Earth system modelling

In addressing management scenarios and climate changes, it is necessary to consider surface water and groundwater resources as an integrated system. In this context, the present research first simulates and evaluates surface water and groundwater simultaneously; then, it examines the possible effects of climate change on these water resources in the study area (Mahabad, Northwest of Iran). In the first stage, the WEAP-MODFLOW model was applied to a 10-year period (2006-2015) in order to take into account the interactions between surface water and groundwater and calibrate the amount of recharge and drainage from the aquifer. In the second stage, in order to study the effect of climate change on surface water and groundwater resources, we compared the micro-scale model outputs under the RCP4.5 scenario for different climate change models in the period 2021-2045. The results show that root-mean-square error (RMSE) and mean absolute error (MAE) scores are equal to 0.89 and 0.79 in unsteady conditions, respectively, which confirm the efficient performance of groundwater simulation. In addition, the results of the WEAP model based on MARE assessment criteria for calibration and validation modes are equal to 0.54 and 54.0, respectively. This finding provides evidence for the efficient performance of the simulation model. Once the interactions between groundwater and surface water were specified, the results R 2 and NS suggested that indices were equal to 0.62 and 0.59, respectively, for Mahabad hydrometric station. The efficient performance of the proposed model for runoff simulation was therefore confirmed. Owing to climate change in the study period, groundwater decreased by about 1.6-1.9 m. Moreover, the amount of runoff declined from 0.1 to 0.001 MCM/month in all months except December. Unless appropriate decisions are taken to improve groundwater and strategies are applied to reduce the effect of climate change, under the present conditions this region will suffer irreparable damages in the future.

Terrestrial gross primary production (GPP) is the basis of food production and vegetation growth globally 1 , and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP 2 , low soil water availability, heat stress, and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analyzed outputs of 13 Earth System Models (ESMs) to show an increasingly stronger impact on GPP by extreme droughts than mild and moderate droughts over the 21 st century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally-averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075-2099) relative to that of the historical period (1850-1999) under both high and intermediate greenhouse gas emission scenarios. In contrast, the magnitude of GPP reduction associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favorable environmental conditions.

International commitment to the appropriately ambitious Paris climate agreement and the United Nations Sustainable Development Goals in 2015 has pulled into the limelight the urgent need for major scientific progress in understanding and modelling the Anthropocene, the tightly intertwined social-environmental planetary system that humanity now inhabits. The Anthropocene qualitatively differs from previous eras in Earth's history in three key characteristics: (1) There is planetary-scale human agency. (2) There are social and economic networks of teleconnections spanning the globe. (3) It is dominated by planetary-scale socialecological feedbacks. Bolting together old concepts and methodologies cannot be an adequate approach to describing this new geological era. Instead, we need a new paradigm in Earth System science that is founded equally on a deep understanding of the physical and biological Earth System -and of the economic, social and cultural forces that are now an intrinsic part of it. It is time to close the loop and bring socially mediated dynamics explicitly into theory, analysis and models that let us study the whole Earth System.

Recent multimodel studies have shown that if one attempts to cancel increasing CO2 concentrations by reducing absorbed solar radiation, the hydrological cycle will weaken if global temperature is kept unchanged. Using a global climate model, we investigate the hydrological cycle response to “cirrus cloud thinning (CCT),” which is a proposed climate engineering technique that seeks to enhance outgoing longwave radiation. Investigations of the “fast response” in experiments with fixed sea surface temperatures reveal that CCT causes a significant enhancement of the latent heat flux and precipitation. This is due to enhanced radiative cooling of the troposphere, which is opposite to the effect of increased CO2 concentrations. By combining CCT with CO2 increase in multidecadal simulations with a slab ocean, we demonstrate a systematic enhancement of the hydrological cycle due to CCT. This leads to enhanced moisture availability in low‐latitude land regions and a strengthening of the Indi...

Here we show results from Earth System Model simulations from the marine cloud brightening experiment G4cdnc of the Geoengineering Model Intercomparison Project (GeoMIP). The nine contributing models prescribe a 50 % increase in the cloud droplet number concentration (CDNC) of low clouds over the global oceans, with the purpose of counteracting the radiative forcing due to anthropogenic greenhouse gases under the RCP4.5 scenario. The model ensemble median effective radiative forcing (ERF) amounts to −1.9 Wm<sup>−2</sup>, with a substantial inter-model spread of −0.6 to −2.5 Wm<sup>−2</sup>. The large spread is partly related to the considerable differences in clouds and their representation between the models, with an underestimation of low clouds in several of the models. All models predict a statistically significant temperature decrease with a median of (for years 2020–2060) −0.95 [−0.18 ...

With the advent of climate change as a major challenge of our time, Earth system modeling has become highly policy-relevant regulatory science. In this situation, the social mechanisms that play a role in any scientific endeavor become particularly exposed. By discussing historical, philosophical, and sociological (HPS) aspects of the field's current "cultures of prediction" together with the physical science community in a physical science journal, we aim to provide an entry point into HPS reasoning for climate scientists interested in reflecting on their field and science in general. This paper, first, introduces our perspective on "science as culture" and climate modeling as "regulatory science" and, second, highlights and connects relevant ideas from the three commentaries that follow it. In so doing, we hope to give a fuller picture of climate science, the interplay it engenders between HPS and the physical sciences, the distinctions that it gives rise to as compared to some of the more traditional, exact, sciences in which it is rooted and its place in society including its role in scientific policy advice.

