Dist_beam or constant ROI

Joshwx · January 15, 2026, 10:36pm

Hi,

I currently am working on a project involving 5 different radars and plotting them to a grid via grid_from_radars. This past week I have been trying to decide of whether using the dist_beam function or a constant ROI value for the weighting aspect of my grids to work along with Barnes2. I am mainly wondering if there is additional information on the dist_beam function and how exactly it works to support my decision between that and a constant ROI.

Thanks,

Josh

zssherman · January 15, 2026, 11:17pm

Hi @Joshwx , there is some more info in the docs here:

github.com/ARM-DOE/pyart

pyart/map/grid_mapper.py

6af6edb4d


      
          gatefilters : GateFilter, tuple of GateFilter objects, optional
              Specify what gates from each radar will be included in the
              interpolation onto the grid. Only gates specified in each gatefilters
              will be included in the mapping to the grid. A single GateFilter can
              be used if a single Radar is being mapped. A value of False for a
              specific element or the entire parameter will apply no filtering of
              gates for a specific radar or all radars (the default).
              Similarily a value of None will create a GateFilter from the
              radar moments using any additional arguments by passing them to
              :py:func:`moment_based_gate_filter`.
          roi_func : str or function
              Radius of influence function. A functions which takes an
              z, y, x grid location, in meters, and returns a radius (in meters)
              within which all collected points will be included in the weighting
              for that grid points. Examples can be found in the
              :py:func:`example_roi_func_constant`,
              :py:func:`example_roi_func_dist`, and
              :py:func:`example_roi_func_dist_beam`.
              Alternatively the following strings can use to specify a built in
              radius of influence function:

But essentially the dist roi functions account for beam spacing as the beam goes out so the radius increases to captures gates due to beam spread. There are other parameters like bsp h factor etc you can provide for height scaling, virtual beam width etc. In terms of which would be best, dist beam might work best because as the beam goes out you would want a larger ROI to capture data points/neighbors, a constant ROI wont do that at further distances. Trapp and Doswell discuss this:

https://journals.ametsoc.org/view/journals/atot/17/2/1520-0426_2000_017_0105_rdoa_2_0_co_2.xml

Joshwx · January 16, 2026, 10:34pm

Okay, thank you so much for some guidance!

-Josh

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Dist_beam or constant ROI

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