Search

Our paper explores the implication of climate mitigation policy and electricity generation technology performance for capital investment demands by the electric power sector on near term to century time scales. We find that stabilizing GHG emissions will require additional investment in the electricity generation sector over and above investments that would be needed in the absence of climate policy, in the range of 15 to 29 trillion US$ (48–94%) depending on the stringency of climate policy during the period 2015 to 2095 under default technology assumptions. This increase reflects the higher capital intensity of power systems that control emissions as well as increased electrification of the global economy. Limits on the penetration of nuclear and carbon capture and storage technology could increase costs substantially. Energy efficiency improvements can reduce the investment requirement by 18 to 24 trillion US$ (compared to default technology climate policy assumptions), depending on climate policy scenario. We also highlight the implications of different technology evolution scenarios for different regions. Under default technology set, the heaviest investments across scenarios in power generation were observed in China, India, SE Asia and Africa regions with the latter three regions dominating in the second half of the 21st century.

Climate projections depend on scenarios of fossil fuel emissions and land use change, and the Intergovernmental Panel on Climate Change (IPCC) AR5 parallel process assumes consistent climate scenarios across integrated assessment and earth system models (IAMs and ESMs). The CMIP5 (Coupled Model Intercomparison Project Phase 5) project used a novel "land use harmonization" based on the Global Land use Model (GLM) to provide ESMs with consistent 1500–2100 land use trajectories generated by historical data and four IAMs. A direct coupling of the Global Change Assessment Model (GCAM), GLM, and the Community ESM (CESM) has allowed us to characterize and partially address a major gap in the CMIP5 land coupling design: the lack of a corresponding land cover harmonization. For RCP4.5, CESM global afforestation is only 22% of GCAM's 2005 to 2100 afforestation. Likewise, only 17% of GCAM's 2040 afforestation, and zero pasture loss, were transmitted to CESM within the directly coupled model. This is a problem because GCAM relied on afforestation to achieve RCP4.5 climate stabilization. GLM modifications and sharing forest area between GCAM and GLM within the directly coupled model did not increase CESM afforestation. Modifying the land use translator in addition to GLM, however, enabled CESM to include 66% of GCAM's afforestation in 2040, and 94% of GCAM's pasture loss as grassland and shrubland losses. This additional afforestation increases CESM vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, which demonstrates that CESM without additional afforestation simulates a different RCP4.5 scenario than prescribed by GCAM. Similar land cover inconsistencies exist in other CMIP5 model results, primarily because land cover information is not shared between models. Further work to harmonize land cover among models will be required to increase fidelity between IAM scenarios and ESM simulations and realize the full potential of scenario-based earth system simulations.

Human activities are significantly altering biogeochemical cycles at the global scale, and the scope of these activities will change with both future climate and socioeconomic decisions. This poses a significant challenge for Earth system models (ESMs), which can incorporate land use change as prescribed inputs but do not actively simulate the policy or economic forces that drive land use change. One option to address this problem is to couple an ESM with an economically oriented integrated assessment model, but this is challenging because of the radically different goals and underpinnings of each type of model. This study describes the development and testing of a coupling between the terrestrial carbon cycle of an ESM (CESM) and an integrated assessment (GCAM) model, focusing on how CESM climate effects on the carbon cycle could be shared with GCAM. We examine the best proxy variables to share between the models, and we quantify how carbon flux changes driven by climate, CO2 fertilization, and land use changes (e.g., deforestation) can be distinguished from each other by GCAM. The net primary production and heterotrophic respiration outputs of the Community Land Model (CLM), the land component of CESM, were found to be the most robust proxy variables by which to recalculate GCAM's assumptions of equilibrium ecosystem steady-state carbon. Carbon cycle effects of land use change are spatially limited relative to climate effects, and thus we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. This paper does not present results of a fully coupled simulation but shows, using a series of offline CLM simulations and an additional idealized Monte Carlo simulation, that our CESM–GCAM proxy variables reflect the phenomena that we intend and do not contain erroneous signals due to land use change. By allowing climate effects from a full ESM to dynamically modulate the economic and policy decisions of an integrated assessment model, this work will help link these models in a robust and flexible framework capable of examining two-way interactions between human and Earth system processes.

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community-integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W m−2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095, particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase, driven by higher water demands for bio-energy crops.