It is a matter of consensus that the ability to efficiently use current and future high performance computing systems is crucial for science, however, the reality is that the performance currently achieved by most of the parallel scientific applications is far from desired. Despite inter-process communication has already been a matter of study in many different works, it is a fact that their recommendations are not taken into account in most of computational model development processes, at least in the case of Earth Science. This work presents a methodology that aims to help scientists working with computational models using inter-process communication, to deal with the difficulties they face when trying to understand their applications behaviour. Following a series of steps that are presented here, both users and developers will learn how to identify performance issues by characterizing applications scalability, identifying which parts present a bad performance and understand the role that inter-process communication plays. In this work, the Nucleus for European Modelling of the Ocean (NEMO), the state-of-the-art European global ocean circulation model, will be used as an example of success. It is a community code widely used in Europe, to the extent that more than a hundred million core hours are used every year in experiments involving NEMO. In the analysis exercise, it is shown how to answer the questions of where, why and what is degrading model's scalability, and how this information can help developers in finding solutions that will mitigate their eventual issues. This document also demonstrates how performance analysis carried out with small size experiments, using limited resources, can lead to optimizations that will impact bigger experiments running on thousands of cores, making it easier to deal with the exascale challenge.

Quantifying the output uncertainty and tracking down its origins is key to interpreting the results of modelling studies. We perform such an uncertainty analysis on the predictions of forest growth and yield under climate change. We specifically focus on the effect of the inter-annual climate variability. For that, the climate years in the model input (daily resolution) were randomly shuffled within each 5-year period. In total, 540 simulations (10 parameter sets, 9 climate shuffles, 3 global climate models and 2 mitigation scenarios), were made for one growing cycle (80 years) of a Scots pine forest growing in Peitz (Germany). Our results show that, besides the important effect of the parameter set, the random order of climate years can significantly change results such as basal area and produced volume, and the response of these to climate change. We stress that the effect of weather variability should be included in the design of impact model ensembles, and the accompanying uncertainty analysis. We further suggest presenting model results as likelihoods to allow risk assessment. For example, in our study the likelihood of a decrease in basal area of >10% with no mitigation was 20.4%, while the likelihood of an increase >10% was 34.4%.

Process-based ecological models are essential tools to quantify and predict forest growth and carbon cycles under the background of climate change. The accurate description of phenology and tree growth processes enables an improved understanding and predictive modeling of forest dynamics. An individual tree-based carbon model, FOR-CCHN2 (Forest Ecosystem Carbon Budget Model for China version 2.0), used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. This model performed well in reducing uncertainty when predicting forest carbon fluxes. Here, we describe the framework in detail and provide the source code of FORCCHN2. We also present a dynamiclink library (DLL) package containing the latest version of FORCCHN2. This package has the advantage of using Fortran as an interface to make the model run fast on a daily step, and the package also allows users to call it with their preferred computer tools (e.g., MATLAB, R, Python). FORC-CHN2 can be used directly to predict spring and autumn phenological dates, daily carbon fluxes (including photosynthesis, aboveground and belowground autotrophic respiration, and soil heterotrophic respiration), and biomass on plot, regional, and hemispheric scales. As case studies, we provide an example of FORCCHN2 running model validations in 78 forest sites and an example model application for the carbon dynamics of Northern Hemisphere forests. We demonstrate that FORCCHN2 can produce a reasonable agreement with flux observations. Given the potential importance of the application of this ecological model in many studies, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimations.

Process-based ecological models are essential tools to quantify and predict forest growth and carbon cycles under the background of climate change. The accurate description of phenology and tree growth processes enables an improved understanding and predictive modeling of forest dynamics. An individual tree-based carbon model, FOR-CCHN2 (Forest Ecosystem Carbon Budget Model for China version 2.0), used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. This model performed well in reducing uncertainty when predicting forest carbon fluxes. Here, we describe the framework in detail and provide the source code of FORCCHN2. We also present a dynamiclink library (DLL) package containing the latest version of FORCCHN2. This package has the advantage of using Fortran as an interface to make the model run fast on a daily step, and the package also allows users to call it with their preferred computer tools (e.g., MATLAB, R, Python). FORC-CHN2 can be used directly to predict spring and autumn phenological dates, daily carbon fluxes (including photosynthesis, aboveground and belowground autotrophic respiration, and soil heterotrophic respiration), and biomass on plot, regional, and hemispheric scales. As case studies, we provide an example of FORCCHN2 running model validations in 78 forest sites and an example model application for the carbon dynamics of Northern Hemisphere forests. We demonstrate that FORCCHN2 can produce a reasonable agreement with flux observations. Given the potential importance of the application of this ecological model in many studies, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimations.

Given the multiple abiotic and biotic stressors resulting from global changes, management systems and practices must be adapted in order to maintain and reinforce the resilience of forests. Among others, the transformation of monocultures into uneven-aged and mixed stands is an avenue to improve forest resilience. To explore the forest response to these new silvicultural practices under a changing environment, one need models combining a process-based approach with a detailed 5 spatial representation, which is very rare. We therefore decided to develop our own model (HETEROFOR) according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). HETEROFOR was progressively elaborated through the integration of various modules (light interception, phenology, water cycling, photosynthesis and respiration, carbon allocation, mineral nutrition and nutrient cycling) within CAPSIS, a collaborative modelling platform devoted to tree growth 10 and stand dynamics. The advantage of using such a platform is to use common development environment, model execution system, user-interface and visualization tools and to share data structures, objects, methods and libraries. This paper describes the carbon-related processes of HETEROFOR (photosynthesis, respiration, carbon allocation and tree dimensional growth) and evaluates the model performances for a mixed oak and beech stand in Wallonia (Belgium). This first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size-growth relationships. 15 We also noticed that the more empirical options for describing maintenance respiration and crown extension provide the best results while the process-based approach best performs for photosynthesis. To illustrate how the model can be used to predict climate change impacts on forest ecosystems, the growth dynamics in this stand was simulated according to four IPCC climate scenarios. According to these simulations, the tree growth trends will be governed by the CO2 fertilization effect with the increase in vegetation period length and in water stress also playing a role but offsetting each other. 20

Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as ‘1.5 °C scenarios’, with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define ‘medium’ and ‘high’ upper bounds that deli...

Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as ‘1.5 °C scenarios’, with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define ‘medium’ and ‘high’ upper bounds that deli...

Global net-negative carbon emissions are prevalent in almost all emission pathways that meet the Paris temperature targets. In this paper, we generate and compare cost-effective emission pathways that satisfy two different types of climate targets. First, the common approach of a radiative forcing target that has to be met by the year 2100 (RF2100), and, second, a temperature ceiling target that has to be met over the entire period, avoiding any overshoot. Across two integrated assessment models (IAMs), we found that the amount of net-negative emissions—when global net emissions fall below zero—depends to a large extent on how the target is represented, i.e. implemented in the model. With a temperature ceiling (no temperature overshoot), net-negative emissions are limited and primarily a consequence of trade-offs with non-CO2 emissions, whereas net-negative emissions are significant for the RF2100 target (temperature overshoot). The difference becomes more pronounced with more strin...

Contributing Authors: Katherine Calvin (USA), Oreane Edelenbosch (Netherlands), Johannes Emmerling (Germany/Italy), Sabine Fuss (Germany), Thomas Gasser (France/Austria), Nathan Gillet (Canada), Chenmin He (China), Edgar Hertwich (Austria/USA), Lena Höglund-Isaksson (Sweden/Austria), Daniel Huppmann (Austria), Gunnar Luderer (Germany), Anil Markandya (UK/Spain), David L. McCollum (USA/Austria), Richard Millar (UK), Malte Meinshausen (Germany/Australia), Alexander Popp (Germany), Joana Correia de Oliveira de Portugal Pereira (Portugal/UK), Pallav Purohit (India/Austria), Keywan Riahi (Austria), Aurélien Ribes (France), Harry Saunders (Canada/USA), Christina Schädel (Switzerland/USA), Chris Smith (UK), Pete Smith (UK), Evelina Trutnevyte (Lithuania/Switzerland), Yang Xiu (China), Kirsten Zickfeld (Germany/Canada), Wenji Zhou (China/Austria)

Opening paragraph The Paris Agreement has opened debate on whether limiting warming to 1.5°C is compatible with current emission pledges and warming of about 0.9°C from the mid-19 th-century to the present decade. We show that limiting cumulative post-2015 CO2 emissions to about 200 GtC would limit post-2015 warming to less than 0.6°C in 66% of Earth System Model members of the CMIP5 ensemble with no mitigation of other climate drivers, increasing to 240GtC with ambitious non-CO2 mitigation. We combine a simple climatecarbon-cycle model with estimated ranges for key climate system properties from the IPCC 5 th Assessment Report. Assuming emissions peak and decline to below current levels by 2030 and continue thereafter on a much steeper decline, historically unprecedented but consistent with a standard ambitious mitigation scenario (RCP2.6), gives a likely range of peak warming of 1.2-2.0°C above the mid-19 th-century. If CO2 emissions are continuously adjusted over time to limit 2100 warming to 1.5°C, with ambitious non-CO2 mitigation, net future cumulative CO2 emissions are unlikely to prove less than 250 GtC and unlikely greater than 540GtC. Hence limiting warming to 1.5°C is not yet a geophysical impossibility, but likely requires delivery on strengthened pledges for 2030 followed by challengingly deep and rapid mitigation. Strengthening near-term emissions reductions would hedge against a high climate response or subsequent reduction-rates proving economically, technically or politically unfeasible.

Contributing Authors: Katherine Calvin (USA), Oreane Edelenbosch (Netherlands), Johannes Emmerling (Germany/Italy), Sabine Fuss (Germany), Thomas Gasser (France/Austria), Nathan Gillet (Canada), Chenmin He (China), Edgar Hertwich (Austria/USA), Lena Höglund-Isaksson (Sweden/Austria), Daniel Huppmann (Austria), Gunnar Luderer (Germany), Anil Markandya (UK/Spain), David L. McCollum (USA/Austria), Richard Millar (UK), Malte Meinshausen (Germany/Australia), Alexander Popp (Germany), Joana Correia de Oliveira de Portugal Pereira (Portugal/UK), Pallav Purohit (India/Austria), Keywan Riahi (Austria), Aurélien Ribes (France), Harry Saunders (Canada/USA), Christina Schädel (Switzerland/USA), Chris Smith (UK), Pete Smith (UK), Evelina Trutnevyte (Lithuania/Switzerland), Yang Xiu (China), Kirsten Zickfeld (Germany/Canada), Wenji Zhou (China/Austria)

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO 2 , nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a "SQLite" relational database or "ASCII" flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model setup , calibration and evaluation.

