headshot

Bryan Mundhenk

PhD Candidate, Barnes & Maloney Research Groups
email: bryan dot mundhenk at colostate dot edu


Atmospheric River (AR) Research

AR Detection Algorithm

  • Algorithm, Python 2.7 Web Version
  • Disclaimer: This algorithm was written by an atmospheric scientist, not a formally-trained developer; as a result, inefficiencies and code quirks may exist. Comments regarding errors or potential efficiencies are welcomed.
  • See Mundhenk et al., (2016) for details regarding this detection algorithm. Should you find this algorithm beneficial to your research, please acknowledge this work by citing the aforementioned article.
  • See also the poster presented during the 2015 AGU Fall Meeting related to this research.
  • This algorithm executes in < 1 hour in an OS X desktop environment (w/ 3.2 GHz Intel Core i5 and 16 GB RAM) for the 36 years of 6-hourly MERRA data truncated to the North Pacific basin. No effort has been made to optimize the performance of the program; however, the approach would support parallel processing.
  • Thanks to the ever-growing community behind the Python programming language and specifically to the developers of the modules used in this code for furthering open source programming and computing!

AR Climatology

  • Mean All-Season AR Frequency of Occurrence Plot
  • The plot linked above depicts the all-season mean AR frequencies over the North Pacific based on ARs detected within 36 years (1979-2014) of MERRA-derived vertically-integrated water vapor transport anomalies.

Related Publications





* Downloads courtesy of the American Meteorological Society (AMS), who owns sole rights to them, and are subject to AMS copyright laws and statutes; for more information, visit the AMS Journals website.
^ Downloads courtesy of the American Geophysical Union (AGU), who owns sole rights to them, and are subject to AGU copyright laws and statutes; for more information, visit the AGU Publications website.
Further reproduction or electronic distribution is not permitted.