Analyzing Climate Change Consequences through Downscaling Techniques: a Case Study

EasyChair Preprint 14894

Abstract

As global climate change intensifies, understanding its impacts on regional scales is crucial for effective adaptation and mitigation strategies. This study analyzes climate change consequences by employing downscaling techniques to generate localized climate projections. The case study focuses on a coastal region in the southeastern United States, selected for its vulnerability to sea-level rise and extreme weather events. Both statistical and dynamical downscaling methods were applied to assess temperature and precipitation changes, incorporating historical data and future climate projections. Results revealed significant regional variations in climate impacts: statistical downscaling projected an increase in average temperatures by 3-5°C and a rise in the frequency of heavy rainfall events, while dynamical downscaling highlighted more pronounced regional temperature changes and increased risk of coastal flooding due to sea-level rise. The findings underscore the importance of high-resolution climate projections for local planning and adaptation. Recommendations include enhancing downscaling methods, integrating climate projections with impact assessments, and expanding research to other vulnerable regions.

Keyphrases: Coastal Region, Downscaling, Precipitation Changes, Statistical downscaling, climate change, climate impact assessment, dynamical downscaling, extreme weather events, sea level rise, temperature projections

@booklet{EasyChair:14894,
  author    = {Adeoye Ibrahim},
  title     = {Analyzing Climate Change Consequences through Downscaling Techniques: a Case Study},
  howpublished = {EasyChair Preprint 14894},
  year      = {EasyChair, 2024}}