Purpose of Review This paper assesses social science research relating to BECCS and considers the applicability of research on CCS to BECCS. Recent Findings In recent years, social science research on CCS and BECCS has gone beyond an evaluation of public acceptance to provide a more nuanced analysis of the wider social political, ethical, and governance contexts in which large-scale deployment might be achieved. This raises issues at global, local, and regional scales, requiring a wide array of methods and approaches. Summary Awareness of the scale and urgency needed to act on climate change is growing and the role of BECCS in delivering carbon dioxide removal forms a central argument for the use of this family of technologies. Here, framing becomes a critical factor in how society responds to BECCS technologies and we argue that making the case for BECCS as a means of extending mitigation to make a ‘net zero’ goal achievable could be the key to its acceptable and sustainable deploy...

Biomass Energy with Carbon Capture and Storage (BECCS) is heavily relied upon in scenarios of future emissions that are consistent with limiting global mean temperature increase to 1.5 • C or 2 • C above pre-industrial. These temperature limits are defined in the Paris Agreement in order to reduce the risks and impacts of climate change. Here, we explore the use of BECCS technologies in a reference scenario and three low emission scenarios generated by an integrated assessment model (IMAGE). Using these scenarios we investigate the feasibility of key implicit and explicit assumptions about these BECCS technologies, including biomass resource, land use, CO 2 storage capacity and carbon capture and storage (CCS) deployment rate. In these scenarios, we find that half of all global CO 2 storage required by 2100 occurs in USA, Western Europe, China and India, which is compatible with current estimates of regional CO 2 storage capacity. CCS deployment rates in the scenarios are very challenging compared to historical rates of fossil, renewable or nuclear technologies and are entirely dependent on stringent policy action to incentivise CCS. In the scenarios, half of the biomass resource is derived from agricultural and forestry residues and half from dedicated bioenergy crops grown on abandoned agricultural land and expansion into grasslands (i.e. land for forests and food production is protected). Poor governance of the sustainability of bioenergy crop production can significantly limit the amount of CO 2 removed by BECCS, through soil carbon loss from direct and indirect land use change. Only one-third of the bioenergy crops are grown in regions associated with more developed governance frameworks. Overall, the scenarios in IMAGE are ambitious but consistent with current relevant literature with respect to assumed biomass resource, land use and CO 2 storage capacity.

This paper explores the role and implications of bio-energy with carbon capture and storage (BECCS) for addressing the climate change mitigation challenge. Framed within the context of the latest emissions budgets, and their associated uncertainty, we present a summary of the contribution of BECCS within the Integrated Assessment Model (IAM) scenarios used by the climate change community. Within this discussion we seek to shed light on two important areas. Firstly, that BECCS is a central, but often hidden element of many of the modelling work that underpins climate policy from the global to the national scale. The second area we address are the assumptions for BECCS embedded within IAM models, and the wider system consequences of these implied levels of deployment. In light of these challenges, we question whether BECCS can deliver what is anticipated of it within existing climate change policy.

