investigate the potential changes in the amplitude of the waves, the likelihood of quasi-stationary wave activity, and of summer blockings within the three different simulations, and the weather consequences that such changes lead to.

Anthropogenic and natural CO2 fluxes on land constitute substantial CO2 emissions and removals but are usually not well distinguished in national greenhouse gas inventories (NGHGIs) submitted to the United Nations Framework Convention on Climate Change (UNFCCC). Instead, countries frequently include natural and indirect human-induced CO2 fluxes on managed land in their estimates of CO2 fluxes from land use, land-use change, and forestry (LULUCF), mostly due to methodological constraints. Comparisons of anthropogenic LULUCF flux estimates from global models and from NGHGI reports thus reveal a substantial gap. Globally, this gap could be successfully reconciled by considering the different definitions used by global models and by NGHGI reports. Recent improvements in LULUCF flux modelling enable such a reconciliation now also at the country-level.We separate natural and land-use-related CO2 fluxes from NGHGI reports in eight countries using global models to assess and improve the attribution of land CO2 fluxes to direct anthropogenic activities. In most investigated countries, the gap between model-based and report-based CO2 flux estimates is reduced (by up to 70%) if natural and indirect human-induced CO2 fluxes on managed land are considered. This confirms that the methodological discrepancies between NGHGI reports and global model estimates of LULUCF emissions are primarily due to differing estimation and reporting definitions, which need to be considered when accounting for country contributions to global climate mitigation targets. Further examinations show that remaining differences are linked to country-specific discrepancies between model-based and report-based estimates, such as incomplete reporting by countries, uncertainties in historical land-use dynamics, and model limitations. Moreover, most countries report the areas considered as managed without explicit information on their location, which prevents a precise spatial identification necessary for a detailed comparison of natural fluxes in managed forests with model-based estimates.Reconciling estimates of LULUCF fluxes in individual countries by separating natural and land-use-related CO2 fluxes at national scales provides an important step toward a transparent assessment of LULUCF fluxes from NGHGI reports and supports a fair burden sharing of climate mitigation across countries.

Land cover and land management changes (LCLMC) have often been highlighted as crucial regarding climate change, both for mitigation (e.g. afforestation) and adaptation (e.g. irrigation). In order to understand this role we present fully coupled Earth System Model (ESM) simulations using external forcing conditions from the SSP1-1.9 scenario, except for land cover and land management scenarios that follow differing trajectories. First we conduct a short 30-year historical simulation (histCTL) and a future (years 2015-2100) simulation under SSP1-1.9 conditions but with present day land cover kept at constant end of 2014 conditions (futCTL). These allow us to isolate climate changes in response to the SSP1-19 forcing, but in the absence of land cover changes. Secondly we conduct two simulations under SSP1-1.9 forcing, but with land cover and land management following two different trajectories. These trajectories are derived from the scenarios presented in Humpenöder et al. (2022) and represent two strongly diverging worlds with regard to socio-economic development, environmental protection, and land-based mitigation: (i) the future sustainability scenario (futSust) in which the land sector experiences sustainable development and application of mitigation strategies (such as greenhouse gas emission pricing) in all countries, (ii) the future inequality scenario (futIneq) in which these developments mostly happen in OECD countries, with the rest of the world continuing on current trends (including massive tropical deforestation). Each of these simulations have been run with three different ESMs (CESM, MPI-ESM and EC-EARTH) in order to identify how robust these results are over different ESMs.The results of these simulations can be used to increase our understanding of the role of land cover scenarios within a low-warming future as prescribed by the Paris agreement. We can compare the effects of all other forcings (futCTL- histCTL; CO2, aerosols etc.) to the effects of land cover changes in the different scenarios (futSust – futCTL or futIneq-futCTL) as well as to the difference between the future sustainability and the inequality narratives (futSust-futIneq). These results will be analysed for temperature and moisture fluxes, mainly focusing on warm and dry extremes and how land cover scenarios affect these. ReferencesHumpenöder, F., Popp, A., Schleussner, C. F., Orlov, A., Windisch, M. G., Menke, I., Pongratz, J., Havermann, F., Thiery, W., Luo, F., Jeetze, P. V., Philipp Dietrich, J., Lotze-Campen, H., Weindl, I. & Lejeune, Q. (2022). Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. Nature Communications, 13(1), 1-15.

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We base this update on the assessment methods used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report, updating the monitoring datasets and to produce updated estimates for key climate indicators including emissions, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth’s energy imbalance, warming attributed to human activities, the remaining carbon budget and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.7883758, Smith et al., 2023). As they are traceable and consistent with IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human induced warming reached 1.14 [0.9 to 1.4] °C over the 2013–2022 period and 1.26 [1.0 to 1.6] °C in 2022. Human induced warming is increasing at an unprecedented rate of over 0.2 °C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 57 ± 5.6 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there are signs that emission levels are starting to stabilise, and we can hope that a continued series of these annual updates might track a real-world change of direction for the climate over this critical decade.

