Scientists Call for Real-Time Analysis of Tropical Cyclones in the Context of Climate Change – SBU News

Real-time Attribution of Climate Change on Extreme Weather Events: Hurricane Ian Case Study

STONY BROOK, NY, October 10, 2023 – The need for quick and “real-time” forecasting of tropical cyclones is more necessary than ever given the impact of climate change on rainfall amounts. Two climate scientists who believe this take the notion further by suggesting a storyline case study of Hurricane Ian in 2022 can be used as a blueprint for rapid operational climate change attribution statements about extreme storms. Their premise is detailed in a paper published in the journal Environmental Research: Climate.

Introduction

Co-authors Kevin A. Reed, PhD, Professor and Associate Dean of Research in the School of Marine and Atmospheric Sciences at Stony Brook University, and Michael F. Wehner, PhD, of the Lawrence Berkeley National Laboratory in California, note that tropical cyclones such as Hurricane Ian are devastating events worldwide, endangering lives and causing damage costing billions of dollars to repair. Therefore, the public, media, and governmental leaders affected by such extreme storms turn to scientists to understand more about the weather event and how climate change may have affected it.

Rapid Attribution Methodology

In “Real-time attribution of the influence of climate change on extreme weather events: A storyline case study of Hurricane Ian rainfall,” the authors point out that previously it has taken months or even years after extreme storms for scientific studies to supply results on how such storms were impacted by climate change. Their work shifts this paradigm by providing a tropical cyclone rainfall rapid attribution methodology designed for use by operational climate change attribution centers.

Rapid Assessment During Hurricane Ian

Hurricane Ian made landfall in Florida on September 22, 2022. While the storm was still over Florida, Reed and Wehner used social media to alert the public that climate change increased Ian’s total rainfall by at least 10 percent. They also further informed the public and officials of this phenomenon, along with the media, via their quick scientific work during and in the immediate aftermath of the storm.

Results and Implications

Their initial statement was a deliberately conservative lower bound given the brief period of time available for analysis. Subsequent analysis supports the published “best estimate” of the precipitation increase due to human-induced climate change of 18 percent.

Using a previously developed and tested hindcast attribution methodology in near real-time, the researchers demonstrated that Ian storyline rapid assessments of tropical cyclones can be completed during extreme storms. The authors state that “such rapid assessment offers scientists a useful tool in answering questions about the climate change effect on individual extreme weather events as they unfold.”

The authors further point out that storyline attribution methods can be useful when traditional event attribution methods are not tractable. This is particularly the case in developing nations where the high-quality long-time weather observations necessary for traditional climate change attribution may not be available but weather forecasts demonstrate adequate skill. This capability can then inform decision makers in future loss and damage negotiations.

Conclusion

The research leading to this paper was supported in part by a Department of Energy (DOE) Office of Science award number DE-SC0016605, and the Stony Brook Foundation’s Minghua Zhang Early Career Faculty Innovation Fund. High-performance computing support was provided by the National Center for Atmospheric Research’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Work at Berkeley Lab was supported by the Director, Office of Science, Office of Biological and Environmental Research of the U.S. Department of Energy under Contract No. DE340AC02-05CH11231 under the Regional and Global Model Analysis (RGMA) program.

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SDGs, Targets, and Indicators Analysis

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 13: Climate Action
• SDG 11: Sustainable Cities and Communities
• SDG 9: Industry, Innovation, and Infrastructure

The article discusses the need for quick and real-time forecasting of tropical cyclones, which is directly related to SDG 13 – Climate Action. The authors highlight the impact of climate change on rainfall amounts and how it affects extreme storms like Hurricane Ian. This connects to SDG 11 – Sustainable Cities and Communities, as extreme storms pose a threat to communities and their infrastructure. Additionally, the article mentions the use of social media to alert the public about climate change’s influence on Hurricane Ian, which relates to SDG 9 – Industry, Innovation, and Infrastructure.

2. What specific targets under those SDGs can be identified based on the article’s content?

• SDG 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
• SDG 11.5: Reduce the number of deaths and people affected by disasters
• SDG 9.5: Enhance scientific research, upgrade technological capabilities, and increase access to information and communication technologies

The article emphasizes the need for quick and real-time forecasting of tropical cyclones to strengthen resilience and adaptive capacity to climate-related hazards (SDG 13.1). It also highlights the importance of providing attribution statements about climate change’s impact on extreme storms to inform decision-makers and reduce the number of deaths and people affected by disasters (SDG 11.5). The use of social media to disseminate information about climate change and extreme storms aligns with the target of enhancing scientific research, upgrading technological capabilities, and increasing access to information and communication technologies (SDG 9.5).

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions the following indicators:

• Rapid operational climate change attribution statements about extreme storms
• Increased total rainfall by at least 10% due to climate change
• 18% precipitation increase due to human-induced climate change (best estimate)
• Completion of simulations and analysis of tropical cyclones during extreme storms
• Availability of high-quality long-time weather observations and weather forecast skill

These indicators can be used to measure progress towards the identified targets by assessing the speed and accuracy of attributing extreme storms to climate change, quantifying the impact of climate change on rainfall, and evaluating the ability to simulate and analyze tropical cyclones in real-time.

Table: SDGs, Targets, and Indicators

Behold! This splendid article springs forth from the wellspring of knowledge, shaped by a wondrous proprietary AI technology that delved into a vast ocean of data, illuminating the path towards the Sustainable Development Goals. Remember that all rights are reserved by SDG Investors LLC, empowering us to champion progress together.

Source: news.stonybrook.edu

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