This chapter assesses mitigation pathways consistent with limiting warming to 1.5°C above preindustrial levels. In doing so, it explores the following key questions: What role do CO2 and non-CO2 emissions play? {2.2, 2.3, 2.4, 2.6} To what extent do 1.5°C pathways involve overshooting and returning below 1.5°C during the 21st century? {2.2, 2.3} What are the implications for transitions in energy, land use and sustainable development? {2.3, 2.4, 2.5} How do policy frameworks affect the ability to limit warming to 1.5°C? {2.3, 2.5} What are the associated knowledge gaps? {2.6} The assessed pathways describe integrated, quantitative evolutions of all emissions over the 21st century associated with global energy and land use, and the world economy. The assessment is contingent upon available integrated assessment literature and model assumptions, and is complemented by other studies with different scope, for example those focusing on individual sectors. In recent years, integrated mitigation studies have improved the characterizations of mitigation pathways. However, limitations remain, as climate damages, avoided impacts, or societal co-benefits of the modelled transformations remain largely unaccounted for, while concurrent rapid technological changes, behavioural aspects, and uncertainties about input data present continuous challenges. (high confidence) {2.1.3, 2.3, 2.5.1, 2.6, Technical Annex 2} The chances of limiting warming to 1.5°C and the requirements for urgent action 1.5°C-consistent pathways can be identified under a range of assumptions about economic growth, technology developments and lifestyles. However, lack of global cooperation, lack of governance of the energy and land transformation, and growing resource-intensive consumption are key impediments for achieving 1.5°C-consistent pathways. Governance challenges have been related to scenarios with high inequality and high population growth in the 1.5°C pathway literature. {2.3.1, 2.3.2, 2.5} Under emissions in line with current pledges under the Paris Agreement (known as Nationally-Determined Contributions or NDCs), global warming is expected to surpass 1.5°C, even if they are supplemented with very challenging increases in the scale and ambition of mitigation after 2030 (high confidence). This increased action would need to achieve net zero CO2 emissions in less than 15 years. Even if this is achieved, temperatures remaining below 1.5°C would depend on the geophysical response being towards the low end of the currently-estimated uncertainty range. Transition challenges as well as identified trade-offs can be reduced if global emissions peak before 2030 and already achieve marked emissions reductions by 2030 compared to today. 1 {2.2, 2.3.5, Cross-Chapter Box 9 in Chapter 4} Limiting warming to 1.5°C depends on greenhouse gas (GHG) emissions over the next decades, where lower GHG emissions in 2030 lead to a higher chance of peak warming being kept to 1.5°C (high confidence). Available pathways that aim for no or limited (0-0.2°C) overshoot of 1.5°C keep GHG emissions in 2030 to 25-30 GtCO2e yr-1 in 2030 (interquartile range). This contrasts with median estimates for current NDCs of 50-58 GtCO2e yr-1 in 2030. Pathways that aim for limiting warming to 1.5°C by 2100 after a temporary temperature overshoot rely on large-scale deployment of Carbon Dioxide Removal (CDR) measures, which are uncertain and entail clear risks. {2.2, 2.3.3, 2.3.5, 2.5.3, Cross-Chapter Boxes 6 in Chapter 3 and 9 in Chapter 4, 4.3.7} Limiting warming to 1.5°C implies reaching net zero CO2 emissions globally around 2050 and concurrent deep reductions in emissions of non-CO2 forcers, particularly methane (high confidence). Such mitigation pathways are characterized by energy-demand reductions, decarbonisation of electricity and other fuels, electrification of energy end use, deep reductions in agricultural emissions, and some form of CDR with carbon storage on land or sequestration in geological reservoirs. Low energy demand and low demand for land-and GHG-intensive consumption goods facilitate limiting warming to as close as possible to 1.5°C. {2.2.2, 2.3.1, 2.3.5, 2.5.1, Cross-Chapter Box 9 in Chapter 4}. Final Government Draft Chapter 2 IPCC SR1.5 Do Not Cite, Quote or Distribute 2-5 Total pages: 113 In comparison to a 2°C limit, required transformations to limit warming to 1.5°C are qualitatively similar but more pronounced and rapid over the next decades (high confidence). 1.5°C implies very ambitious, internationally cooperative policy environments that transform both supply and demand (high confidence). {2.3, 2.4, 2.5} Policies reflecting a high price on emissions are necessary in models to achieve cost-effective 1.5°Cconsistent pathways (high confidence). Other things being equal, modelling suggests the price of emissions for limiting warming to 1.5°C being about three four times higher compared to 2°C, with large variations across models and socioeconomic assumptions. A price on carbon can be imposed directly by carbon pricing or implicitly by regulatory policies. Other policy instruments, like technology policies or performance standards, can complement carbon pricing in specific areas. {2.5.1, 2.5.2, 4.4.5} Limiting warming to 1.5°C requires a marked shift in investment patterns (limited evidence, high agreement). Investments in low-carbon energy technologies and energy efficiency would need to approximately double in the next 20 years, while investment in fossil-fuel extraction and conversion decrease by about a quarter. Uncertainties and strategic mitigation portfolio choices affect the magnitude and focus of required investments. {2.5.2} Future emissions in 1.5°C-consistent pathways Mitigation requirements can be quantified using carbon budget approaches that relate cumulative CO2 emissions to global-mean temperature increase. Robust physical understanding underpins this relationship, but uncertainties become increasingly relevant as a specific temperature limit is approached. These uncertainties relate to the transient climate response to cumulative carbon emissions (TCRE), non-CO2 emissions, radiative forcing and response, potential additional Earth-system feedbacks (such as permafrost thawing), and historical emissions and temperature. {2.2.2, 2.6.1} Cumulative CO2 emissions are kept within a budget by reducing global annual CO2 emissions to netzero. This assessment suggests a remaining budget for limiting warming to 1.5°C with a two-thirds chance of about 550 GtCO2, and of about 750 GtCO2 for an even chance (medium confidence). The remaining carbon budget is defined here as cumulative CO2 emissions from the start of 2018 until the time of net-zero global emissions. Remaining budgets applicable to 2100, would approximately be 100 GtCO2 lower than this to account for permafrost thawing and potential methane release from wetlands in the future. These estimates come with an additional geophysical uncertainty of at least ±50%, related to non-CO2 response and TCRE distribution. In addition, they can vary by ±250 GtCO2 depending on non-CO2 mitigation strategies as found in available pathways. {2.2.2, 2.6.1} Staying within a remaining carbon budget of 750 GtCO2 implies that CO2 emissions reach carbon neutrality in about 35 years, reduced to 25 years for a 550 GtCO2 remaining carbon budget (high confidence). The ±50% geophysical uncertainty range surrounding a carbon budget translates into a variation of this timing of carbon neutrality of roughly ±15-20 years. If emissions do not start declining in the next decade, the point of carbon neutrality would need to be reached at least two decades earlier to remain within the same carbon budget. {2.2.2, 2.3.5} Non-CO2 emissions contribute to peak warming and thus affect the remaining carbon budget. The evolution of methane and sulphur dioxide emissions strongly influences the chances of limiting warming to 1.5°C. In the near-term, a weakening of aerosol cooling would add to future warming, but can be tempered by reductions in methane emissions (high confidence). Uncertainty in radiative forcing estimates (particularly aerosol) affects carbon budgets and the certainty of pathway categorizations. Some non-CO2 forcers are emitted alongside CO2, particularly in the energy and transport sectors, and can be largely addressed through CO2 mitigation. Others require specific measures, for example to target agricultural N2O and CH4, some sources of black carbon, or hydrofluorocarbons (high confidence). In many cases, non-CO2 emissions reductions are similar in 2°C pathways, indicating reductions near their assumed maximum potential by integrated assessment models. Emissions of N2O and NH3 increase in some pathways with strongly increased bioenergy demand.

