Downscaling, or reduction, refers to the process of simplifying or decreasing the size of data, models, or systems while retaining essential information. This technique is often used in fields like climate science, where large-scale climate models are adjusted to provide more localized predictions. By focusing on smaller areas, researchers can better understand specific impacts and trends. In addition to climate science, downscaling is also applied in areas such as urban planning and economics. For instance, large datasets can be reduced to highlight key indicators, making it easier for decision-makers to analyze and interpret information effectively.