Urban precipitation downscaling using deep learning: a smart city application over Austin, Texas, USA. (arXiv:2209.06848v1 [physics.ao-ph])

Urban downscaling is a link to transfer the knowledge from coarser climate
information to city scale assessments. These high-resolution assessments need
multiyear climatology of past data and future projections, which are complex
and computationally expensive to generate using traditional numerical weather
prediction models. The city of Austin, Texas, USA has seen tremendous growth in
the past decade. Systematic planning for the future requires the availability
of fine resolution city-scale datasets. In this study, we demonstrate a novel
approach generating a …

application arxiv austin city deep learning physics precipitation smart smart city usa