I'm currently doing my master's research on supercells where I'm writing the mesocyclone vrot, diameter, and altitude at which these occur. I am looking at NEXRAD radar files. I was doing it in GR2 but felt this process was a time-sink and subjective way to do my research. Since then, I've created a code using Py-ART to grid my radar object on a 500m x 500m x 500m grid using the Barnes2 weighting function and 'dist_beam' ROI.
The problem I'm having is that my vrots for all my storms tend to be 2-6 m/s lower than that on GR2. For example, from one volume scan, GR2 Vrot values I get are:
- 11.28865979 m/s at an avg beam height of 719 m
- 11.03092784 m/s at an avg beam height of
1132 m
- 10.51546392 m/s at an avg beam height of
1583 m
These are the Vrot values I get from Py-ART with *no* gatefilter exclusions and used the region-based dealiasing function (I found that the gatefilter made the discrepancies worse):
- 8.5 m/s at a grid altitude of 500 m
- 8 m/s at a grid altitude of 1000 m
- 7 m/s at a grid altitude of 1500 m
I found these values by: 1) subtracting the SMV (found from GR2) from the base velocity radar field by the formula SMV = (translational_motion)*np.cos(np.deg2rad((azimuth_2d-SMVangle)%360)), then subtracting this from the dealiased velocity srv=base_vel-SMV; 2) plotting them at altitude = j using contourf and finding the appropriate polygons through lots of loops I will not post here; 3) calculated vrot using the formula vrot = np.abs(outbound_max-inbound_max)/2. 4) do this for every other subsequent altitude until couplet is no more (I use input a lot as well - I'm not a coder/algorithm-maker, but it works well otherwise).
I wanted to pick your brains and see why they are considerably lower than GR2, whether that is just the nature of gridding a radar (especially mapping the gates to the grid - I tried mapping it to the grid and it took 30+ mins), or if dealiasing could also be a problem. I also wanted to see if anyone had any suggestions on how to correct this or if you've also had this problem.
Best,
Tori