Climate Evidence-Based Design: A Conceptual Framework for Early-Stage Climate-Responsive Building Performance Decisions

Early architectural decisions on orientation, window-to-wall ratio, shading, and envelope composition fix most of a building’s passive thermal performance long before dynamic energy simulation becomes feasible, leaving these decisions without a structured evidentiary basis. This paper proposes Climate Evidence-Based Design (CEBD), a conceptual framework specializing the evidence-based design tradition from healthcare and workplace research into the climatic, physical, and material evidence needed for integrated, early-stage building decisions. CEBD organizes four components: a diagnosis of why evidence arrives too late to inform early-stage climate-responsive decisions; a six-tier evidence-source structure ordered by increasing directness and analytical control, from design heuristic to measured monitoring, complemented by independent case-specific qualifiers of reliability, contextual relevance, transferability, and uncertainty; Architectural Intent, showing how a project’s declared priorities change which recommendation identical evidence supports; and a mechanism for applying graded evidence before simulation is feasible, without displacing it once it is. A single conceptual model integrates climate evidence, envelope physics, and material sustainability into an operational structure, the Climate Evidence-Based Design Methodology (CEBDM), through which a design team applies graded evidence to early-stage climate-responsive building-performance decisions. CEBD is deliberately bounded to climate-responsive building-performance decisions; it does not attempt to classify or evaluate architectural quality, cultural meaning, tectonic expression, or spatial composition. By making the evidentiary basis of passive design explicit and inspectable, CEBD is a conceptual foundation for future evidence-based design tools. This paper establishes CEBD’s specification and internal logic to support empirical testing; it reports the framework’s construction, together with a retrospective application to a previously published case corpus that demonstrates the applicability of its categories and not the effectiveness of the framework, and identifies the validation studies required as next steps: empirical tests of whether this multidimensional evidence representation is associated with subsequently validated performance outcomes.