Behind every COP is a global data project that predicts Earth’s future. Here’s how it works – The Conversation

Report on Climate Modeling and its Contribution to Sustainable Development Goals

Introduction: The Scientific Foundation for Global Climate Action

International political forums, such as the Conference of the Parties to the United Nations Framework Convention on Climate Change (COP), are essential for establishing global agreements on climate change. The decisions made at these events are fundamentally reliant on scientific evidence provided by bodies like the Intergovernmental Panel on Climate Change (IPCC). This scientific underpinning is crucial for achieving Sustainable Development Goal 13 (Climate Action), as it provides the necessary data to understand recent climate shifts and project the magnitude of future impacts. The Coupled Model Intercomparison Project (CMIP) is a key international activity that provides the foundational data for these assessments.

Methodology for Climate Projections: Supporting SDG 13 and SDG 11

Quantitative predictions of future climate change are formulated using sophisticated climate models, which integrate fundamental principles of physics, chemistry, and biology. These models are indispensable tools for translating scientific knowledge into actionable policy guidance.

Earth System Models and Global Collaboration

The most advanced tools, known as Earth System Models, simulate the entire planet’s climate system using supercomputers. This work represents a significant investment in SDG 9 (Industry, Innovation, and Infrastructure) through the development and use of high-performance computational infrastructure.

• International climate centers contribute model data to the global CMIP project.
• This collaborative effort, a prime example of SDG 17 (Partnerships for the Goals), allows scientists worldwide to analyze potential climate trajectories.

Regional Projections for Localized Adaptation

While global models provide a broad overview, effective adaptation strategies require more detailed local information. This is particularly relevant for SDG 11 (Sustainable Cities and Communities), which aims to make human settlements resilient.

1. Global model outputs are computationally expensive, resulting in low-resolution data (e.g., grid boxes of 100 kilometers).
2. Scientists employ “downscaling” techniques to generate high-resolution regional climate projections from this global data.
3. This detailed information is vital for national climate risk assessments and is used by local governments and industries to plan for climate resilience.

Advancements in Climate Modeling: The CMIP7 Initiative

The CMIP project has evolved since 1995, with each iteration improving the scientific community’s understanding of the climate system. The upcoming CMIP7 represents a significant step forward, driven by the need for more accurate and comprehensive data to inform progress on the SDGs.

Key Justifications for CMIP7

• Updated Information: CMIP7 will incorporate an additional decade of observational data since the previous iteration (CMIP6), refining projections and improving their accuracy for climate action planning (SDG 13).
• Enhanced Carbon Cycle Simulation: A shift to emissions-driven simulations will allow models to calculate atmospheric greenhouse gas concentrations dynamically. This enhances the ability to simulate interactions between the atmosphere, land, and ocean, which is critical for understanding impacts on SDG 14 (Life Below Water) and SDG 15 (Life on Land). Australia’s contribution will specifically include refined models for local vegetation, bushfires, and ocean biology.
• Higher Resolution: Advances in computational capability (SDG 9) will enable models to run at a significantly higher resolution, providing more granular data for regional risk assessments and supporting resilience efforts under SDG 11.

Australia’s Contribution to CMIP7: A National and Global Partnership

Australia is actively participating in the CMIP7 process through its newest model, ACCESS-ESM1.6. This multi-year initiative is a partnership between CSIRO, ACCESS-NRI, universities, and the Bureau of Meteorology, exemplifying the collaborative spirit of SDG 17.

The CMIP7 Submission Process

1. Preindustrial Spinup: The model is run for approximately 1,000 virtual years with preindustrial greenhouse gas levels to establish a stable and physically consistent baseline.
2. Historical Simulation: A simulation emulating the climate of the last 200 years is conducted to validate the model against observed data.
3. Future Scenarios: A range of future scenarios based on different socio-economic and policy pathways are implemented to generate final climate projections.

As the only Southern Hemisphere nation consistently contributing to CMIP, Australia provides a unique and crucial perspective. The resulting data, estimated at 8 petabytes, will directly inform the next IPCC assessment report and subsequent regional climate projections, ultimately providing the scientific evidence required for future COPs to refine global targets and accelerate action toward achieving the Sustainable Development Goals.

Analysis of Sustainable Development Goals (SDGs) in the Article

SDG 13: Climate Action

• The entire article is centered on the global effort to understand, predict, and address climate change. It explicitly mentions the “Conference of the Parties to the United Nations Framework Convention on Climate Change” (COP), the “Intergovernmental Panel on Climate Change” (IPCC), and the goal of reaching a “global agreement on how to address climate change.” The development of sophisticated Earth system models like ACCESS-ESM1.6 is presented as a fundamental tool for informing climate action, risk assessments, and adaptation plans.

