Negative sign of xleeway velocity in leeway module

[Kostas84B]

Dear Knut-Frode, good morning! I am a new user of Opendrift, and I would like to why do you insert -x_leeway instead of x_leeway in self.update_positions in leeway.py?

[knutfrode]

Good morning Kostas!

I agree that this looks a bit strange. However, it is a consequence of the choices that have been made in the previous lines, in particular:

winddir = np.arctan2(self.environment.x_wind, self.environment.y_wind)
....
sinth = np.sin(winddir)
costh = np.cos(winddir)
....
x_leeway = -downwind_leeway*sinth+crosswind_leeway*costh

The last definition of x_leeway could have used opposite signs to make it positive eastwards, and not westwards, which explains the need for the - before x_leeway in the call to update_positions. So this is simply a consequence of the way the geometrical helper drawing was made a long time ago. I don't have this drawing at hand, but you may check that it gives correct results with the following snippet:

from datetime import datetime, timedelta
from opendrift.models.leeway import Leeway
lw = Leeway()
lw.set_config('environment:constant:x_sea_water_velocity', 0)
lw.set_config('environment:constant:y_sea_water_velocity', 0)
lw.set_config('environment:constant:x_wind', 10)  # eastwards wind
lw.set_config('environment:constant:y_wind', 0)
lw.seed_elements(lon=2, lat=60, number=1000, time=datetime.now(), object_type=26)
lw.run(duration=timedelta(hours=48))
lw.plot(fast=True)

So if you remove the - in the call to update_positions, you will get westwards drift, instead of eastwards as expected.

[Kostas84B]

Thanks!

I see. So, in case I want to add an extra velocity (let's say a paddling velocity along the direction of object motion) I could do it using the negative sign as follows:

#first define the direction of motion w.r.t the east direction theta_11 = np.arctan( (y_leeway+self.environment.y_sea_water_velocity) / (self.environment.x_sea_water_velocity-x_leeway) ) #add an x and y velocity component to the already velocity components due to wind and ambient currents x_pad = cacc * np.cos(theta_11) y_pad = cacc * np.sin(theta_11) self.update_positions(x_pad, y_pad)

[knutfrode]

This seems to make sense. But you could do some simple sensitivity tests like the sample above to check whether it works as you intended.

[Kostas84B]

Thanks for the help!!