The natural vegetation has been substantially changed over the last millenium, especially from forest to agricultural areas in Europe. To study the effects of deforestation on carbon and climate system, it is essential to construct spatially precise maps in forest cover. The current representative historical forest data sets are either derivatives of agricultural datasets or are produced based on the deforestation-population relationship. Almost no attempts have been made to use the inherently linked relationship between deforestation and cropland expansion that has run through Europe for millennia. This study created an approach based on the relationship between cultivation intensity and forest fraction to reconstruct forest cover changes in central and southeast Europe from AD 1800 to 2000 by the following steps: (1) To develop the spatial relationship curve (spatial resolution is 1°) between the “cultivation intensity (0–100%)” and the “forest fraction (0–100%)” derived from modern land cover datasets; (2) To generate the national-scale cropland data based on historical records from AD 1800 to 2000, and to allocate them to a 1° pixel; (3) To reconstruct the forest cover using the aforementioned relationship curve and the historical gridded cropland database. The results show that: (1) The forest fraction in central and southeast Europe decreased from 38.4% in AD 1800 to 27.0% in AD 1900, and then increased to 32.5% in AD 2000. (2) In AD 1800, large areas of forests can be primarily found in Luxembourg, Netherlands and Belgium, the south of France, the south of Germany, the Alps region, Poland, and the majority of the Balkans. (3) Throughout the 19th century, the entire region was generally subjected to deforestation, with large areas of forest coverage only being preserved in the Alps and the western and southern Balkans after 100 years of exploration. (4) The forest coverage in most of the study regions increased again at the end of the 20th century.

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO2 yr−1) in global land-use CO2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO2 yr−1 for the period 2000–2020, and NGHGIs, which estimate a sink of −1.9 GtCO2 yr−1 in the same period. Most of the gap is found on forest land (3.5 GtCO2 yr−1), with differences also for deforestation (2.4 GtCO2 yr−1), for fluxes from other land uses (1.0 GtCO2 yr−1) and to a lesser extent for fluxes from organic soils (0.2 GtCO2 yr−1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (−6.4 GtCO2 yr−1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO2 yr−1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at https://doi.org/10.5281/zenodo.7650360.

The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive analysis of state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon. Over the whole Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast with a carbon small source simulated by top-down inversions (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed on an Amazon net carbon source during recent climate extremes and that south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought. If the current trends in deforestation and forest degradation and regional drying continue, it will have negative implications for reducing carbon emissions and maintaining globally important natural carbon stocks, as part of the requirements for achieving the Paris Agreement goals.

The Amazon forests are one of the largest ecosystem carbon pools on Earth. Although more frequent and prolonged future droughts have been predicted, the impacts have remained largely uncertain, as most land surface models (LSMs) fail to capture the vegetation drought responses. In this study, the ability of the LSM JSBACH to simulate the drought responses of leaf area index (LAI) and leaf litter production in the Amazon forests is evaluated against artificial drought experiments. Based on the evaluation, improvements are implemented, including a dependency of leaf growth on leaf carbon allocation and a better representation of drought-dependent leaf shedding. The modified JSBACH is shown to capture the drought responses at two sites and across different regions of the basin. It is then coupled with an atmospheric model to simulate the carbon and biogeophysical feedbacks of drought under future climate. We separate the drought impacts into (a) the direct effect, resulting from drier soil and stomatal closure, which does not involve a change in canopy structure, and (b) the LAI effect, resulting from leaf shedding and involving canopy response. We show that the latter accounts for 35% of reduced land carbon uptake (9 ± 10 vs. 26 ± 7 g/m2/yr; mean ± 1 sd) and 12% of surface warming (0.09 ± 0.03 vs. 0.7 ± 0.07 K) during the late 21st century. A north-south dipole of precipitation change is found, which is largely attributable to the direct effect. The results highlight the importance of incorporating drought deciduousness of tropical rainforests in LSMs to better simulate land-atmosphere interactions in the future.

Regional land carbon budgets provide insights into the spatial distribution of the land uptake of atmospheric carbon dioxide and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields, or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions due to different definitions and component fluxes being reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers that connect CO2 uptake in one area with its release in another also requires better definitions and protocols to reach harmonized regional budgets that can be summed up to a globe scale and compared with the atmospheric CO2 growth rate and inversion results. In this study, using the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims to be an update to regional carbon budgets over the last 2 decades based on observations for 10 regions covering the globe with a better harmonization than the precursor project, we provide recommendations for using atmospheric inversion results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes, and land use fluxes.

Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) fluxes and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021b). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven sectoral model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with European National Greenhouse Gas Inventories (NGHGIs) reported by Parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 3392 ± 49 Tg CO2 yr-1 (926 ± 13 Tg C yr-1), while eight other BU sources report a mean value of 3340 [3238,3401] [25th,75th percentile] Tg CO2 yr-1 (948 [937,961] Tg C yr-1). The sole top-down inversion of fossil emissions currently available accounts for 3800 Tg CO2 yr-1 (1038 Tg C yr-1), a value close to that of the NGHGI, but for which uncertainty estimates are not yet available. For the net CO2 land fluxes, during the most recent five-year period including the NGHGI estimates, the NGHGI accounted for -91 ± 32 Tg C yr-1 while six other BU approaches reported a mean sink of -62 [-117,-49] Tg C yr-1 and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5] Tg C yr-1. The five-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73 Tg C yr-1 has a slightly smaller spread (0th–100th percentile of [-135,45] Tg C yr-1), and was calculated after removing land-atmosphere CO2 fluxes caused by lateral transport of carbon (crops, wood trade and inland waters) resulting in increased agreement with the the NGHGI and bottom-up approaches. Results at the sub-sector level (Forestland, Cropland, Grassland) show generally good agreement between the NGHGI and sub-sector-specific models, but results for a DGVM are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while large uncertainties on net uptake of CO2 by the land surface prevent trend identification. In addition, a gap on the order of 1000 Tg C yr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.7365863.

Anthropogenic and natural CO2 fluxes on land constitute substantial CO2 emissions and removals but are usually not well distinguished in national greenhouse gas reporting. Instead, countries frequently combine natural and indirect human-induced CO2 fluxes on managed land in their reports, which diminishes their usefulness for designing policies consistent with climate mitigation targets. Here, we separate natural and land-use-related CO2 fluxes from national reports in eight countries using global models to improve the assessment of attribution of terrestrial CO2 fluxes to direct anthropogenic activities. In most investigated countries, the gap between model-based and report-based CO2 flux estimates is reduced if natural and indirect human-induced CO2 fluxes on managed land are considered. Further examinations show that remaining differences are linked to country-specific discrepancies between model-based and report-based estimates. Separating natural and land-use-related CO2 fluxes at national scales supports a fair burden sharing of climate mitigation across countries and facilitates the assessment of land-based mitigation ambitions. © 2022 The Authors

Society is set to experience significant land cover changes in order to achieve the temperature goals agreed upon under the Paris Agreement. Such changes carry both global implications, pertaining to the biogeochemical effects of land cover change and thus the global carbon budget, and regional/local implications, pertaining to the biogeophysical effects arising within the immediate area of land cover change. Biogeophysical effects of land cover change are of high relevance to national policy- and decision- makers and their accountance is essential towards effective deployment of land cover practices that optimises between global and regional impacts. To this end, ESM outputs that isolate the biogeophysical responses of climate to land cover changes are key in informing impact assessments and supporting scenario development exercises. Generating multiple such ESM outputs, in a manner that allows comprehensive exploration of all plausible land cover scenarios however, is computationally untenable. This study proposes a framework to agilely explore the local biogeophysical responses of climate under different land cover scenarios by means of a computationally inexpensive emulator. The emulator is novel in that it solely represents the land cover forced, biogeophysical responses of climate, and can be used as either a standalone device or supplementary to existing climate model emulators that represent greenhouse gas (GHG)- or Global Mean Temperature (GMT)- forced climate responses. We start off by modelling local minimum, mean and maximum surface temperature responses to tree cover changes by means of a month- and Earth System Model (ESM)- specific Generalised Additive Model (GAM) trained over the whole globe. 2-m air temperature responses are then diagnosed from the modelled minimum and maximum surface temperature responses using observationally derived relationships. Such a two-step procedure accounts for the different physical representations of surface temperature responses to tree cover changes under different ESMs, whilst respecting a definition of 2-m air temperature that is more consistent across ESMs and with observational datasets. In exploring new tree cover change scenarios, we employ a parametric bootstrap sampling method to generate multiple possible temperature responses, such that the uncertainty within the GAM's derived shape of the response is also quantified. The output of the final emulator is demonstrated for the SSP 1-2.6 and 3-7.0 scenarios. Relevant temperature responses are identified as those displaying a clear signal in relation to the surrounding uncertainty in shape of derived response, calculated as the "signal-to-noise" ratio between the sample set mean and sample set variability. The emulator framework developed in this study thus provides a first step towards bridging the information-gap surrounding biogeophysical implications of land cover changes, allowing for smarter land-use decision making.