Dimethylsulfide (DMS), outgassed from ocean waters, plays an important role in the climate system, as it oxidizes to methane sulfonic acid (MSA) and sulfur dioxide (SO 2), which can lead to the formation of sulfate aerosol. Newly formed sulfate aerosol resulting from DMS oxidation may grow by condensation of gases, in-cloud oxidation, and coagulation to sizes where they may act as cloud condensation nuclei (CCN) and influence cloud properties. Under future global warming conditions, sea ice in the Arctic region is expected to decline significantly, which may lead to increased emissions of DMS from the open ocean and changes in cloud regimes. In this study we evaluate impacts of DMS on Arctic sulfate aerosol budget, changes in cloud droplet number concentration (CDNC), and cloud radiative forcing in the Arctic region under current and future sea ice conditions using an atmospheric global climate model. Given that future DMS concentrations are highly uncertain, several simulations with different surface seawater DMS concentrations and spatial distributions in the Arctic were performed in order to determine the sensitivity of sulfate aerosol budgets, CDNC, and cloud radiative forcing to Arctic surface seawater DMS concentrations. For any given amount and distribution of Arctic surface seawater DMS, similar amounts of sulfate are produced by oxidation of DMS in 2000 and 2050 despite large increases in DMS emission in the latter period due to sea ice retreat in the simulations. This relatively low sensitivity of sulfate burden is related to enhanced sulfate wet removal by precipitation in 2050. However simulated aerosol nucleation rates are higher in 2050, which results in an overall increase in CDNC and substantially more negative cloud radiative forcing. Thus potential future reductions in sea ice extent may cause cloud albedos to increase, resulting in a negative climate feedback on radiative forcing in the Arctic associated with ocean DMS emissions.

Biogeosciences and Forestry Biogeosciences and Forestry Short-time effect of harvesting methods on soil respiration dynamics in a beech forest in southern Mediterranean Italy Vittoria Coletta (1) , Gaetano Pellicone (2) , Vincenzo Bernardini (3) , Bruno De Cinti (4) , Raffaele Froio (2) , Pasquale A Marziliano (1) , Giorgio Matteucci (2) , Nicola Ricca (2) , Rosario Turco (3) , Antonella Veltri (2) CO2 fluxes from soil, together with soil water content and temperature have been measured over one solar year in an even-aged beech forest (Fagus Sylvatica L.) in southern Italy. We investigated the effects of three different harvested biomass removal treatments (traditional, innovative, unharvested control) on soil respiration (Rs) in three plots from May 2014 to April 2015, with the aim to evaluate the effects of such silvicultural practices on the CO2 respired from the forest floor. The influence of soil temperature and soil moisture on soil respiration was also analysed. Rs showed large variations among the treatments, with the innovative treatment resulting in significantly higher soil respiration than control and traditional treatments. There were no significant differences in soil temperature between the treatments, whereas soil water content was statistically different only in the innovative treatment. The study showed that the mean soil respiration increased with thinning intensity, confirming that after harvesting, residues remaining on the forest floor and decomposing roots may contribute to raise soil respiration, due to the higher microbial activity.

Implementing the 17 United Nations Sustainable Development Goals (SDGs) requires meeting 169 targets at the municipality level. Meanwhile, municipalities also have issues that they should address for residents. Small municipalities may lack access to the necessary human resources and funds to treat new issues regarding SDGs. In this study, new ideas for localizing the goals and targets for connecting municipalitiesʼ policies were proposed. First, the relationships among forest management policies and the national SDGs were investigated in Kobe, Japan as a case study. Using expert judgement, 11 goals and 20 targets regarding forest management policies were extracted. Next, as the extracted goals and targets include many foci, selected goals and targets were translated into descriptive sentences that the municipalities could easily apply to their forest management policies. The relationship among Kobeʼs forest management policies and national SDGs was visualized through these processes. In addition, the relative importance of each goal was weighted using a questionnaire and thinking of a pairwise comparison to clarify the priorities of goals based on the summed consciousness of Kobe residents. The result revealed that water resources and biodiversity were significant goals for the residents.

Reply to 'Interpretations of the Paris climate target' Millar et al. reply-Our paper aimed to remain as consistent as possible with the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) definitions that have informed the United Nations Framework Convention on Climate Change (UNFCCC) negotiations. The definition of global average temperature in the Paris Agreement is undoubtedly important, and different interpretations are possible, as acknowledged in our paper. However, the Paris Agreement built on the reports of Working Group I and II 1,2 of the IPCC AR5. In these reports, global temperature change was explicitly defined using the observations in the period 1850-1900 as "an approximation of preindustrial levels" (Fig. 1 of ref. 2). Climate model projections were assessed relative to 1986-2005 and then expressed relative to 1850-1900 using observed warming between these periods in the HadCRUT4 dataset 3 (+ 0.61 °C). Based on the IPCC-AR5-assessed 4 near-term projections of a warming of 0.3-0.7 °C for the period 2016-2035 compared to 1986-2005, warming in the decade 2010-2019 is expected to be centred on 0.93 °C above 1850-1900, given forcing consistent with the representative concentration pathways and no large volcanic eruptions. Such a level of warming is consistent with the "increase of 0.85 °C [to 2012] since 1880, a good approximation for pre-industrial levels" reported in the Structured Expert Dialogue (SED) 5-dashed light blue line in Fig. 2 of Schurer et al. 6-and with the independent estimate for 2015 human-induced warming used in our paper 7. Alternative definitions of global average temperature or preindustrial conditions may not be consistent with "observed impacts of climate change at 0.85 °C of warming" 5 (original emphasis) in the context of which the UNFCCC longterm temperature goal was agreed-over the period 2006-2015, warming (relative to 1850-1900) in datasets that stretch back to 1850 are: 0.84 °C (HadCRUT4), 0.92 °C (HadCRUT4: Cowtan and Way) and 1.00 °C (Berkeley Earth). We aimed to remain as consistent as possible with the IPCC-AR5 definitions that have informed

