What is the primary reason for downscaling global climate model outputs to local scales for flood risk projections?

The primary reason for downscaling Global Climate Model (GCM) outputs to local scales for flood risk projections is that GCMs operate at spatial resolutions too coarse to represent the fine-scale meteorological, topographical, and land surface features critical for accurately simulating local hydrological processes that lead to flooding. Global Climate Models (GCMs) are complex mathematical representations of Earth's climate system, designed to simulate future climate at a global or continental scale. They typically use grid cells that average climate conditions over very large areas, often ranging from 50 to 300 kilometers per side. This means a single GCM grid cell can encompass entire mountain ranges, multiple river basins, and diverse land uses. Consequently, GCMs cannot resolve localized atmospheric phenomena like individual convective thunderstorms, which are crucial for generating extreme precipitation events over small areas. More importantly, they cannot capture the variability of local topography, such as river valleys, floodplains, and specific slopes, nor can they distinguish between different types of local land cover, such as urban areas, forests, or agricultural fields. All these fine-scale details—local precipitation patterns, terrain elevation, and land surface characteristics—profoundly influence how water infiltrates the ground, runs off the surface, and accumulates within a specific river catchment or urban area, directly determining the likelihood and severity of a flood event. Downscaling is the process of transforming these coarse-resolution GCM outputs, such as projected changes in temperature and precipitation, into finer-resolution information. This finer-scale data is essential because hydrological models, which are used to simulate water movement and predict flood inundation, require inputs at much higher resolutions, often down to tens or hundreds of meters. Without downscaling, the average climate conditions provided by GCMs over vast regions would lead to highly inaccurate or even misleading flood risk assessments at the local level, where flood mitigation and adaptation decisions are made.