Katharine J. Mach | Searcharxiv

arXiv2026

AI-Assisted Scientific Assessment: A Case Study on Climate Change

The emerging paradigm of AI co-scientists focuses on tasks characterized by repeatable verification, where agents explore search spaces in 'guess and check' loops. This paradigm does not extend to problems where repeated evaluation is impossible and ground truth is established by the consensus synthesis of theory and existing evidence. We evaluate a Gemini-based AI environment designed to support collaborative scientific assessment, integrated into a standard scientific workflow. In collaboration with a diverse group of 13 scientists working in the field of climate science, we tested the system on a complex topic: the stability of the Atlantic Meridional Overturning Circulation (AMOC). Our results show that AI can accelerate the scientific workflow. The group produced a comprehensive synthesis of 79 papers through 104 revision cycles in just over 46 person-hours. AI contribution was significant: most AI-generated content was retained in the report. AI also helped maintain logical consistency and presentation quality. However, expert additions were crucial to ensure its acceptability: less than half of the report was produced by AI. Furthermore, substantial oversight was required to expand and elevate the content to rigorous scientific standards.

cs.CL↗

arXiv2025

Recognizing Salt Wave Events in Coastal Systems

Saltwater intrusion is a critical challenge to coastal ecosystems, impacting freshwater resources, biogeochemical cycles, and habitat stability. While relevant studies often focus on the long-term trends of salinity, its episodic variability and resulting ecological disturbance remains underexplored. Here, we introduce the concept of "coastal salt waves" - periods of elevated salinity anomalies, akin to heat waves - to better characterize extreme salinity events and emphasize their significance. Using cases studies, we show that coastal salt waves exhibit significant spatial and temporal variability based on their duration, intensity, frequency, cumulation, and timing, with drivers and impacts that may differ from gradual saltwater intrusion. In years with similar average salinity, salt waves may still vary greatly in characteristics like intensity, resulting in varying environmental impacts. Furthermore, systems without rising average salinity may still face more frequent or intense salt waves. This framework supports monitoring and management strategies to mitigate coastal salinization risks.

physics.geo-ph↗