Showing papers by "Joint Global Change Research Institute published in 2015"

Can Paris pledges avert severe climate change

Abstract: Current international climate negotiations seek to catalyze global emissions reductions through a system of nationally determined country-level emissions reduction targets that would be regularly updated. These “Intended Nationally Determined Contributions” (INDCs) would constitute the core of mitigation commitments under any agreement struck at the upcoming Paris Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC) ( 1 ). With INDCs now reported from more than 150 countries and covering around 90% of global emissions, we can begin to assess the role of this round of INDCs in facilitating or frustrating achievement of longer-term climate goals. In this context, it is important to understand what these INDCs collectively deliver in terms of two objectives. First, how much do they reduce the probability of the highest levels of global mean surface temperature change? Second, how much do they improve the odds of achieving the international goal of limiting temperature change to under 2°C relative to preindustrial levels ( 2 )? Although much discussion has focused on the latter objective ( 3 – 5 ), the former is equally important when viewing climate mitigation from a risk-management perspective.

A global map of urban extent from nightlights

Abstract: Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering not just water and carbon cycling, biodiversity, and climate, but also demography, public health, and economy. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. We developed a method to map the urban extent from the defense meteorological satellite program/operational linescan system nighttime stable-light data at the global level and created a new global 1 km urban extent map for the year 2000. Our map shows that globally, urban is about 0.5% of total land area but ranges widely at the regional level, from 0.1% in Oceania to 2.3% in Europe. At the country level, urbanized land varies from about 0.01 to 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration between 30° N and 45° N latitude and the largest longitudinal peak around 80° W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban areas provides a reliable estimate of global urban areas and offers the potential for producing a time-series of urban area maps for temporal dynamics analyses.

Post-2020 climate agreements in the major economies assessed in the light of global models

Abstract: Integrated assessment models can help in quantifying the implications of international climate agreements and regional climate action. This paper reviews scenario results from model intercomparison projects to explore different possible outcomes of post-2020 climate negotiations, recently announced pledges and their relation to the 2 °C target. We provide key information for all the major economies, such as the year of emission peaking, regional carbon budgets and emissions allowances. We highlight the distributional consequences of climate policies, and discuss the role of carbon markets for financing clean energy investments, and achieving efficiency and equity.

Near-term acceleration in the rate of temperature change

Abstract: Knowledge of the near-term rate of change is needed for adaptation. The rate at which climate change is occurring, over 40-year periods, is found to be unprecedented in the past 1,000 years. Regionally, Europe, North America and the Arctic are above the global average.

BAAD: a Biomass And Allometry Database for woody plants

Abstract: Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01–100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world's vegetation.

A Comprehensive View of Global Potential for Hydro-generated Electricity

Abstract: In this study, we assess global hydropower potential using runoff and stream flow data, along with turbine technology performance, cost assumptions, and consideration of protected areas. The results provide the first comprehensive quantification of global hydropower potential including gross, technical, economic, and exploitable estimates. Total global potential of gross, technical, economic, and exploitable hydropower are estimated to be approximately 128, 26, 21, and 16 petawatt hours per year, respectively. The economic and exploitable potential of hydropower are calculated at less than 9 cents per kW h. We find that hydropower has the potential to supply a significant portion of world energy needs, although this potential varies substantially by region. Globally, exploitable hydropower potential is comparable to total electricity demand in 2005. Hydropower plays different roles in each country owing to regional variation in potential relative to electricity demand. In some countries such as the Congo, there is sufficient hydropower potential (>10 times) to meet all electricity demands, while in other countries such as United Kingdom, hydropower potential can only accommodate a small portion (<3%) of total demand. A sensitivity analysis indicates that hydropower estimates are sensitive to a number of parameters: design flow (varying by −10% to +0% at less than 9 cents per kW h), cost assumptions (by −35% to +12%), turbine efficiency (by −40% to +20%), stream flow (by −35% to +35%), fixed charge rate (by −15% to 10%), and protected land (by −15% to 20%). This sensitivity analysis emphasizes the reliable role of hydropower for future energy systems, when compared to other renewable energy resources with larger uncertainty in their future potentials.