The EU has established an aggressive portfolio with explicit near-term targets for 2020 – to reduce GHG emissions by 20%, rising to 30% if the conditions are right, to increase the share of renewable energy to 20%, and to make a 20% improvement in energy efficiency – intended to be the first step in a long-term strategy to limit climate forcing. The effectiveness and cost of extending these measures in time are considered along with the ambition and propagation to the rest of the world. Numerical results are reported and analysed for the contribution of the portfolio's various elements through a set of sensitivity experiments. It is found that the hypothetical programme leads to very substantial reductions in GHG emissions, dramatic increases in use of electricity, and substantial changes in land-use including reduced deforestation, but at the expense of higher food prices. The GHG emissions reductions are driven primarily by the direct limits. Although the carbon price is lower under the hypothetical pro...

We explore the implications of potentially counteractive greenhouse gas mitigation responses to carbon prices and the complications that could ensue for limiting radiative forcing in the near-term. Specifically we consider the problem of reproducing the radiative forcing pathway for Representative Concentration Pathway, RCP4.5, which stabilizes radiative forcing at 4.5 W m − 2 (650 ppm CO 2 -e) under a different terrestrial policy assumption. We show that if indirect land-use change emissions are not priced, carbon prices that can replicate this pathway in the near-term may not exist. We further show that additional complexities could emerge as a consequence of the co-production of CO 2 and sulfur emissions as byproducts of fossil fuel combustion.

Three potential future scenarios of expanded global biofuel production are presented here utilizing the GCAM integrated assessment model. These scenarios span a range that encompasses on the low end a continuation of existing biofuel production policies to two scenarios that would require an expansion of current targets as well as an extension of biofuels targets to other regions of the world. Conventional oil use is reduced by 4–8% in the expanded biofuel scenarios, which results in a decrease of in CO2 emissions on the order of 1–2 GtCO2/year by mid-century from the global transportation sector. The regional distribution of crop production is relatively unaffected, but the biofuels targets do result in a marked increase in the production of conventional crops used for energy. Producer prices of sugar and corn reach levels about 12% and 7% above year 2005 levels, while the increased competition for land causes the price of food crops such as wheat, although not used for bioenergy in this study, to increase by 1–2%. The amount of land devoted to growing all food crops and dedicated bioenergy crops is increased by about 10% by 2050 in the High biofuel case, with concurrent decreases in other uses of land such as forest and pasture. In both of the expanded biofuels cases studied, there is an increase in net cumulative carbon emissions for the first couple of decades due to these induced land use changes. However, the difference in net cumulative emissions from the biofuels expansion decline by about 2035 as the reductions in energy system emissions exceed further increases in emissions from land use change. Even in the absence of a policy that would limit emissions from land use change, the differences in net cumulative emissions from the biofuels scenarios reach zero by 2050, and are decreasing further over time in both cases.

This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the representative concentration pathways (RCPs). We build on the recently completed Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to the GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6 W/m2 in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.

In this paper, we assess future water demands for the agricultural (irrigation and livestock), energy (electricity generation, primary energy production and processing), industrial (manufacturing and mining), and municipal sectors, by incorporating water demands into a technologically-detailed global integrated assessment model of energy, agriculture, and climate change � the Global Change Assessment Model (GCAM). Base-year water demands � both gross withdrawals and net consumptive use � are assigned to specific modeled activities in a way that maximizes consistency between bottom-up estimates of water demand intensities of specific technologies and practices, and top-down regional and sectoral estimates of water use. The energy, industrial, and municipal sectors are represented in fourteen geopolitical regions, with the agricultural sector further disaggregated into as many as eighteen agro-ecological zones (AEZs) within each region. We assess future water demands representing six socioeconomic scenarios, with no constraints imposed by future water supplies. The scenarios observe increases in global water withdrawals from 3710 km3 year- 1 in 2005 to 6195�8690 km3 year- 1 in 2050, and to 4869�12,693 km3 year- 1 in 2095. Comparing the projected total regional water withdrawals to the historical supply of renewable freshwater, the Middle East exhibits the highest levels of water scarcity throughout the century, followed by India; water scarcity increases over time in both of these regions. In contrast, water scarcity improves in some regions with large base-year electric sector withdrawals, such as the USA and Canada, due to capital stock turnover and the almost complete phase-out of once-through flow cooling systems. The scenarios indicate that: 1) water is likely a limiting factor in meeting future water demands, 2) many regions can be expected to increase reliance on non-renewable groundwater, water reuse, and desalinated water, but they also highlight an important role for development and deployment of water conservation technologies and practices.

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicator Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.

'gcamland v1.0' is an open source R package that was built to allocate land across a variety of uses based on changes in agricultural yield and commodity price. The land allocation algorithm is based on the one included in the Global Change Assessment Model (GCAM). 'gcamland v1.0' includes the ability to run in a historical mode, enabling model validation and parameter estimation, or in a future mode, simulating changes in land use/land cover in the future. For both modes, 'gcamland v1.0' can run a single simulation or a large ensemble of simulations with different parameters. When ensembles are generated in the historical mode, 'gcamland v1.0' calculates the likelihood of a given parameter set by comparing to observational data. 'gcamland v1.0' is publicly available via GitHub and has can be adjusted to represent alternative scenarios or configured to different regions and land types. Funding statement: This research was supported by the Office of Science of the U.S. Department of Energy as part of the Multi-Sector Dynamics Program. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830.