SDG 17: Partnerships for the Goals

• The article highlights multiple layers of collaboration essential for advancing climate science. It describes international partnerships such as the IPCC and the Coupled Model Intercomparison Project (CMIP), which is a “global data project” involving climate centers from “many different nations.” It also details a national-level partnership in Australia “between CSIRO and Australia’s climate simulator (ACCESS-NRI), with support from university-based scientists and the Bureau of Meteorology” to contribute to this global effort. This demonstrates the multi-stakeholder cooperation required to achieve climate goals.

SDG 9: Industry, Innovation and Infrastructure

• While not the primary focus, this goal is connected through the article’s emphasis on scientific research, technological advancement, and the infrastructure required to support it. The text discusses the use of “supercomputers,” “advances in computational capability and modelling software,” and the “high performance supercomputers of the National Computational Infrastructure.” This technological infrastructure is crucial for the scientific innovation (developing Earth system models) that underpins climate action.

Specific SDG Targets Identified

SDG 13: Climate Action

1. Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries. The article directly supports this by explaining that the data from climate models is used for “higher resolution regional climate projections, which will then be used for future climate risk assessments and adaptation plans.” It also mentions the “National Climate Risk Assessment from the Australian Climate Service” as a product of this work.
2. Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction and early warning. The article describes the process of generating scientific knowledge through IPCC reports and CMIP data, which are then used by “local governments, businesses and industry to understand their exposure to climate risk.” This process is a form of capacity building and awareness-raising based on scientific evidence.
3. Target 13.b: Promote mechanisms for raising capacity for effective climate change-related planning and management in least developed countries and small island developing States, including focusing on women, youth and local and marginalized communities. While not explicitly mentioning LDCs or SIDS, the article’s focus on Australia as the “only Southern Hemisphere nation submitting to past CMIPs” highlights the importance of diverse geographical perspectives in global climate modeling, which is a foundational step for effective planning in all regions, particularly those most vulnerable.

SDG 17: Partnerships for the Goals

1. Target 17.6: Enhance North-South, South-South and triangular regional and international cooperation on and access to science, technology and innovation. The CMIP is described as a “global data project” where nations contribute and share data, which is a clear example of international cooperation on science and technology. Australia’s contribution is a specific instance of this global collaboration.
2. Target 17.17: Encourage and promote effective public, public-private and civil society partnerships, building on the experience and resourcing strategies of partnerships. The article explicitly names a multi-stakeholder partnership in Australia involving CSIRO (a government agency), ACCESS-NRI, universities, and the Bureau of Meteorology, demonstrating a public and academic partnership model for achieving a common scientific goal.

SDG 9: Industry, Innovation and Infrastructure

1. Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries, including, by 2030, encouraging innovation and substantially increasing the number of research and development workers and public and private research and development spending. The article is a case study of enhancing scientific research. It details the iterative improvement of climate models (CMIP5, CMIP6, CMIP7), the development of Australia’s newest Earth system model (ACCESS-ESM1.6), and the massive investment in computational resources (“hundreds of millions of compute hours” and “8 petabytes of data”).

Indicators for Measuring Progress

Target 13.1: Strengthen resilience and adaptive capacity

• Implied Indicator: The development and use of national and regional climate risk assessments. The article explicitly mentions the “National Climate Risk Assessment from the Australian Climate Service” and states that model data is used for “future climate risk assessments and adaptation plans.” The existence and regular updating of such plans serve as a measure of progress.

Target 13.3: Improve education, awareness-raising and capacity

• Implied Indicator: The production and dissemination of scientific reports and data for decision-making. The article points to the regular “assessment reports that are written by the Intergovernmental Panel on Climate Change (IPCC)” and the CMIP global data project as key sources of information that are ultimately used to “translate this evidence into global action.” The volume and accessibility of this data are indicators of capacity.

Target 17.6: Enhance international cooperation on science

• Implied Indicator: The number of countries and institutions contributing to global scientific projects. The article refers to “Climate centres from many different nations” contributing to the CMIP project and highlights Australia’s unique role as a Southern Hemisphere contributor. The scale of the data produced (“8 petabytes of data”) also serves as a proxy indicator for the intensity of this collaboration.

Target 17.17: Promote effective partnerships

• Implied Indicator: The number and scope of multi-stakeholder partnerships for sustainable development. The article provides a concrete example of such a partnership: “a partnership between CSIRO and Australia’s climate simulator (ACCESS-NRI), with support from university-based scientists and the Bureau of Meteorology.” Documenting these collaborative efforts is a way to measure progress.

Target 9.5: Enhance scientific research

• Implied Indicator: Investment in research and development infrastructure and activities. The article implies significant investment through its mention of using “high performance supercomputers of the National Computational Infrastructure,” a project that will “consume hundreds of millions of compute hours,” and the multi-year effort to develop and run the new ACCESS-ESM1.6 model for CMIP7.

Summary Table of SDGs, Targets, and Indicators

Source: theconversation.com