Amid escalating climate impacts, understanding private sector adaptation is critical. Here using data of actual adaptation expenditures from nearly 300,000 businesses in five coastal regions, we reveal variations in private sector adaptation across sectors and regions. The agriculture sector leads in adaptation efforts, while transport, construction and utilities—that is potential sources of system-wide cascading effects—lag. Small, medium and large businesses prioritize hard and soft measures, barely investing in ecosystem-based adaptations. Adding to the multifaceted discourse on adaptation effectiveness, our panel data reveal positive, although inelastic in the short run, relationships between private sector adaptations and aggregate regional economic performance. Business adaptations in the construction, transport and health sectors associate positively with regional economic performance, with the accommodation and food services sector yielding the highest return per euro invested in adaptation. Combining these findings with existing assessments of adaptation could support the development of societally effective adaptation strategies.

Climate policy faces increasingly complex challenges that span multiple human decision scales in nature-society systems. Contemporary climate policy models, while valuable and increasingly versatile in handling spatial and temporal scales, struggle to capture interacting multiscale decisions on the socioeconomic side. This perspective draws attention to the power of coupling among different modeling families, taking integrated assessment models (IAM), computable general equilibrium models (CGE), and agent-based models (ABM) as examples. Recent computational advances, maturity of models, availability of data, and interdisciplinary expertise make model coupling an increasingly feasible, effective, and useful tool for climate policy analysis. We examine the unique contributions of each modeling approach, highlight synergies from uniting their strengths, and discuss alternatives to and conditions for coupling. In addressing methodological challenges, we present examples of effective coupling of IAM-ABM-CGE, emphasizing the importance of maintaining model integrity while enhancing policy relevance. By bridging human decision scales and leveraging complementary strengths, coupled models can provide nuanced insights into climate-economy interactions, ultimately supporting effective and equitable-not just efficient and optimal-climate policies.

Despite the growing calls to integrate realistic human behavior in sustainability science models, the representative rational agent prevails. This is especially problematic for climate change adaptation that relies on actions at various scales: from governments to individuals. Empirical evidence on individual adaptation to climate-induced hazards reveals diverse behavioral and social factors affecting economic considerations. Yet, implications of replacing the rational optimizer by realistic human behavior in nature-society systems models are poorly understood. Using an innovative evolutionary economic agent-based model we explore different framings regarding household adaptation behavior to floods, leveraging on behavioral data from a household survey in Miami, USA. We find that a representative rational agent significantly overestimates household adaptation diffusion and underestimates damages compared to boundedly rational behavior revealed from our survey. This "adaptation deficit" exhibited by a population of empirically informed agents is explained primarily by diverse "soft" adaptation constraints-awareness, social influences-rather than heterogeneity in financial constraints. Besides initial inequality disproportionally impacting low/medium adaptive capacity households post-flood, our findings suggest that even under a nearly complete adaptation diffusion, adaptation benefits are uneven, with late or less-efficient actions locking households to a path of higher damages, further exacerbating inequalities. Our exploratory modeling reveals that behavioral assumptions shape the uncertainty of physical factors, like exposure and objective effectiveness of flood-proofing measures, traditionally considered crucial in risk assessments. This unique combination of methods facilitates the assessment of cumulative and distributional effects of boundedly rational behavior essential for designing tailored climate adaptation policies, and for equitable sustainability transitions in general.

Climate change intensifies the likelihood of extreme flood events worldwide, amplifying the potential for compound flooding. This evolving scenario represents an escalating risk, emphasizing the urgent need for comprehensive climate change adaptation strategies across society. Vital to effective response are models that evaluate damages, costs, and benefits of adaptation strategies, encompassing non-linearities and feedback between anthropogenic and natural systems. While flood risk modeling has progressed, limitations endure, including inadequate stakeholder representation and indirect risks such as business interruption and diminished tax revenues. To address these gaps, we propose an innovative version of the Climate-economy Regional Agent-Based model that integrates a dynamic, rapidly expanding agglomeration economy populated by interacting households and firms with extreme flood events. Through this approach, feedback loops and cascading effects generated by flood shocks are delineated within a socio-economic system of boundedly-rational agents. By leveraging extensive behavioral data, our model incorporates a risk layering strategy encompassing bottom-up and top-down adaptation, spanning individual risk reduction to insurance. Calibrated to resemble a research-rich coastal megacity in China, our model demonstrates how synergistic adaptation actions at all levels effectively combat the mounting climate threat. Crucially, the integration of localized risk management with top-down approaches offers explicit avenues to address both direct and indirect risks, providing significant insights for constructing climate-resilient societies.