The increasing data requirements of complex models demand robust, reproducible, and transparent systems to track and prepare models’ inputs. Here we describe version 1.0 of the gcamdata R package that processes raw inputs to produce the hundreds of XML files needed by the GCAM integrated human-earth systems model. It features extensive functional and unit testing, data tracing and visualization, and enforces metadata, documentation, and flexibility in its component data-processing subunits. Although this package is specific to GCAM, many of its structural pieces and approaches should be broadly applicable to, and reusable by, other complex model/data systems aiming to improve transparency, reproducibility, and flexibility. Funding statement: Primary support for this work was provided by the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program. Additional support was provided by the U.S. Department of Energy Offices of Fossil Energy, Nuclear Energy, and Energy Efficiency and Renewable Energy and the U.S. Environmental Protection Agency.

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.

Many papers have shown that bioenergy and land-use are potentially important elements in a strategy to limit anthropogenic climate change. But, significant expansion of bioenergy production can have a large terrestrial footprint. In this paper, we test the implications for land use, the global energy system, emissions and mitigation costs of meeting a specific climate target, using a single fossil fuel and industrial sector policy instrument, but with five alternative bioenergy and land-use policy architectures. These scenarios are illustrative in nature, and designed to explore trade-offs. We find that the policies we examined have differing effects on the different segments of the economy. Comprehensive land policies can reduce land-use change emissions, increasing allowable emissions in the energy system, but have implications for the cost of food. Bioenergy penalties and constraints, on the other hand, have little effect on food prices, but result in less bioenergy and thus can increase mitigation costs and energy prices.

The magnitude and character of the global resource base of fossil fuels is a key determinant of the evolution of the future global energy system and corresponding fossil fuel carbon emissions. What is less well understood is the potential magnitude of impact of the availability of fossil fuels, due to the interaction with biomass energy, on agriculture, land use, ecosystems and therefore carbon emissions from land-use change. This paper explores these links and implications. We show that if oil resources are limited, then the consequently higher price for liquids induces both the use of coal-to-liquids technology deployment, but also enhanced production of bioenergy crops particularly in a business-as-usual scenario. This in turn implies greater pressure to convert unmanaged ecosystems to produce bioenergy, and higher rates of terrestrial carbon emissions from land use.

While the international community has agreed on the long-term target of limiting global warming to no more than 2°C above pre-industrial levels, only a few concrete climate policies and measures to reduce greenhouse gas (GHG) emissions have been implemented.We use a set of three global integrated assessment models to analyze the implications of current climate policies on long-term mitigation targets. We define a weak-policy baseline scenario, which extrapolates the current policy environment by assuming that the global climate regime remains fragmented and that emission reduction efforts remain unambitious in most of the world’s regions. These scenarios clearly fall short of limiting warming to 2°C. We investigate the cost and achievability of the stabilization of atmospheric GHG concentrations at 450 ppm CO2e by 2100, when countries follow the weak policy pathway until 2020 or 2030 before pursuing the long-term mitigation target with global cooperative action. We find that after a deferral of ambitious action the 450 ppm CO2e is only achievable with a radical up-scaling of efforts after target adoption. This has severe effects on trans-formation pathways and exacerbates the challenges of climate stabilization, in particular for a delay of cooperative action until 2030. Specifically, reaching the target with weak near-term action implies (a) faster and more aggressive transformations of energy systems in the medium term, (b) more stranded investments in fossil-based capacities, (c) higher long-term mitigation costs and carbon prices and (d) stronger transitional economic impacts, rendering the political feasibility of such pathways questionable.

