[ncl-talk] Lanczos Filtering

[Kiswendsida Hyacinthe GUIGMA]

Thank you dear Dennis for your help. I am sorry if my questions look too basic. I already read the filtering examples. 
The fact is that using their method (you can see my code in my previous post), from daily rainfall data I got negative values after filtering, what is abnormal.   
-----------------------------
GUIGMA 

    On Tuesday, 5 December 2017, 19:03, Dennis Shea <shea at ucar.edu> wrote:
 

 Please look at the filtering examples:
   https://www.ncl.ucar.edu/Applications/filter.shtml

   In particular, run Example 8

[1] yes, of course ... more weights can create a sharper cutoff but there is a larger loass od data at the beginning and end.

[2] re: practical criterion .... That is up to you as a scientist.

--
Note ncl-talk is not the place to learn about filtering.

Good luck



On Tue, Dec 5, 2017 at 9:14 AM, Kiswendsida Hyacinthe GUIGMA <karongseba at gmail.com> wrote:

Dear NCL users,I am very new on NCL and I am trying to filter my rainfall data using Lanczos Filter (bandpass 10-90 day filtering). My question concerns the processing of the weights. I would like to know 
1-is there any relationship between the number of weights to choose and the cutoff frequencies?2-is there any practical criterion to choose the number of weights? I know that this number influences the loss of data.Below is my code:
------------------------------ ------------------------------ ------------------------------ ------------------------------ ------------------------------ ----------------;import the file
gpcp=addfile("gpcp_Sahel.nc"," r")
rr=gpcp->precip
;filter parameters
ihp=2 ;bandpass
sigma=1.0 ; Lanczos sigma
nWgt    = 81  ; number of weights -> means 40 data lost at the beginning and 40 data lost at the end.                      
fca     = 1./90.            ; start freq ;highpass= 90 days
fcb     = 1./10.                        ; last  freq; lowpass= 10 days
wgt     = filwgts_lanczos (nWgt, ihp, fca, fcb, sigma )
printVarSummary(wgt)
xBPF    = wgt_runave_n_Wrap ( rr, wgt, 0, 0)      ; 10-90 day bp performed across time dimension(0) of rr (meaning the time dimension)
 ----------------------------- ------------------------------ ------------------------------ ------------------------------ ------------------------------ ----------------




Cheers,

GUIGMA
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