A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0

Abstract: . Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganic carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO2], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.

Agriculture intensifies soil moisture decline in Northern China

Abstract: Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50 cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of −0.011 to −0.015 m3 m−3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system.

Atmospheric carbonyl sulfide sources from anthropogenic activity: Implications for carbon cycle constraints

Abstract: Carbonyl sulfide (COS) has recently emerged as an atmospheric tracer of gross primary production All modeling studies of COS air-monitoring data rely on a climatological anthropogenic inventory that does not reflect present conditions or support interpretation of ice core and firn trends Here we develop a global anthropogenic inventory for the years 1850 to 2013 based on new emission measurements and material-specific data By applying methods from a recent regional inventory to global data, we find that the anthropogenic source is similar in magnitude to the plant sink, confounding carbon cycle applications However, a material-specific approach results in a current anthropogenic source that is only one third of plant uptake and is concentrated in Asia, supporting carbon cycle applications of global air-monitoring data Furthermore, changes in the anthropogenic source alone cannot explain the century-scale mixing ratio growth, which suggests that ice and firn data may provide the first global history of gross primary production

Improved representation of investment decisions in assessments of CO 2 mitigation

Abstract: Assessments of emissions mitigation patterns have largely ignored differences in investment risk across technologies and regions. With a model accounting for such differences in the electricity generation sector, research now finds that mitigation costs are higher than with no risk variation, and highlights the importance of institutional reforms to lower investment risks.

Understanding the contribution of non-carbon dioxide gases in deep mitigation scenarios

Abstract: In 2010, the combined emissions of methane (CH4), nitrous oxide (N2O) and the fluorinated gasses (F-gas) accounted for 20–30% of Kyoto emissions and about 30% of radiative forcing. Current scenario studies conclude that in order to reach deep climate targets (radiative forcing of 2.8 W/m2) in 2100, carbon dioxide (CO2) emissions will need to be reduced to zero or negative. However, studies indicated that non-CO2 emissions seem to be have less mitigation potential. To support effective climate policy strategies, an in-depth assessment was made of non-CO2 greenhouse gas emission and their sources in achieving an ambitious climate target. Emission scenarios were assessed that had been produced by six integrated assessments models, which contributed to the scenario database for the fifth IPCC report. All model scenarios reduced emissions from energy-related sectors, largely resulting from structural changes and end-of-pipe abatement technologies. However, emission reductions were much less in the agricultural sectors. Furthermore, there were considerable differences in abatement potential between the model scenarios, and most notably in the agricultural sectors. The paper shows that better exploration of long-term abatement potential of non-CO2 emissions is critical for the feasibility of deep climate targets.

Climate mitigation policy implications for global irrigation water demand

Abstract: Measures to limit greenhouse gas concentrations will result in dramatic changes to energy and land systems and in turn alter the character of human requirements for water. We employ the global change assessment model (GCAM), an integrated assessment model, to explore the interactions of energy, land, and water systems under combinations of three alternative radiative forcing stabilization levels and two carbon tax regimes. The paper analyzes two important research questions: i) how large may global irrigation water demands become over the next century, and ii) what are the potential impacts of emissions mitigation policies on global irrigation-water withdrawals. We find that increasing population and economic growth could more than double the demand for water for agricultural systems in the absence of climate policy, and policies to mitigate climate change further increase agricultural demands for water. The largest increases in agricultural irrigation water demand occur in scenarios where only fossil fuel emissions are priced (but not land use change emissions) and are primarily driven by rapid expansion in bio-energy production. Regions such as China, India, and other countries in South and East Asia are likely to experience the greatest increases in water demands. Finally, we test the sensitivity of water withdrawal demands to the share of bio-energy crops under irrigation and conclude that many regions have insufficient space for heavy bio-energy crop irrigation in the future—a result that calls into question the physical possibility of producing the associated biomass energy, especially under climate policy scenarios.