To assess the degree to which it has met its commitments under the Paris Agreement, Morocco is called upon to carry out carbon assessments and transparent evaluations. Within the forestry sector, little is known about the role of Morocco's forests in contributing to carbon uptake. With this aim, we applied for the first time in literature the 3-PG model to Cedrus atlantica ((Endl.) Manetti ex Carrière, 1855), which represents about 131.800 ha of Morocco's forest area (i.e. Azrou forest). Through the Differential Evolution-Markov Chains (DE-MC) we tested and assessed the sensitivity and calibrated the 3-PG model. This process-based model provided significant results regarding the carbon sequestration capacity. The results showed the following: i-Parameters related to stand properties, canopy structure, and processes, as well as biomass partitioning, are the most important or sensitive for the performance of the model; ii-The DE-MC method optimized the values of the 3-PG parameters which was confirmed by the means of Gelman-Rubin convergence test; iii-According to the predictions of the calibrated 3-PG, the Net Primary Production in the pure Azrou forest varies between 0.32 and 7.88 tC.ha −1 .yr −1 , it is equal in average to 4.9 tC.ha −1 .yr −1 , which given the total area corresponds to 7078 tC.yr −1 .

Forests and wood products play a major role in climate change mitigation strategies and the transition from a fossil-based economy to a circular bioeconomy. Accurate estimates of future forest productivity are crucial to predict the carbon sequestration and wood provision potential of forests. Since long, forest managers have used empirical yield tables as a cost-effective and reliable way to predict forest growth. However, recent climate change-induced growth shifts raised doubts about the long-term validity of these yield tables. In this study, we propose a methodology to improve available yield tables of 11 tree species in the Netherlands and Flanders, Belgium. The methodology uses scaling functions derived from climate-sensitive process-based modelling (PBM) that reflect state-of-the-art projections of future growth trends. Combining PBM and stand information from the empirical yield tables for the region of Flanders, we found that for the period 1987-2016 stand productivity has on average increased by 13% compared to 1961-1990. Furthermore, simulations indicate that this positive growth trend is most likely to persist in the coming decades, for all considered species, climate or site conditions. Nonetheless, results showed that local site variability is equally important to consider as the in-or exclusion of the CO2 fertilization effect or different climate projections, when assessing the magnitude of forests' response to climate change. Our projections suggest that incorporating these climate change-related productivity changes lead to a 7% increase in standing stock and a 22% increase in sustainably potentially harvestable woody biomass by 2050. The proposed methodology and resulting estimates of climate-sensitive projections of future woody biomass stocks will facilitate the further incorporation of forests and their products in global and regional strategies for the transition to a climate-smart circular bioeconomy.

Contributing Authors: Katherine Calvin (USA), Oreane Edelenbosch (Netherlands), Johannes Emmerling (Germany/Italy), Sabine Fuss (Germany), Thomas Gasser (France/Austria), Nathan Gillet (Canada), Chenmin He (China), Edgar Hertwich (Austria/USA), Lena Höglund-Isaksson (Sweden/Austria), Daniel Huppmann (Austria), Gunnar Luderer (Germany), Anil Markandya (UK/Spain), David L. McCollum (USA/Austria), Richard Millar (UK), Malte Meinshausen (Germany/Australia), Alexander Popp (Germany), Joana Correia de Oliveira de Portugal Pereira (Portugal/UK), Pallav Purohit (India/Austria), Keywan Riahi (Austria), Aurélien Ribes (France), Harry Saunders (Canada/USA), Christina Schädel (Switzerland/USA), Chris Smith (UK), Pete Smith (UK), Evelina Trutnevyte (Lithuania/Switzerland), Yang Xiu (China), Kirsten Zickfeld (Germany/Canada), Wenji Zhou (China/Austria)

Considering the ambitious climate targets of the Paris Agreement to limit global warming to 2°C, with aspirations of even 1.5°C, questions arise on how to achieve this. Climate geoengineering has been proposed as a potential tool to minimize global harm from anthropogenic climate change. Here, an Earth system model is used to evaluate the climate response when transferring from a high CO2forcing scenario, RCP8.5, to a middle-of-the-road forcing scenario, like RCP4.5, using aerosol geoengineering. Three different techniques are considered: stratospheric aerosol injections (SAI), marine sky brightening (MSB), and cirrus cloud thinning (CCT). The climate states appearing in the climate geoengineering cases are found to be closer to RCP4.5 than RCP8.5 and many anthropogenic global warming symptoms are alleviated. All three techniques result in comparable global mean temperature evolutions. However, there are some notable differences in other climate variables due to the nature of the fo...

