Shirin Ermis (she/her)

Abstract:

As global temperatures rise, extreme weather events are increasingly causing damages across human health, infrastructure, agriculture, and the broader economy. The science of event attribution is evolving to include estimates of economic damages attributable to climate change in addition to physical impacts. A key challenge in this field is to create physically consistent and high-resolution counterfactuals which can be used to estimate to attributable losses.Here, we analyse the precipitation-driven impacts of Storm Irene in August 2011 when it was undergoing extratropical transition in the Northeastern United States. Across the Northeast United States, this storm caused rainfall of up to 180 mm within a few hours, leading to fluvial and pluvial flooding with catastrophic consequences that caused  more than $1.3 billion in property damages in the state of Vermont alone.Our method enables linking economic damages attributable to climate change to meteorological drivers through a direct modelling chain by combining an operational weather forecasting model, hydrodynamic model, and economic damage model.This research underscores the potential of interdisciplinary attribution methodologies to inform climate risk assessments in insurance and provide an evidentiary basis for climate-related liability.

Abstract:

Since 2004, many methods for event attribution have been developed. Early studies showed that attribution statements are sensitive to the framing of research questions but few large comparisons have been undertaken.Here, we firstly motivate the need for multi-method extreme event attribution, highlighting conceptual differences between methods. In a second part, we present a case study of midlatitude storm Babet (2023) to compare three common storyline attribution methods, alongside a severity-based probabilistic method. We discuss three widely relevant questions which highlight the complementarity and the differences between methods: (1) How has climate change impacted the frequency of the event? (2) How has climate change impacted the event severity? (3) Were the dynamics of the event influenced by climate change and if yes, how?We show that methods differ in the extent to which they reproduce observed weather patterns. This influences attribution statements, and can even change the sign of results for events with uncertain climate signals. We argue that limitations and strengths of methods need to be clearly communicated when presenting event attribution reports to ensure findings can be used reliably by a wide range of stakeholders.

Abstract:

Over the past 20 years, extreme event attribution has developed rapidly, providing a wide range of methods to attribute weather events - from unconditioned probabilistic to strongly conditioned storyline approaches. Advancing the field now requires combining results from multiple methods, allowing more robust conclusions drawing from various lines of evidence. Yet, doing so remains challenging. We call for closer interaction within the attribution field to develop approaches with method comparison in mind. We highlight the need to explicitly define the research questions answerable by specific methods, and to clearly outline the limitations of each method.