Proposed climate mitigation measures do not account for direct biophysical climate impacts of land-use change (LUC), nor do the stabilization targets modeled for phase 5 of the Coupled Model Intercomparison Project (CMIP5) representative concentration pathways (RCPs). To examine the significance of such effects on global and regional patterns of climate change, a baseline and an alternative scenario of future anthropogenic activity are simulated within the Integrated Earth System Model, which couples the Global Change Assessment Model, Global Land-Use Model, and Community Earth System Model. The alternative scenario has high biofuel utilization and approximately 50% less global forest cover than the baseline, standard RCP4.5 scenario. Both scenarios stabilize radiative forcing from atmospheric constituents at 4.5 W m−2 by 2100. Thus, differences between their climate predictions quantify the biophysical effects of LUC. Offline radiative transfer and land model simulations are also utilized to identify forcing and feedback mechanisms driving the coupled response. Boreal deforestation is found to strongly influence climate because of increased albedo coupled with a regional-scale water vapor feedback. Globally, the alternative scenario yields a twenty-first-century warming trend that is 0.5°C cooler than baseline, driven by a 1 W m−2 mean decrease in radiative forcing that is distributed unevenly around the globe. Some regions are cooler in the alternative scenario than in 2005. These results demonstrate that neither climate change nor actual radiative forcing is uniquely related to atmospheric forcing targets such as those found in the RCPs but rather depend on particulars of the socioeconomic pathways followed to meet each target.

Fossil resource endowments and the future development of fossil fuel prices are important factors that will critically influence the nature and direction of the global energy system. In this paper we analyze a multi-model ensemble of long-term energy and emissions scenarios that were developed within the framework of the EMF27 integrated assessment model intercomparison exercise. The diverse nature of these models highlights large uncertainties in the likely development of fossil resource (coal, oil, and natural gas) consumption, trade, and prices over the course of the twenty-first century and under different climate policy frameworks. We explore and explain some of the differences across scenarios and models and compare the scenario results with fossil resource estimates from the literature. A robust finding across the suite of IAMs is that the cumulative fossil fuel consumption foreseen by the models is well within the bounds of estimated recoverable reserves and resources. Hence, fossil resource constraints are, in and of themselves, unlikely to limit future GHG emissions this century. Our analysis also shows that climate mitigation policies could lead to a major reallocation of financial flows between regions, in terms of expenditures on fossil fuels and carbon, and can help to alleviate near-term energy security concerns via the reductions in oil imports and increases in energy system diversity they will help to motivate. Aggressive efforts to promote energy efficiency are, on their own, not likely to lead to markedly greater energy independence, however, contrary to the stated objectives of certain industrialized countries., JRC.J.1-Economics of Climate Change, Energy and Transport

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

International audience; Abstract. Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land–atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies, and quantifying the impacts of land cover change on the climate system. Here we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. This article is protected by copyright. All rights reserved.

Mexico’s climate policy sets ambitious national greenhouse gas (GHG) emission reduction targets—30% versus a business-as-usual baseline by 2020, 50% versus 2000 by 2050. However, these goals are at odds with recent energy and emission trends in the country. Both energy use and GHG emissions in Mexico have grown substantially over the last two decades. We investigate how Mexico might reverse current trends and reach its mitigation targets by exploring results from energy system and economic models involved in the CLIMACAP-LAMP project. To meet Mexico’s emission reduction targets, all modeling groups agree that decarbonization of electricity is needed, along with changes in the transport sector, either to more efficient vehicles or a combination of more efficient vehicles and lower carbon fuels. These measures reduce GHG emissions as well as emissions of other air pollutants. The models find different energy supply pathways, with some solutions based on renewable energy and others relying on biomass or fossil fuels with carbon capture and storage. The economy-wide costs of deep mitigation could range from 2% to 4% of GDP in 2030, and from 7% to 15% of GDP in 2050. Our results suggest that Mexico has some flexibility in designing deep mitigation strategies, and that technological options could allow Mexico to achieve its emission reduction targets, albeit at a cost to the country.

Impact Relevance and Usability of High Resolution Climate Modeling and Datasets; Aspen, Colorado, 2–7 August 2015

Human land-use activities have resulted in large to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past–future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and are there regional land-management strategies with promise to help mitigate and/or adapt to climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from land-use change relative to fossil fuel emissions, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use. LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to-. In this paper, we describe the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to experiments from the CMIP core, ScenarioMIP, and C4MIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model experiments designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request (primary and secondary land, crops, pasture, urban). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible.

Governments worldwide have agreed that international climate policy should aim to limit the increase of global mean temperature to less than 2°C with respect to pre-industrial levels. The purpose of this paper is to analyse the emission reductions and related energy system changes in various countries in pathways consistent with the 2°C target. We synthesize and provide an overview of the national and regional information contained in different scenarios from various global models published over the last few years, as well as yet unpublished scenarios submitted by modelling teams participating in the MILES project (Modelling and Informing Low-Emission Strategies). We find that emissions in the mitigation scenarios are significantly reduced in all regions compared to the baseline without climate policies. The regional cumulative CO2 emissions show on average a 76% reduction between the baseline and 450 scenario. The 450 scenarios show a reduction of primary energy demand in all countries of roughly 30-40% compared to the baseline. In the baseline scenario, the contribution of low-carbon energy technology remains around 15%, i.e. similar as today. In the mitigation scenario, these numbers are scaled up rapidly towards 2050. Looking at air quality, sulphur dioxide and black carbon emissions are strongly reduced as a co-benefit of greenhouse gas emission reductions, in both developing and developed countries. However, black carbon emissions increase in countries that strongly rely on bioenergy to reach mitigation targets. Concerning energy security, energy importing countries generally experience a decrease in net-energy imports in mitigation scenarios compared to the baseline development, while energy exporters experience a loss of energy export revenues.

