Expert Perspectives

Scenarios to Model Long-term Climate Strategies Can Help Focus Action Today

Abstract

Long-term strategies represent a new and unique opportunity for prompting countries to enhance their understanding of the pathways to domestic and international climate goals, and the associated changes that would be needed. Maximizing this opportunity requires it to be a community activity that engages stakeholders, including government and other members of civil society, along with the analysts. This produces both a more enlightening set of “answers” and catalyzes a process that both educates stakeholders and supports concrete decisions.

The opportunity of long-term strategy development

In contrast to previous approaches, the Paris Agreement explicitly calls on countries to deliver long-term strategies (LTSs) for decarbonization to the international community, calling on “all Parties . . . to formulate and communicate long-term low greenhouse gas emission development strategies.” Now, modeling and scenario development processes will be driven by a consistent policy framework—one that can support development of global best practices and that creates a mechanism for governments to engage with international and domestic stakeholders. Moreover, the exercise can encourage countries to raise ambition and avoid locking in less promising investment pathways. The value of this process can be maximized when the role of scenarios and models is properly contextualized for stakeholders, and when the process engages stakeholders to coproduce the roadmap. This essay outlines the role of modeling and scenario development for developing national long-term low greenhouse gas [GHG] emission development strategies and suggests approaches that can lead to a more robust national policy roadmap.

Models and scenarios for long-term strategies

Developing an LTS requires working with diverse actors to implement the vision of current national leadership, reflect agendas from diverse government departments, integrate stakeholder perspectives and inputs, and communicate to domestic and international audiences. This integrative effort requires that stakeholders and analysts collaborate to illuminate options and better understand the scope for action within a specific national context. Modeling and scenario analysis are essential tools in this process.

Models

Models provide a way of systematically organizing thoughts and understanding the implications of alternate pathways. When used appropriately, models are a powerful tool for LTS development, connecting core drivers to possible outcomes. For example, models can illuminate the relationship between drivers like population, economic activity, available technology, and policy (all outside the model) and predicted values in outcomes like energy use, land use, greenhouse gas emissions, or climate change. While models can theoretically be either qualitative or quantitative, most countries will engage with numerical models of some kind. These can produce conditional forecasts based on where countries currently are, and what they feel their choices might be.

For models to be most useful in this process of developing strategies, they need to be chosen carefully and used appropriately. Models in the LTS process should have three characteristics:

  1. Models should be science-based. Models should reflect the best current scientific understanding of human and physical Earth systems. Models do not always have to have the highest resolution or be the “most powerful,” but they should be appropriate to the questions being asked and provide a sound basis in science and a reflection of process.
  2. Models should provide national scale in a global context. Because national strategies require thinking at national scales, the models should be able to match this scale. At the same time, countries are an amalgam of activities in sectors, across regions, and within institutional and social contexts, so it is important that either the models or the broader process and analysis set countries in a larger regional or global context.
  3. Models should examine multiple angles, and multiple models should be used. Models are always imperfect, and no model can do everything. Therefore, one of the core principles of using models properly is to the select models best suited to answering the questions posed. A complex question like developing a long-term strategy (or nationally determined contribution [NDC]) may require several models to be integrated in a wider analysis. For example, national planning might require high-level strategic or tailored, country-focused energy models (such as the National Energy Modeling System (NEMS) model in the United States). National policies can be embedded in a global context through integrated assessment models. Other questions can be examined and additional inputs provided to the process through complementary models—such as engineering and technology-based models to understand aspects of technology choice (e.g., the Long-Range Energy Alternatives Planning [LEAP] model) or economy-focused models to understand impacts on employment and economic output (e.g., computable general equilibrium models).

In considering all of these, the consistent advice from analysts is to choose the model to fit the question being asked. For example, national energy models can answer questions about national energy trends (some being better than others, of course) but cannot capture many important greenhouse gases at all, such as N2O or land use change emissions. The need to “fit for purpose” is why multiple models may be necessary to answer questions about overall national strategy, but this need also underscores why models (or even suites of models) should not be chosen that do not capture the full set of important drivers of development and emission outcomes.

Scenarios

Scenarios are also essential to a larger process of developing a national strategy. While models allow stakeholders to understand the outcomes of a specific pathway, scenarios are the alternate options for that pathway. Simple kinds of scenarios for a country could be “High Renewables Future” or “Mixed Renewables and Natural Gas Future.” A selected model could then be engaged to run these two different pathways and report back about the projected situation in the country at a target date under each. Stakeholders, working with analysts , can help build what kinds of scenarios are most interesting to consider and what kinds of implications are most important to model.

In a world of deep uncertainty about the future, scenarios are an essential partner to modeling. Models are not unconditionally predictive and are most helpful when viewed as “if-then” processes. In other words, “If the world evolves like this, then what happens in our country?” Scenarios help simplify the many permutations of alternatives into a few tractable stories that can be understood and communicated from stakeholders to analysts and back. The basic motivation for scenarios thus allows us to bracket the uncertainties and capture a range of decisions and evolutionary pathways. An alternate framing of scenarios is that they can set an end goal and help illuminate the systemic changes needed to get there.

Using variations on this approach, several countries have produced documents outlining their long-term strategies. These include Canada, Mexico, France, Germany, the United States (under the Obama administration), and Benin. Since there is no formal template or set of requirements, these documents take different approaches to scenarios for their long-term strategy development.

