Question about wrf-python pw: layer vs. column precipitable water

[Arty]

Hello,

I was wondering whether the wrf-python function pw returns precipitable water for a specific model layer/height, or for the vertically integrated column from the surface up to that height.

Based on the documentation, it appears to be the first case (layer-specific), which leads me to a follow-up question: what is the best way to compute column-integrated precipitable water, either from the surface to a specified height or over the full atmospheric column?

My goal is to analyze the spatial distribution of precipitable water over a tropical, mostly oceanic domain with small islands, using high-resolution simulations with convection activated and deactivated. I have noticed that rainfall becomes more spatially homogeneous when convection is activated, and I would like to better understand the physical reasons behind this model behavior.

Thank you for your time and insight.

 

[Ming Chen]

Hi Arty,

I believe PW is vertically integrated precipitable water.

PW calculation in wrf-python simply follows the standard approach in meteorology. I don't have the formula at hand. I suppose it is easy to find it.

 

[Arty]

Hi Arty,

I believe PW is vertically integrated precipitable water.

PW calculation in wrf-python simply follows the standard approach in meteorology. I don't have the formula at hand. I suppose it is easy to find it.

Hi Ming,

Thank you. I believe I was confused by the presence of height in the function variables:

wrf.pw(pres, tkel, qv, height, meta=True)

However, in retrospect, I now understand that the height variable is used together with pressure at each level.