The contribution of Paris to limit global warming to 2 °C

Abstract: The international community has set a goal to limit global warming to 2 °C. Limiting global warming to 2 °C is a challenging goal and will entail a dramatic transformation of the global energy system, largely complete by 2040. As part of the work toward this goal, countries have been submitting their Intended Nationally Determined Contributions (INDCs) to the United Nations Framework Convention on Climate Change, indicating their emissions reduction commitments through 2025 or 2030, in advance of the 21st Conference of the Parties (COP21) in Paris in December 2015. In this paper, we use the Global Change Assessment Model (GCAM) to analyze the near versus long-term energy and economic-cost implications of these INDCs. The INDCs imply near-term actions that reduce the level of mitigation needed in the post-2030 period, particularly when compared with an alternative path in which nations are unable to undertake emissions mitigation until after 2030. We find that the latter case could require up to 2300 GW of premature retirements of fossil fuel power plants and up to 2900 GW of additional low-carbon power capacity installations within a five-year period of 2031–2035. INDCs have the effect of reducing premature retirements and new-capacity installations after 2030 by 50% and 34%, respectively. However, if presently announced INDCs were strengthened to achieve greater near-term emissions mitigation, the 2031–2035 transformation could be tempered to require 84% fewer premature retirements of power generation capacity and 56% fewer new-capacity additions. Our results suggest that the INDCs delivered for COP21 in Paris will have important contributions in reducing the challenges of achieving the goal of limiting global warming to 2 °C.

Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

Abstract: The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

Correcting Incompatible DN Values and Geometric Errors in Nighttime Lights Time-Series Images

Abstract: The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime lights imagery has proven to be a powerful remote sensing tool to monitor urbanization and assess socioeconomic activities at large scales. However, the existence of incompatible digital number (DN) values and geometric errors severely limit application of nighttime light image data on multiyear quantitative research. In this paper, we extend and improve previous studies on intercalibrating nighttime lights image data to obtain more compatible and reliable nighttime lights time-series (NLT) image data for China and the U.S. through four steps, namely, intercalibration, geometric correction, steady-increase adjustment, and population data correction. We then use gross domestic product (GDP) data to test the processed NLT image data indirectly and find that sum light (summed DN value of pixels in a nighttime light image) maintains apparent increase trends with relatively large GDP growth rates but does not increase or decrease with relatively small GDP growth rates. As nighttime light is a sensitive indicator for economic activity, the temporally consistent trends between sum light and GDP growth rate imply that brightness of nighttime lights on the ground is correctly represented by the processed NLT image data. Finally, through analyzing the corrected NLT image data from 1992 to 2008, we find that China experienced apparent nighttime lights development in 1992–1997 and 2001–2008, respectively, and the U.S. showed nighttime lights decay in large areas after 2001.

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

Abstract: The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insights on tail events.

