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Novel approach to improving precipitation forecasts over complex terrain


New member
We are looking for someone with experience with WPS who might consider it a fun challenge to help us get a new capability into WPS (and perhaps test it on some interesting cases). A former PhD student of mine, Tom Robinson, developed a novel method for modeling the lowest level vertical motion in WRF and applied it in Hawaii. Tom’s method allows precipitation generated by our steep orography to be more accurately predicted with lower resolution, less compute intensive WRF runs (see link to reference below). The approach Tom used was to take high resolution USGS terrain data and calculate the gradient of the terrain (dh/dx and dh/dy). Then he smoothed the gradient to fit the model resolution. Finally, he changed the boundary condition where w is calculated to use the new gradient that he had calculated (u dh/dx and v dh/dy). It is fairly simple coding. Unfortunately, Tom only set it up in a custom way over the island of Oahu and is currently swamped with a full-time position. We believe the approach could have significant value for the broader community if it were generalized and made available as an option in the WRF Preprocessing System (WPS). For example, in modeling the interaction of atmospheric rivers with the Sierra Nevada or Cascade Mountains.

Please let us know if you are interested in this promising approach.

Robinson, T. E. and S. Businger, 2019: A Novel Method for Modeling Lowest-Level Vertical Motion, Weather and Forecasting, 34, 943 - 957.

Best regards, Steven Businger and Tom Robinson
University of Hawaii