We investigate the extent to which future energy transformation pathways meeting ambitious climate change mitigation targets depend on assumptions about economic growth and fossil fuel availability. The analysis synthesizes results from the RoSE multi-model study aiming to identify robust and sensitive features of mitigation pathways under these inherently uncertain drivers of energy and emissions developments. Based on an integrated assessment model comparison exercise, we show that economic growth and fossil resource assumptions substantially affect baseline developments, but in no case they lead to the significant greenhouse gas emission reduction that would be needed to achieve long-term climate targets without dedicated climate policy. The influence of economic growth and fossil resource assumptions on climate mitigation pathways is relatively small due to overriding requirements imposed by long-term climate targets. While baseline assumptions can have substantial effects on mitigation costs and carbon prices, we find that the effects of model differences and the stringency of the climate target are larger compared to that of baseline assumptions. We conclude that inherent uncertainties about socio-economic determinants like economic growth and fossil resource availability can be effectively dealt with in the assessment of mitigation pathways.

Most research on future climate change discusses mitigation and impacts/adaptation separately. However, mitigation will have implications for impacts and adaptation. Similarly, impacts and adaptation will affect mitigation. This paper begins to explore these two veins of research simultaneously using an integrated assessment model. We begin by discussing the types of interactions one might expect by impact sector. Then, we develop a numerical experiment in the agriculture sector to illustrate the importance of considering mitigation, impacts, and adaptation at the same time. In our experiment, we find that climate change can reduce crop yields, resulting in an expansion of cropland to feed a growing population and a reduction in bioenergy production. These two effects, in combination, result in an increase in the cost of mitigation.

In 2010, Asia accounted for 60% of global population, 39% of Gross World Product, 44% of global energy consumption and nearly half of the world's energy system CO2 emissions. Thus, Asia is an important region to consider in any discussion of climate change or climate change mitigation. This paper explores the role of Asia in mitigating climate change, by comparing the results of 23 energy-economy and integrated assessment models. We focus our analysis on seven key areas: base year data, future energy use and emissions absent climate policy, the effect of urban and rural development on future energy us and emissions, the role of technology in emissions mitigation, regional emissions mitigation, and national climate policies.

What are the drivers of future global carbon dioxide (CO 2 ) emissions growth and how would the availability of key energy supply technologies change their relative importance? In this paper, we apply a novel index number decomposition technique to the results of a multi-region, multi-sector computable general equilibrium model to quantify the influence of five factors on the growth of future carbon emissions: (1) growth in global economic activity; (2) shifts in the regional composition of gross world product; (3) shifts in the sectoral composition of regions' GDP; (4) changes in sectors' energy–output ratios; and (5) changes in the CO 2 intensity of energy sources. We elucidate how the relative importance of these factors changes in response to the imposition of a global carbon tax and alternative assumptions about the future availability of key energy supply technologies. Rising global economic activity and shifts in regional composition put upward pressure on emissions while changes in energy and emission intensity and the sectoral output mix have attenuating effects. A global emission tax that increases over time slows economic expansion and shifts the fuel mix, with the most pronounced impacts on China, India, and Russia. Limited availability of carbon capture and storage, nuclear, and hydroelectric generation all lead to upward shifts in the long-run marginal abatement cost curve, causing some countries to choose to pay the tax rather than abate.

While the world has yet to adopt a single unified policy to limit climate change, many countries and regions have adopted energy and climate policies that have implications for global emissions. In this paper, we discuss a few key policies and how they are included in a set of 23 energy and integrated assessment models that participated in the Asia Modeling Exercise. We also compare results from these models for a small set of stylized scenarios to the pledges made as part of the Copenhagen Accord and the goals stated by the Major Economies Forum. We find that the targets outlined by the United States, the European Union, Japan, and Korea require significant policy action in most of the models analyzed. For most of the models in the study, however, the goals outlined by India are met without any climate policy. The stringency of climate policy required to meet China's Copenhagen pledges varies across models and accounting methodologies.

