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This research paper evaluates the diversity of six major global scenario sets used in climate research and policymaking to determine how effectively they span the uncertainty space of future environmental change.

This research paper by the Climate Policy Initiative evaluates methodologies for tracking investments in climate resilient infrastructure (CRI). The study pilots a framework based on five climate resilience principles across the water, transport, energy, and AFOLU sectors, finding that CRI investments are a small fraction of total infrastructure spending, with USD 87 spent on non-resilient projects for every USD 1 spent on CRI.

This research paper evaluates the use of MODIS satellite data and spectral indices to map open water surfaces in coastal wetland systems, specifically testing the effectiveness of the MNDWI6 index and a new threshold optimization method.

This report examines the use of social strategy games as a research and communication tool to help people understand the complex trade-offs and synergies between climate change mitigation and adaptation strategies in urban environments.

This research paper compares two methods for calculating energy footprints embodied in trade for the United Kingdom in 2002: the National Footprint Accounts' Product Land Use Matrix (NFA-PLUM) and a multi-region input–output model (MRIO). While total import and export figures are comparable between the two, the study finds significant discrepancies when results are broken down by economic sector.

This report details the proof of concept testing (POCT) of the Canadian Biodiversity Index (CBI), a tool designed to consistently assess and convey biodiversity status and trends across Canada. The testing applied the CBI framework to two distinct ecounits—Netley-Libau Marsh in Manitoba and Banks Island in the Northwest Territories—to evaluate the index's methodology, the effectiveness of its normalized scoring scale, and the challenges of data availability.

This briefing by the Stockholm Environment Institute (SEI) details a pilot project evaluating the use of the SEI AI Reader, a tool based on large language models, to conduct systematic policy analysis. The project tested the tool's ability to extract data from policy evaluations and audits using a framework of 12 independent variables and 46 questions, focusing on climate policy implementation. The results indicate that with iterative prompt calibration, the AI can achieve high levels of accuracy and consistency, making it a viable method for processing large volumes of grey literature to identify drivers of successful policy outcomes.