Energy and Meteorology Portal

Understanding Risk and the Sendai Framework

Framework for Climate Risk

Exposure and sensitivity to climate change, coupled with a relatively low adaptive capacity to offset system vulnerabilities can considerably increase climate risk. Therefore, it is important to quantify the risk posed by climate change and extreme weather events, to better address, plan, adapt and respond to their various, and sometimes compounded, associated threats.

Over the past few decades, there has been a growing emphasis on the need to build a resilient society, which is in harmony with the natural environment. Consequently, even energy systems need to widely reduce their environmental impacts, while contributing to human well-being and development in a sustainable manner. A close coupling between society, nature and the energy systems will be even more important when extreme events or local regime shifts (e.g. from a mild to a hot climate) occur. To plan and take action, the capacity to forecast not only climate variations but also energy demand and generation in order to create scenarios with a high level of accuracy and at different periods is key.

Risk is a combination of three components: hazard, exposure, and vulnerability (Figure 1, click on the blue dots for their definitions).

Climate-related risks are dynamic and changing. Weather and climate hazards like storms, cyclones, or droughts may increase in frequency and intensity in some areas, and be reduced in others. But with good planning, weather-proofing of infrastructure, capacity building and timely and efficient responses, both vulnerability and exposure can be reduced or at least be managed. Collecting data, at a certain location, to evaluate each of these components can be used to assess the future risk that is very context specific (UN-DRR, 2015).
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Figure 1. Dynamic Risk: Hazard, Exposure and Vulnerability

To incorporate key elements of the dynamic and emerging risks, it is important to include the interaction between various risk factors, and multiple time scales have been currently recognized. These kinds of assessments are becoming increasingly accurate thanks to the advancements of W&CSs, as for instance reanalysis data and improved climate projection models improve in quality and are also easier to access. Nevertheless, there is a need of developing encompassing system models that allow a better understanding of the impacts of climate risks across sectors at different spatial and temporal scales.
The influence of drivers to vulnerability can change during the temporal progression of a hazard. It is therefore critical to ensure that there are mechanisms and procedures to incorporate local knowledge to assist with risk assessments to understand locally and regionally specific vulnerabilities (Viner et al, 2020).
Climate projections are available at various levels of resolution, but there can be a trade-off between robustness and capturing fine-grain detail. There is generally greater confidence in projections at a larger geographical scale, and for some variables (e.g. temperature) rather than others (e.g. precipitation).

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