  Hurricanes and, more generally, tropical cyclones (TCs) are rare, complex
natural phenomena of both scientific and public interest. The importance of
understanding TCs in a changing climate has increased as recent TCs have had
devastating impacts on human lives and communities. Moreover, good prediction
and understanding about the complex nature of TCs can mitigate some of these
human and property losses. Though TCs have been studied from many different
angles, more work is needed from a statistical approach of providing prediction
regions. The current state-of-the-art in TC prediction bands comes from the
National Hurricane Center of the National Oceanographic and Atmospheric
Administration (NOAA), whose proprietary model provides "cones of uncertainty"
for TCs through an analysis of historical forecast errors.
  The contribution of this paper is twofold. We introduce a new pipeline that
encourages transparent and adaptable prediction band development by
streamlining cyclone track simulation and prediction band generation. We also
provide updates to existing models and novel statistical methodologies in both
areas of the pipeline, respectively.
