Climate change has very wide-ranging economic impacts, particularly on bay areas, which serve as critical hubs for global maritime networks and complex ecological systems. While comprehensive economic assessments are essential for guiding regional adaptation, existing macroeconomic models often rely on globally homogenous damage functions that fail to capture localized vulnerabilities. To this end, we develop an integrated evaluation framework that combines systematic meta-analysis with a regionally adapted Marine-DICE model to provide a much more complete economic valuation of climate risks in bay areas. Using many estimates from models and expert elicitations, we systematically synthesize fragmented empirical data into three core impact channels: physical and infrastructure risks, ecological and natural resource risks, and macroeconomic and spillover risks. This is achieved by extracting and standardizing effect sizes across these diverse studies. Within the macroeconomic meta-analysis, we apply specific constraints to evaluate supply chain trade resilience, capturing trade spillovers and labor productivity declines rather than focusing on generalized value chain optimization. Meanwhile, tailored to the coastal zone complex system characteristics of bay areas, we construct the Marine-DICE model and embed these meta-calibrated parameters to achieve a dynamic assessment of regional macroeconomic output trajectories and long-term welfare losses under multiple scenarios. This advanced framework offers a rigorous foundation for projecting localized climate risks and designing targeted adaptation policy interventions in bay areas.