Regional scale cropland carbon budgets

Abstract: Accurate quantification and clear understanding of regional scale cropland carbon (C) cycling is critical for designing effective policies and management practices that can contribute toward stabilizing atmospheric CO2 concentrations. However, extrapolating site-scale observations to regional scales represents a major challenge confronting the agricultural modeling community. This study introduces a novel geospatial agricultural modeling system (GAMS) exploring the integration of the mechanistic Environmental Policy Integrated Climate model, spatially-resolved data, surveyed management data, and supercomputing functions for cropland C budgets estimates. This modeling system creates spatially-explicit modeling units at a spatial resolution consistent with remotely-sensed crop identification and assigns cropping systems to each of them by geo-referencing surveyed crop management information at the county or state level. A parallel computing algorithm was also developed to facilitate the computationally intensive model runs and output post-processing and visualization. We evaluated GAMS against National Agricultural Statistics Service (NASS) reported crop yields and inventory estimated county-scale cropland C budgets averaged over 2000-2008. We observed good overall agreement, with spatial correlation of 0.89, 0.90, 0.41, and 0.87, for crop yields, Net Primary Production (NPP), Soil Organic C (SOC) change, and Net Ecosystem Exchange (NEE), respectively. However, we also detected notable differences in the magnitude of NPP and NEE, as well as in the spatial pattern of SOC change. By performing crop-specific annual comparisons, we discuss possible explanations for the discrepancies between GAMS and the inventory method, such as data requirements, representation of agroecosystem processes, completeness and accuracy of crop management data, and accuracy of crop area representation. Based on these analyses, we further discuss strategies to improve GAMS by updating input data and by designing more efficient parallel computing capability to quantitatively assess errors associated with the simulation of C budget components. The modularized design of the GAMS makes it flexible to be updated and adapted for different agricultural models so long as they require similar input data, and to be linked with socio-economic models to understand the effectiveness and implications of diverse C management practices and policies. A novel geospatial cropland carbon modeling system based on a mechanistic agroecosystem model.Close agreement between modeled cropland carbon budgets and those estimated by the inventory method.Detailed assessment and discussion by individual crop species.Highly modularized framework facilitating adaptation for diverse purposes, such as socio-economic analysis.

Effects of episodic flooding on the net ecosystem CO2 exchange of a supratidal wetland in the Yellow River Delta

Abstract: Episodic flooding due to intense rainfall events is characteristic in many wetlands, which may modify wetland-atmosphere exchange of CO2. However, the degree to which episodic flooding affects net ecosystem CO2 exchange (NEE) is poorly documented in supratidal wetlands of coastal zone, where rainfall-driven episodic flooding often occurs. To address this issue, the ecosystem CO2 fluxes were continuously measured using the eddy covariance technique for 4 years (2010-2013) in a supratidal wetland in the Yellow River Delta. Our results showed that over the growing season, the daily average uptake in the supratidal wetland was -1.4, -1.3, -1.0, and -1.3 g Cm-2 d(-1) for 2010, 2011, 2012, and 2013, respectively. On the annual scale, the supratidal wetland functioned as a strong sink for atmospheric CO2, with the annual NEE of -223, -164, and -247 g Cm-2 yr(-1) for 2011, 2012, and 2013, respectively. The mean diurnal pattern of NEE exhibited a smaller range of variation before episodic flooding than after it. Episodic flooding reduced the average daytime net CO2 uptake and the maximum rates of photosynthesis. In addition, flooding clearly suppressed the nighttime CO2 release from the wetland but increased its temperature sensitivity. Therefore, effects of episodic flooding on the direction and magnitude of NEE should be considered when predicting the ecosystem responses to future climate change in supratidal wetlands.

Big Data issues and opportunities for electric utilities

Abstract: Advances and innovations are crucial for a sustainable electricity system that includes smart grid technologies, renewable energy sources, and greater energy efficiency. These technologies are often layered on top of the existing infrastructure and legacy information systems. The management and utilization of the data generated from the different components of the electrical system are critical for the successful deployment and operation of this system. This paper reviews the issues and opportunities of the use of Big Data for electric utilities. Big Data provides the opportunity to better monitor, correct, and integrate smart grid technologies and renewable energy. At the same time, data management and utilization must be integrated into organizational operations if the potentials are to be realized. Electric utilities are conservative, heavily-regulated, and concerned with both system reliability and overall profitability. Thus, technological, economic, institutional, and policy constraints must all be addressed. After reviewing these issues and opportunities, we empirically analyze whether these are part of the discussions about electric utilities with federal policymakers. The results show that while conversations about electric utilities overall are plentiful, conversations about data in the context of electric utilities are relatively rare.

The integrated Earth system model version 1: formulation and functionality

Abstract: . The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. The iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.

Overview of the special issue: a multi-model framework to achieve consistent evaluation of climate change impacts in the United States

Abstract: The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets of 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potentialmore » benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less