The atmospheric concentration of CO 2 increased from 190 to 280 ppm between the last glacial maximum 21,000 years ago and the pre-industrial era 1,2. This CO 2 rise and its timing have been linked to changes in the Earth's orbit, ice sheet configuration and volume, and ocean carbon storage 2,3. The

Two decades of measurements of spectral reflectance of solar radiation at the top of the atmosphere and a complementary record of cloud properties from satellite passive remote sensing have been analyzed for their pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of brightness, which is explained by the retreat of sea ice during the current warming period, is not compensated by a corresponding increase in cloud cover. A systematic change in the thermodynamic phase of clouds has taken place, shifting towards the liquid phase at the expense of the ice phase. Without significantly changing the total cloud optical thickness or the mass of condensed water in the atmosphere, liquid water content has increased, resulting in positive trends in liquid cloud optical thickness and albedo. This leads to a cooling trend by clouds being superimposed on top of the pan-Arctic amplified warming, induced by the anthropogenic release of greenhouse gases, the ice-albedo feedback, and related effects. Except over the permanent and parts of the marginal sea ice zone around the Arctic Circle, the rate of surface cooling by clouds has increased, both in spring (−32 % in total radiative forcing for the whole Arctic) and in summer (−14 %). The magnitude of this effect depends on both the underlying surface type and changes in the regional Arctic climate.

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In the Anthropocene, social processes have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling are needed to address these challenges, but the current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth System Models, to hybrid macroeconomic Integrated Assessments Models, to a plethora of models of socio-cultural dynamics. World-Earth models, currently not yet available, will need to integrate all these elements, so future World-Earth modellers require a structured approach to identify, classify, select, and combine model components. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e., the usual components of Earth system models), (ii) socio-cultural, dominated by processes of human behaviour, decision making and collective social dynamics (e.g., politics, institutions, social networks), and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g., human bodies, natural resource and agriculture). We show how higher-order taxonomies for interactions between two or more subsystems can be derived, highlighting the kinds of social-ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World-Earth system model of socially transmitted discount rates in a greenhouse gas emissions game to illustrate the effects of social-ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World-Earth models for 1

The degree to which elevated CO 2 concentrations (e[CO 2 ]) increase the amount of carbon (C) assimilated by vegetation plays a key role in climate change. However, due to the short-term nature of CO 2 enrichment experiments and the lack of reconciliation between different ecological scales, the effect of e[CO 2 ] on plant biomass stocks remains a major uncertainty in future climate projections. Here, we review the effect of e[CO 2 ] on plant biomass across multiple levels of ecological organization, scaling from physiological responses to changes in population-, community-, ecosystem-, and global-scale dynamics. We find that evidence for a sustained biomass response to e[CO 2 ] varies across ecological scales, leading to diverging conclusions about the responses of individuals, populations, communities, and ecosystems. While the distinct focus of every scale reveals new mechanisms driving biomass accumulation under e[CO 2 ], none of them provides a full picture of all relevant processes. For example, This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of two model intercomparison projects: GeoMIP (Geoengineering Model Intercomparison Project) and IMPLICC (EU project "Implications and risks of engineering solar radiation to limit climate change"). In G1, the radiative forcing from an instantaneous quadrupling of the CO 2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged compared to the control simulation, the meridional temperature gradient is reduced in all models. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. In comparison to the climate response to a quadrupling of CO 2 alone, the temperature responses are small in experiment G1. Precipitation responses are, however, in many regions of comparable magnitude but globally of opposite sign.

The Paris Agreement has set stringent temperature targets to limit global warming to 2°C above preindustrial level, with efforts to stay well below 2°C. At the same time, its bottom-up approach with voluntary national contributions makes the implementation of these ambitious targets particularly challenging. Climate engineering-both through carbon dioxide removal (CDR) and solar radiation management (SRM)-is currently discussed to potentially complement mitigation and adaptation. Results from integrated assessment models already suggest a significant role for some forms of climate engineering in achieving stringent climate objectives1. However, these estimates and their underlying assumptions are uncertain and currently heavily debated2-4. By reviewing the existing literature and reporting the views of experts, we identify research gaps and priorities for improving the integrated assessment of climate engineering. Results point to differentiated roles of CDR and SRM as complementary strategies to the traditional ones, as well as diverse challenges for an adequate representation in integrated assessment models. We identify potential synergies for model development which can help better represent mitigation and adaptation challenges, as well as climate engineering. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 703399 for the project 'Robust Policy'. The results presented here reflect only the authors' view and FEEM is not responsible for any use that may be made of the information it contains.

The potential effect of climate change on regional suitability for cocoa cultivation is a serious economic concern for West Africa—especially for Ghana and Côte d’Ivoire, whose cocoa cultivation accounts for respectively ∼19% and ∼45% of world production. Here, we present a modelling and observational study of cocoa net primary productivity (NPP) in present day and future West African climates. Our analysis uses a data assimilation technique to parameterise a process-based land-surface model. The parameterisation is based on laboratory observations of cocoa, grown under both ambient and elevated CO2. Present day and end of 21st century cocoa cultivation scenarios are produced by driving the parameterised land-surface model with output from a high-resolution climate model. This represents a significant advance on previous work, because unlike the CMIP5 models, the high-resolution model used in this study accurately captures the observed precipitation seasonality in the cocoa-growing ...

Economic evaluations of solar radiation management (SRM) usually assume that the temperature will be stabilized, with no economic impacts of climate change, but with possible side-effects. We know from experiments with climate models, however, that unlike emission control the spatial and temporal distributions of temperature, precipitation and wind conditions will change. Hence, SRM may have economic consequences under a stabilization of global mean temperature even if side-effects other than those related to the climatic responses are disregarded. This paper addresses the economic impacts of implementing two SRM technologies; stratospheric sulfur injection and marine cloud brightening. By the use of a computable general equilibrium model, we estimate the economic impacts of climatic responses based on the results from two earth system models, MPI-ESM and NorESM. We find that under a moderately increasing greenhouse-gas concentration path, RCP4.5, the economic benefits of implementi...