Climate change adaptation needs, as well as the capacity to adapt, are unequally distributed around the world. Here we propose ways to quantify adaptive capacity within the framework of Shared Socioeconomic Pathways, a scenario set widely used by climate impact and integrated assessment models.  

This paper provides an assessment on regional perceptions of adaptation constraints and avenues to overcome them based on a mixed-method approach, combining an online survey and semi-structured interviews with adaptation experts from Caribbean SIDS. It finds that finance is the largest constraint being faced.  

Current levels of adaptation finance are woefully insufficient. This brief compares what has been delivered to date, with future commitments, and what the IPCC estimates costs will be in 2030 and 2050.  

Burkina Faso is highly vulnerable to the increasing impacts of climate change and currently has large adaptation deficits. Systematic policy document analysis, semi-structured interviews and participant observations were undertaken to explore how scientific information makes its way into national adaptation policy documents from its production to its inclusion into policies.  

The COP26 climate summit in Glasgow saw important progress made on the Global Goal on Adaptation (GGA). However, there is much work still to be done to bring the GGA concept to life. Striking a balance between the GGA serving its ‘global’ purpose, whilst providing sufficient flexibility for countries to describe their own adaptation objectives and progress will ultimately determine the effectiveness of the GGA.  

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. This paper systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers to identify eight priority areas for research.  

Increasing evidence suggests that climate change impacts are already observed around the world. Global environmental assessments face challenges to appraise the growing literature. Here we use the language model BERT to identify and classify studies on observed climate impacts, producing a comprehensive machine-learning-assisted evidence map.