We explore the implications that alternative pathways for human population and economic development have for the role of Asia in reference no-climate-policy scenarios and scenarios in which climate forcing is limited. We consider three different pathways of socioeconomic development, which we refer to as Shared Socio-economic Pathways (SSPs) and four different levels of limitation on climate forcing, which we refer to as Shared Climate Policy Assumptions (SPAs). SSPs are differentiated by population and economic growth assumptions, while SPAs are differentiated on the level of radiative forcing in the year 2100. Regardless of the scenarios we examined Asia plays a central role in shaping the world's future with nearly half of the world's people and more than half of the world's economic activity and energy consumption. The future of Asia and the world are dramatically different across the various combinations of SSPs and SPAs. High population worlds place significant stress on Asian resources and ecosystems. In high population SSPs the poorest members of the population face high energy and food prices and the more stringent the level of emissions mitigation, the more stress poor populations experience, though the more stringent the emissions mitigation, the larger the area of unmanaged ecosystems that are preserved.

The 1992 Framework Convention on Climate Change created the basic international architecture for addressing climate change. That treaty was negotiated at a time when the research literature examining emissions mitigation and the role of energy technology was relatively limited. In the two subsequent decades a great deal has been learned. The problem of stabilizing the concentration of greenhouse gases in the atmosphere has proved far more difficult than envisioned in 1992 and the role of technology appears even more important when emissions mitigation strategies are co-developed in the context of multiple competing ends.

The Intergovernmental Panel on Climate Change’s (IPCC) Fifth Assessment (to be published in 2013–2014) will to a significant degree be built around four Representative Concentration Pathways (RCPs) that are intended to represent four scenarios of future development of greenhouse gas emissions, land use, and concentrations that span the widest range of potential future atmospheric radiative forcing. Under the very stringent climate policy implied by the 2.6 W/ m 2 overshoot scenario, all electricity is eventually generated from low carbon sources. However, carbon dioxide capture and storage (CCS) technologies never comprise more than 50% of total electricity generation in that very stringent scenario or in any of the other cases examined here. There are significant differences among the cases studied here in terms of how CCS technologies are used, with the most prominent being is the significant expansion of biomass+CCS as the stringency of the implied climate policy increases. Cumulative CO 2 storage across the three cases that imply binding greenhouse gas constraints ranges by nearly an order of magnitude from 170 Gt CO 2 (radiative forcing of 6.0 W/ m 2 in 2100) to 1600 Gt CO 2 (2.6 W/ m 2 in 2100) over the course of this century. This potential demand for deep geologic CO2 storage is well within published estimates of total global CO2 storage capacity.

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m −2 (approximately 526 ppm CO 2 ) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

The EMF 22 subgroup on Transition Scenarios explores a rich suite of potential future worlds in which climate change is limited to a variety of alternative radiative forcing levels. This paper focuses primarily on the requirements to limit radiative forcing from Kyoto gases to 2.6 W/m2. Given that we estimate year 2005 radiative forcing to be 2.4 W/m2, the 2.6 W/m2 limit creates a non-trivial constraint. Allowing radiative forcing to exceed the long-term target level provides greater latitude in achieving the goal, but implies major changes to both global energy and land-use systems in the near term as well as the long term. In addition, delay on the part of major emitting parties creates potential “leakage” in both energy and land use. We estimate the challenging near-term and long-term deployment of new wind power, nuclear power and CO2 capture and storage associated with the 2.6 W/m2 limit.

The EMF22 Transition Scenario subgroup explores the implications of delayed accession on limiting climate change to various radiative forcing levels. This paper focuses on the cost of limiting radiative forcing and the role that industrial leakage plays in scenarios of delayed accession. We find that delayed participation shifts the cost burden toward regions that take early action and away from regions that undertake mitigation later. However, the inefficiencies introduced by delay are so great that present discounted costs are higher in the delayed scenario for regions that delay as well as for regions taking early actions. An important element of these inefficiencies is industrial emissions leakage, that is non-participating regions increase their emissions relative to the reference case. In aggregate, industrial leakage rates are less than 10% if all regions of the world begin emissions mitigation by 2050—higher in carbon-intensive sectors and lower in low-carbon-intensity sectors. Additionally, we consider the implication of technology on carbon prices, the feasibility of limiting radiative forcing to low levels, and the incentives to overshoot the radiative forcing limit.