The United States clustered its scenarios around four areas, all of which would see emissions reduced by at least 80 percent by 2050. These included the following:

  • A benchmark scenario, intended as a starting point for the analysis and basis for comparison (not a “most likely” pathway).
  • Two negative emissions scenarios. First, a “no CO2 removal technology” option assumed that engineered CO2 removal technologies like bioenergy with carbon capture and storage (BECCS) are unavailable and larger emphasis is placed on land sink and low carbon energy transition beyond the benchmark scenario. A second “limited sink” scenario limited availability of CO2 removal tech, but also limited success in maintaining and enhancing the land sink.
  • Three advanced energy technology scenarios, which included a “no carbon capture, utilization, and storage (CCUS)” scenario that required greater emphasis on land carbon sink and a more rapid phase-out of coal and natural gas, a “smart growth” scenario focused on the transportation and buildings sectors, and a “limited biomass” scenario that limited bioenergy consumption and used no BECCS.
  • A beyond 80 scenario, which included stronger global action to reduce emissions and more rapid advances in low-carbon technology.

This overall approach, which uses a core scenario and builds a few complementary scenarios featuring alternate assumptions about technologies, land use, or ambition, is shared by a few of the existing LTS reports and provides a potentially useful point of departure for others considering how to structure their scenarios.

Mexico developed three scenarios:

  • A baseline projection under no climate or energy policy constraints, assuming a 3 percent average growth rate
  • An NDC policy scenario that reaches the NDC reduction target of 22 percent of economy-wide GHGs by 2030 and 51 percent of black carbon. After 2030, the trajectory achieves 50 percent reduction of GHGs compared to Mexico’s 2000 emissions.
  • An NDC more ambition scenario that reduces emissions by 36 percent, and black carbon 70 by percent, by 2030.

Mexico's approach is similar to that of the United States in overall structure, but two countries’ choice of models and what to focus on were different and related to their national circumstances and priorities. Black carbon, for example, has been a focus of Mexico’s national strategy and was therefore more overtly reflected in its discussions and analysis.

Canada developed a diverse set of scenarios bracketing baseline through high ambition (89 percent reduction) and included a core scenario focusing on currently deployed technologies with plausible rates of cost reduction producing 80 percent reduction by 2050. Several scenarios focused on higher penetrations of specific technologies such as nuclear, hydro, and demand response. Canada’s approach also utilized the idea of a core scenario with different assumptions for specific technologies. France produced a trend-based scenario to reflect existing measures, and an alternate scenario representing policy action. Germany produced a business-as-usual case and then evaluated existing studies and scenarios to show that the German climate target is technically and economically achievable, in most cases based on known technologies. Germany here relied on previous studies for some of the alternate scenarios, which is a way to utilize previous research and therefore potentially more feasible for some countries, although relying on previous work may not allow an exact match to the assumptions in the core scenario and may limit the ability to tailor questions to stakeholders. Benin’s LTS took a different approach, focusing on potential ranges of climate impacts on Benin and establishing long-term goals for development across sectors, which is consistent with the Paris Agreement’s suggestion that such strategies be developed taking into account differing national circumstances.

Collaborative scenario development can improve outcomes

The process of scenario building and modeling is best done collaboratively between stakeholders (such as governments and civil society) that are interested in the outcomes. Such lessons have been learned in decades of scenario development experience and were applied at least in part in the development of the recent LTS studies described above. In the United States, for example, the modelers and scenario developers jointly developed scenarios that were “informed by the input received at a series of stakeholder listening sessions with non-governmental and private sector organizations . . . and by ongoing collaboration with Canada, Mexico, and other nations.” When done well, collaborative scenario development integrates models, policy roadmaps, and decision making, and can lead to better outcomes in two significant ways.

First, collaborative scenario development leads to results that are more closely tailored to government and stakeholder interests. Because of the “if-then” nature of models and scenarios, somebody needs to develop the alternate ideas for the future. Such questions may include, What kinds of futures are we most interested in testing? What is politically feasible in the near term? What long-term goals can we hope to stretch for? While such questions can be asked and answered by the analysts and modelers, these researchers may not have the full diversity of perspectives on constraints, opportunities, or policy goals that government or other stakeholders bring to the process. At the same time, policymakers and other stakeholders are not usually aware of what choices need to be made explicit for different modeling platforms to work. Therefore, a conversation in which all stakeholders produce scenarios together stands the best chance of producing outcomes helpful to the broader community.

Second, collaborative scenario development raises understanding and buy-in to the eventual results of the modeling for governments, policymakers, and other stakeholders. When stakeholders from government and civil society groups formulate scenarios collaboratively with the analytical community, they confront the choices inherent in each, often including specific policy directions. This is a helpful process for all stakeholders, including the analysts, and it increases their capacity to understand policy choices. Such choices, and the pathways they support, need to be viewed as a reasonable, and appropriately complete in their scope, by the various participants in the strategy development process. Having helped construct the scenarios, such stakeholders have higher confidence in the outcome and are more interested in the eventual result. Such engagement is likelier to create feedback between the analytical work and policy processes in government and civil society.

When done well, the development of a national long-term strategy can leverage the opportunity provided under Paris. Models and scenarios can help this process reach its full potential. Creating a culture of close linking between analytical inputs and LTS will help countries better understand their current scope for action and align their ambitions for pathways with their eventual goals. In addition to its usefulness to domestic processes, robust LTS creation can enhance global confidence that countries are engaging fully and allow conversations about progress toward domestic and global goals.

All the interpretations and findings set forth in this expert perspective are those of the author alone.