[ncl-talk] Question about Spectral Analysis(computation of variance)

[Lyndon Mark Olaguera]

Dear Sir Dennis,

Many thanks for the reply. I really thought that the iopt in the
specx_anal() function would remove the mean annual cycle (should be in
terms of anomalies!).
I misunderstood this. :-(

I followed your suggestions above and rerun the script (detrend and use
anomalies). The new output is attached in this email.

The variance/freq is still very large (~600).



Many thanks for the help.

*Lyndon Mark P. Olaguera*


On Mon, Jan 16, 2017 at 7:55 AM, Dennis Shea <shea at ucar.edu> wrote:

> The "power" at the lowest frequencies is because:
>
> [a] you have not removed the mean annual cycle
>      and/or
> [b] you not removed linear trend.
>
> Both contribute to "power" at low frequencies.
>
> Removing the influence of known signals that may obscure the signals is
> called "prewhitening". Please look this up.
>
> I speculate [a] is the primary reason.
>
> http://www.ncl.ucar.edu/Applications/climo.shtml
> http://www.ncl.ucar.edu/Applications/Scripts/climo_5.ncl
>
> http://www.ncl.ucar.edu/Applications/mjoclivar.shtml
> http://www.ncl.ucar.edu/Applications/mjoclivar.shtml#ex2
>
> Please read:
> http://www.ncl.ucar.edu/Document/Functions/Contributed/calcDayAnomTLL.
> shtml
>
> Good Luck
>
> On Thu, Jan 12, 2017 at 7:59 PM, Lyndon Mark Olaguera <
> olagueralyndonmark429 at gmail.com> wrote:
>
>> Dear Sir Dennis,
>>
>> I tried to perform the spectral analysis in different regions using a
>> different data set from my previous post. For example, Western Africa and
>> South China Sea but I still get the same spike in variance near the 0 mark.
>> I am using gpcp daily data. Attached are the images and my script.
>>
>> Any suggestion on how can I fix this?
>>
>>
>> Here is the link to the data that I am using.
>>
>> https://drive.google.com/drive/folders/0B9faET7Bc2o8R0ZsZXM1
>> bkxUWlE?usp=sharing
>>
>>
>> Many thanks,
>>
>> Lyndon
>>
>>
>> On Mon, Jan 9, 2017 at 11:14 AM, Lyndon Mark Olaguera <
>> olagueralyndonmark429 at gmail.com> wrote:
>>
>>> Hi Sir Dennis,
>>>
>>> Thanks for the help. I was looking for peaks with periods of 30 to 60
>>> days.
>>> The data is not good for this analysis. I also tried in the raw daily
>>> values (attached in this email) but there is still a very large
>>> variance/frequency.
>>>
>>>
>>>
>>> On Sat, Jan 7, 2017 at 1:42 AM, Dennis Shea <shea at ucar.edu> wrote:
>>>
>>>> [1]
>>>> As noted in the documentation:
>>>>    "The units are variance/(unit frequency interval)."
>>>>     **not**
>>>>    "variance"
>>>>
>>>> [2]
>>>> Look at the data ... literally
>>>>    plot = gsn_csm_y(wks,rain,False)                      ; see
>>>> attachment
>>>>
>>>> Basically, the annual cycle of rain.
>>>>
>>>> What is it you expect from a time series like this? The lag-1 day auto
>>>> correlation is 0.96. A ***very red** process.
>>>>
>>>> Assuming this is a climatology, I did a [four)info] on the data, The
>>>> 1st harmonic has amplitude 7.3 with the phase max at day 220 and it
>>>> explains 82% of the variance. The 2nd harmonic has amplitude 2.3; phase day
>>>> 32; 8% of the variance.
>>>>
>>>>
>>>>
>>>> On Fri, Jan 6, 2017 at 1:57 AM, Lyndon Mark Olaguera <
>>>> olagueralyndonmark429 at gmail.com> wrote:
>>>>
>>>>> Hi All,
>>>>>
>>>>> I'm trying to perform spectral analysis using the specx_anal function
>>>>> in ncl.
>>>>> I'm getting a variance around 1000 near the zero mark.I dont know if
>>>>> I'm missing a step prior to performing the spectral analysis. I would like
>>>>> to ask for any suggestions on how can I improve this.
>>>>>
>>>>>
>>>>> Attached are the data set and script.
>>>>>
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/shea_util.ncl"
>>>>>
>>>>> begin
>>>>> filename = "type1_clim.csv"
>>>>> lines    = asciiread(filename,-1,"string")
>>>>> data     = lines(1:)
>>>>> rain    = tofloat(str_get_field(data,10,","))
>>>>>
>>>>> d = 1
>>>>> sm = 12
>>>>> pct = 0.10
>>>>>
>>>>> spec= specx_anal(rain,d,sm,pct)
>>>>> printVarSummary(spec)
>>>>>
>>>>> wks  = gsn_open_wks("png","test_fldmean")             ; Opens a ps
>>>>> file
>>>>> res = True
>>>>> res at tiMainString = "Type1_Spectrum"                     ; title
>>>>> f = spec at frq
>>>>> res at tiXAxisString = "Frequency (cycles/day)"  ; xaxis
>>>>> res at tiYAxisString = "Variance"                       ; yaxis
>>>>>
>>>>> splt = specx_ci(spec, 0.05, 0.95)
>>>>>
>>>>> res at xyLineColors        = (/"foreground","green","blue","red"/)
>>>>> plot = gsn_csm_xy(wks,f,splt,res)     ; create plot
>>>>> end
>>>>>
>>>>> I'll appreciate any help.
>>>>>
>>>>> Many thanks,
>>>>>
>>>>> Lyndz
>>>>>
>>>>>
>>>>> _______________________________________________
>>>>> ncl-talk mailing list
>>>>> ncl-talk at ucar.edu
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>>>>>
>>>>>
>>>>
>>>
>>
>
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