This paper, a contribution to the EMF 22 subgroup on Transition Scenarios, examines the relationship between technology evolution over the next 40 years and the cost, energy, and greenhouse gas emissions consequences of possible U.S. mitigation goals. The paper explores these issues within the context of cumulative emissions targets based on linear reductions in CO 2 -e emissions of 50% and 80% below 1990 levels by 2050. Six technology futures were constructed within the MiniCAM integrated assessment model and then applied to the emissions targets. The paper explores the influence of technology availability and expectations of future technology availability on the economic consequences of emissions mitigation, on the time path of emissions mitigation, and on the evolution of the U.S. energy system over time. One of the strongest themes to emerge from the scenarios in this study is that near-term decision-making depends on the availability of technology decades into the future, when deep emissions reductions are required to meet the cumulative emissions goals. In the scenarios in this paper, it is the expectations about future technology that have the most dramatic effect on greenhouse gas emissions prices and emissions reductions in 2020, as opposed to near-term technology availability. Moreover, it is the nature of technology 20, 30, and 40 years out, rather than availability and deployment of technology in the next decade, that will largely determine the character of the mid-century energy system.

The Energy Modeling Forum 22 study included a set of U.S. transition scenarios designed to bracket a range of potential U.S. climate policy goals. Models from the six teams that participated in this part of the study include models that have been prominently involved in analyzing proposed U.S. climate legislation, as well as models that have been involved in the Climate Change Science Program and other parts of this EMF 22 study. This paper presents an overview of the results from the U.S. transition scenarios, and provides insights into the comparison of results from the participating models.

Among the tRNA population of the archaeal parasite Nanoarchaeum equitans are five species assembled from separate 5′ and 3′ tRNA halves and four species derived from tRNA precursors containing introns. In both groups an intervening sequence element must be removed during tRNA maturation. A bulge–helix–bulge (BHB) motif is the hallmark structure required by the archaeal splicing endonuclease for recognition and excision of all introns. BHB motifs are recognizable at the joining sites of all five noncontinuous tRNA species, although deviations from the canonical BHB motif are clearly present in at least two of them. Here, we show that the N. equitans splicing endonuclease cleaves tRNA precursors containing normal introns, as well as all five noncontinuous precursor tRNAs, at the predicted splice sites, indicating the enzyme's dual role in the removal of tRNA introns and processing of tRNA halves to be joined in trans. The cleavage activity on a set of synthetic canonical and noncanonical BHB constructs showed that the N. equitans splicing endonuclease accepts a broader range of substrates than the homodimeric Archaeoglobus fulgidus enzyme. In contrast to the A. fulgidus endonuclease, the N. equitans splicing enzyme possesses two different subunits. This heteromeric endonuclease type, found in N. equitans , in all Crenarchaeota, and in Methanopyrus kandleri , is able to act on the noncanonical tRNA introns present only in these organisms, which suggests coevolution of enzyme and substrate.

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%–40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between −12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.

We report results of a “hindcast” experiment focusing on the agricultural and land-use component of the Global Change Assessment Model (GCAM). We initialize GCAM to reproduce observed agriculture and land use in 1990 and forecast agriculture and land use patterns on one-year time steps to 2010. We report overall model performance for nine crops in 14 regions. We report areas where the hindcast is in relatively good agreement with observations and areas where the correspondence is poorer. We find that when given observed crop yields as input data, producers in GCAM implicitly have perfect foresight for yields leading to over compensation for year-to-year yield variation. We explore a simple model in which planting decisions are based on expectations but production depends on actual yields and find that this addresses the implicit perfect foresight problem. Second, while existing policies are implicitly calibrated into IAMs, changes in those policies over the period of analysis can have a dramatic effect on the fidelity of model output. Third, we demonstrate that IAMs can employ techniques similar to those used by the climate modeling community to evaluate model skill. We find that hindcasting has the potential to yield substantial benefits to the IAM community.

Energy is crucial for supporting basic human needs, development and well-being. The future evolution of the scale and character of the energy system will be fundamentally shaped by socioeconomic conditions and drivers, available energy resources, technologies of energy supply and transformation, and end-use energy demand. However, because energy-related activities are significant sources of greenhouse gas (GHG) emissions and other environmental and social externalities, energy system development will also be influenced by social acceptance and strategic policy choices. All of these uncertainties have important implications for many aspects of economic and environmental sustainability, and climate change in particular. In the Shared-Socioeconomic Pathway (SSP) framework these uncertainties are structured into five narratives, arranged according to the challenges to climate change mitigation and adaptation. In this study we explore future energy sector developments across the five SSPs using Integrated Assessment Models (IAMs), and we also provide summary output and analysis for selected scenarios of global emissions mitigation policies. The mitigation challenge strongly corresponds with global baseline energy sector growth over the 21st century, which varies between 40% and 230% depending on final energy consumer behavior, technological improvements, resource availability and policies. The future baseline CO2-emission range is even larger, as the most energy-intensive SSP also incorporates a comparatively high share of carbon-intensive fossil fuels, and vice versa. Inter-regional disparities in the SSPs are consistent with the underlying socioeconomic assumptions; these differences are particularly strong in the SSPs with large adaptation challenges, which have little inter-regional convergence in long-term income and final energy demand levels. The scenarios presented do not include feedbacks of climate change on energy sector development. The energy sector SSPs with and without emissions mitigation policies are introduced and analyzed here in order to contribute to future research in climate sciences, mitigation analysis, and studies on impacts, adaptation and vulnerability.

