Advancing Climate Attribution: A Tribute to Geert Jan’s Legacy

The article commemorates the publication of a paper by Geert Jan and the author that introduces a quantitative statistical synthesis method for rapid probabilistic event attribution. This advance allows for a more comprehensive understanding of how climate change influences extreme weather events. The paper also addresses the limitations of current models and the importance of evaluating data quality and methodological soundness in attribution studies.

Three years after the passing of Geert Jan, we commemorate his legacy as we publish the last paper we collaborated on, coinciding with the approaching 10-year anniversary of World Weather Attribution. This paper outlines a novel quantitative statistical synthesis method we developed during our eight-year exploration of rapid probabilistic event attribution studies. While the manuscript may not captivate a general audience, it marks a crucial advancement in our ability to quantify the overarching influence of climate change on the intensity and likelihood of extreme weather events—a methodological evolution we refer to as hazard synthesis. Many studies on attribution have relied solely either on climate models or weather observations, rarely integrating both or analyzing the multifaceted nature of extreme events thoroughly. Our approach allows for a more comprehensive evaluation, realistically reflecting the complex interplay between climate change and extreme atmospheric occurrences. Despite our significant advancements, we have encountered certain limitations, particularly in estimating how much more probable certain extreme weather events have become compared to a hypothetical 1.3°C cooler world devoid of climate change impacts. This has been particularly evident in extreme weather phenomena observed in regions such as the Mediterranean and the Sahel over recent years. Furthermore, discrepancies often arise between climate model outputs and established physical principles governing weather behaviors. For instance, the Clausius-Clapeyron relation indicates that warmer atmospheres retain greater moisture, leading to intensified rainfall—an observation corroborated in several locations. Nevertheless, instances in countries across the Global South reveal that climate models frequently fail to match observed rainfall patterns, highlighting gaps in our predictive capabilities. Nevertheless, when model outcomes align with observational data, synthesis becomes feasible, allowing for precise quantification of changes in intensity and likelihood of extreme events. For example, our research in 2022 concluded that climate change increased the probability of a lethal heatwave in Argentina and Paraguay by 60-fold, and recently, we noted that Hurricane Helene’s rainfall escalated by approximately 10% due to climate change. The paper further emphasizes important evaluative questions regarding attribution studies. These inquiries include assessing the statistical model’s fit with data, the quality of observational data, consistency among different climate models, and whether results align with established physical science principles. The complexity of these issues elucidates why automation or reliance on artificial intelligence for hazard analysis is insufficient. As Geert Jan astutely remarked, “you need time and experience to know when your numbers lie.”

The article discusses the pivotal development of a statistical synthesis method for rapid probabilistic event attribution, culminating in a collaborative paper written by the author and Geert Jan. This advancement plays a significant role in assessing the extent to which climate change affects extreme weather events and addresses challenges faced in aligning climate models with observed data. Through the elucidation of these concepts, the article highlights the methodological evolution and its implications for the field of climate science and event attribution.

In conclusion, the collaborative research led by Geert Jan and the author represents a significant methodological step in the domain of event attribution, particularly regarding the quantification of how climate change influences extreme weather. Despite recognizable limitations, the established synthesis method promises to enhance our understanding of climate impacts, facilitating more informed discussions and interpretations within the field. Continued scrutiny of the methodology and observational data remains critical in resolving the ongoing discrepancies between climate models and real-world phenomena.

Original Source: www.worldweatherattribution.org