Hi Roberto,

Many thanks for your answer. I just had a look to the link you sent me but I will try it soon!

Laurent.

Salut Laurent,

A wind diagnostic model has been developed by Francis Ludwig at Stanford (http://www.met.sjsu.edu/~wind/FrancisLLudwig/flludwig.html)

See analyses for San Francisco area at:

http://www.met.sjsu.edu/cgi-bin/wind/windbin.cgi

and associated references:

Ludwig, F. L. and D. Sinton, 2000; Evaluating an Objective Wind Analysis Technique with a Long Record of Routinely Collected Data, J. Appl. Meteorol., 39, 335-348.

Ludwig, F. L., J. M. Livingston, and R. M. Endlich, 1991: Use of Mass Conservation and Dividing Streamline Concepts for Efficient Objective Analysis of Winds in Complex Terrain, J. Appl. Meteorol., Vol. 30, pp. 1490-1499.

Endlich, R.M., F.L. Ludwig, C.M. Bhumralkar, and M.A. Estoque, 1982: A Diagnostic Model for Estimating Winds at Potential Sites for Wind Turbines. J. Appl. Meteor., 21, 1441-1454

Ludwig , F.L. and G. Byrd, 1980: An efficient method for deriving mass-consistent flow fields from wind observations in rough terrain, Atmos. Environ., 14, 585-587

A way to approach this question is to use 3D Quiver Plots as available in Matlab.

3D Quiver Plots (quiver3) display vectors consisting of (u,v,w) components at (x,y,z) locations. For example, you can show the path of a wind vector as a function of time, and evidently a DEM.

Assign values to the constants vz and a:

vz = 10; % Velocity

a = -32; % Acceleration

Calculate the height z as time varies from 0 to 1 in increments of 0.1:

t = 0:.1:1;

z = vz*t + 1/2*a*t.^2;

Calculate the position in the x and y directions:

vx = 2;

x = vx*t;

vy = 3;

y = vy*t;

Compute the components of the velocity vectors and display the vectors using the 3-D quiver plot:

u = gradient(x);

v = gradient(y);

w = gradient(z);

scale = 0;

quiver3(x,y,z,u,v,w,scale)

view([70 18])

There ya go.

Frank

Dear Robert, dear Franck,

Thank you very much for your detailed answers. I will see the work of Ludwig and try 3D Quiver Plots very soon. We keep in touch!

Best regards,

Laurent.

WOCSS is a good choice for many applications, although not so much for highly unstable conditions.  The GPL'd release of WOCSS is on github now.

(I would not recommend CalMet, as it really doesn't have the same resolution or physics capabilities, and was not designed for the same kinds of applications, whereas WOCSS has been heavily used/tested in several different applications  such as wind energy, flow & transport, forecast grid downscaling, air quality, etc)

https://github.com/sarnold/gwocss

Many thanks Stephen for your answer. I will start to work with WOCSS very soon.

Cheers,

Laurent.