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. The resulting pollutant emission trajectories under the SSP scenarios cover a wider range than the scenarios used in previous international climate model comparisons. In the SSP3 and SSP4 scenarios, where economic, institutional and technological limitations slow air quality improvements, global pollutant emissions over the 21st century can be comparable to current levels. Pollutant emissions in the SSP1 scenarios fall to low levels due to the assumption of technological advances and successful global action to control emissions.

Energy from biomass is potentially an important contributor to U.S. climate change mitigation efforts. However, an important consideration to large-scale implementation of bioenergy is that the production of biomass competes with other uses of land. This includes traditionally economically productive uses, such as agriculture and forest products, as well as storage of carbon in forests and non-commercial lands. In addition, in the future, biomass may be more easily traded, meaning that increased U.S. reliance on bioenergy could come with it greater reliance on imported energy. Several approaches could be implemented to address these issues, including limits on U.S. biomass imports and protection of U.S. and global forests. This paper explores these dimensions of bioenergy’s role in U.S. climate policy and the relationship to these alternative measures for ameliorating the trade and land use consequences of bioenergy. It first demonstrates that widespread use of biomass in the U.S. could lead to imports; and it highlights that the relative stringency of domestic and international carbon mitigation policy will heavily influence the degree to which it is imported. Next, it demonstrates that while limiting biomass imports would prevent any reliance on other countries for this energy supply, it would most likely alter themore » balance of trade in other agricultural products against which biomass competes; for example, it might turn the U.S. from a corn exporter to a corn importer. Finally, it shows that increasing efforts to protect both U.S. and international forests could also affect the balance of trade in other agricultural products.« less

International audience; This paper uses the EMF27 scenarios to explore the role of renewable energy (RE) in climate change mitigation. Currently RE supplies almost 20 % of global electricity demand. Almost all EMF27 mitigation scenarios show a strong increase in renewable power production, with a substantial ramp-up of wind and solar power deployment. In many scenarios, renewables are the most important long-term mitigation option for power supply. Wind energy is competitive even without climate policy, whereas the prospects of solar photovoltaics (PV) are highly contingent on the ambitiousness of climate policy. Bioenergy is an important and versatile energy carrier; however--with the exception of low temperature heat--there is less scope for renewables other than biomass for non-electric energy supply. Despite the important role of wind and solar power in climate change mitigation scenarios with full technology availability, limiting their deployment has a relatively small effect on mitigation costs, if nuclear and carbon capture and storage (CCS)--which can serve as substitutes in low-carbon power supply--are available. Limited bioenergy availability in combination with limited wind and solar power by contrast, results in a more substantial increase in mitigation costs. While a number of robust insights emerge, the results on renewable energy deployment levels vary considerably across the models. An in-depth analysis of a subset of EMF27 reveals substantial differences in modeling approaches and parameter assumptions. To a certain degree, differences in model results can be attributed to different assumptions about technology costs, resource potentials and systems integration.

Human activities are significantly altering biogeochemical cycles at the global scale, posing a significant problem for earth system models (ESMs), which may incorporate static land-use change inputs but do not actively simulate policy or economic forces. One option to address this problem is to couple an ESM with an economically oriented integrated assessment model. Here we have implemented and tested a coupling mechanism between the carbon cycles of an ESM (CESM, the Community Earth System Model) and an integrated assessment (GCAM) model, examining the best proxy variables to share between the models, and quantifying our ability to distinguish climate- and land-use-driven flux changes. The net primary production and heterotrophic respiration outputs of the Community Land Model (CLM), the land component of CESM, were found to be the most robust proxy variables by which to manipulate GCAM's assumptions of long-term ecosystem steady state carbon, with short-term forest production strongly correlated with long-term biomass changes in climate-change model runs. Carbon-cycle effects of anthropogenic land-use change are short-term and spatially limited relative to widely distributed climate effects, and as a result we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. By allowing climate effects from a full earth system model to dynamically modulate the economic and policy decisions of an integrated assessment model, this work provides a foundation for linking these models in a robust and flexible framework capable of examining two-way interactions between human and earth system processes.

This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scope—partial versus economy-wide—and in how they represent technology and the behavior of supply and demand in markets. The CGE models are “deep” structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) “shallow” structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) “deep” structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specification—comparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models.