Ethan Gutmann is a hydrometeorologist and the director of the Water Cycle Applications Program in the Research Applications Lab at the National Center for Atmospheric Research (NCAR).  Dr. Gutmann has a background in hydrology, geology, and computer science; he found a happy marriage of these in large scale hydroclimate research.  Dr. Gutmann has published scientific articles in topics related to hydrology, mountain snowpack, and climate change; most of his work has focused on understanding the impacts of climate change on water resources and mountain snowpack.  Dr. Gutmann is the past chair of the AMS Mountain Meteorology committee and the lead scientist and developer of the Intermediate Complexity Atmospheric Research model (ICAR). He has worked closely with water resource managers at the US Bureau of Reclamation and the Army Corps of Engineers, as well as with scientists at NASA, NOAA, DoD, and universities around the world.

Outside of science, Gutmann is also an avid outdoor enthusiast and is enjoying introducing his kids to backpacking, climbing, skiing, and more. His passion for the outdoors has taken him to remote mountains around the world, which has furthered an interest in snow related processes in high altitude regions. This partially explains his current research in snow modeling and measurement, as well as atmospheric modeling of precipitation and turbulence in the mountains.  In addition, Ethan enjoys scientific outreach, having dabbled in science blogging at arstechnica, and science videography with Earth Initiatives.

Ethan Gutmann studies meteorological downscaling for hydrology, mountain snowpack measurement and modeling, canopy interception measurement, land surface atmosphere interactions, and soil hydrology.

ICAR

Ethan developed the Intermediate Complexity Atmospheric Research model (ICAR), which is capable of running hundreds to thousands of times faster than state of the art regional climate models (e.g. WRF) while still providing ~90% of the information about precipitation and temperature patterns.  ICAR enables quasi-dynamical downscaling of global models based on first principles instead of statistics.  More recent work has focused on the use of modern machine learning foundation models to perform dynamical downscaling from hours to decades. 

Snow Measurement

Ethan has also developed novel techniques to measure snow on the ground through the use of terrestrial scanning lasers and GPS interferometry.  The most recent lidar system was deployed as part of the Sublimation of Snow (SOS) field campaign and mapped snow dunes and snow drift formation at very high spatio-temporal resolutions for the entire winter season.