<div dir="ltr"><div><div><div><div>The "power" at the lowest frequencies is because:<br><br></div>[a] you have not removed the mean annual cycle<br></div><div> and/or<br></div>[b] you not removed linear trend.<br><br></div>Both contribute to "power" at low frequencies.<br><br></div><div>Removing the influence of known signals that may obscure the signals is called "prewhitening". Please look this up.<br><br></div><div>I speculate [a] is the primary reason.<br></div><div><br><a href="http://www.ncl.ucar.edu/Applications/climo.shtml">http://www.ncl.ucar.edu/Applications/climo.shtml</a><br><a href="http://www.ncl.ucar.edu/Applications/Scripts/climo_5.ncl">http://www.ncl.ucar.edu/Applications/Scripts/climo_5.ncl</a><br><br><a href="http://www.ncl.ucar.edu/Applications/mjoclivar.shtml">http://www.ncl.ucar.edu/Applications/mjoclivar.shtml</a><br><a href="http://www.ncl.ucar.edu/Applications/mjoclivar.shtml#ex2">http://www.ncl.ucar.edu/Applications/mjoclivar.shtml#ex2</a><br></div><div><br>Please read:<br><a href="http://www.ncl.ucar.edu/Document/Functions/Contributed/calcDayAnomTLL.shtml">http://www.ncl.ucar.edu/Document/Functions/Contributed/calcDayAnomTLL.shtml</a><br><br></div><div>Good Luck<br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Jan 12, 2017 at 7:59 PM, Lyndon Mark Olaguera <span dir="ltr"><<a href="mailto:olagueralyndonmark429@gmail.com" target="_blank">olagueralyndonmark429@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Dear Sir Dennis,<div><br></div><div>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.</div><div><br></div><div>Any suggestion on how can I fix this?</div><div><br></div><div><br></div><div>Here is the link to the data that I am using.</div><div><br></div><div><a href="https://drive.google.com/drive/folders/0B9faET7Bc2o8R0ZsZXM1bkxUWlE?usp=sharing" target="_blank">https://drive.google.com/drive<wbr>/folders/0B9faET7Bc2o8R0ZsZXM1<wbr>bkxUWlE?usp=sharing</a><br></div><div><br></div><div><br></div><div>Many thanks,</div><div><br></div><div>Lyndon</div><div><div class="h5"><div class="gmail_extra"><div><div class="m_-4266364096742564518gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><br></div></div></div></div></div></div></div></div></div>
<br><div class="gmail_quote">On Mon, Jan 9, 2017 at 11:14 AM, Lyndon Mark Olaguera <span dir="ltr"><<a href="mailto:olagueralyndonmark429@gmail.com" target="_blank">olagueralyndonmark429@gmail.<wbr>com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hi Sir Dennis,<div><br></div><div>Thanks for the help. I was looking for peaks with periods of 30 to 60 days. </div><div>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.</div><div><div class="m_-4266364096742564518h5"><div><br></div><div><div class="gmail_extra"><div><div class="m_-4266364096742564518m_-3760562482669382915gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><br></div></div></div></div></div></div></div></div></div></div>
<br><div class="gmail_quote">On Sat, Jan 7, 2017 at 1:42 AM, Dennis Shea <span dir="ltr"><<a href="mailto:shea@ucar.edu" target="_blank">shea@ucar.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div><div>[1]<br></div>As noted in the documentation:<br> "The units are variance/(unit frequency interval)."<br></div> **not** <br> "variance"<br><br>[2]<br></div>Look at the data ... literally<br> plot = gsn_csm_y(wks,rain,False) <wbr> ; see attachment<br><br></div>Basically, the annual cycle of rain. <br><br></div>What is it you expect from a time series like this? The lag-1 day auto correlation is 0.96. A ***very red** process. <br><br></div>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.<br><br><br></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="m_-4266364096742564518m_-3760562482669382915h5">On Fri, Jan 6, 2017 at 1:57 AM, Lyndon Mark Olaguera <span dir="ltr"><<a href="mailto:olagueralyndonmark429@gmail.com" target="_blank">olagueralyndonmark429@gmail.c<wbr>om</a>></span> wrote:<br></div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="m_-4266364096742564518m_-3760562482669382915h5"><div dir="ltr">Hi All,<div><br></div><div>I'm trying to perform spectral analysis using the specx_anal function in ncl.</div><div>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.</div><div><br></div><div><br></div><div>Attached are the data set and script.</div><div><br></div><div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_code.ncl"</div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/gsn_csm.ncl"</div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/contributed.ncl"</div><div>load "$NCARG_ROOT/lib/ncarg/nclscri<wbr>pts/csm/shea_util.ncl"</div><div><br></div><div>begin</div><div>filename = "type1_clim.csv"</div><div>lines = asciiread(filename,-1,"string"<wbr>)</div><div>data = lines(1:)</div><div>rain = tofloat(str_get_field(data,10,<wbr>","))</div><div><br></div><div>d = 1</div><div>sm = 12</div><div>pct = 0.10</div><div><br></div><div>spec= specx_anal(rain,d,sm,pct)</div><div>printVarSummary(spec)</div><div><br></div><div>wks = gsn_open_wks("png","test_fldme<wbr>an") ; Opens a ps file</div><div>res = True </div><div>res@tiMainString = "Type1_Spectrum" ; title</div><div>f = spec@frq</div><div>res@tiXAxisString = "Frequency (cycles/day)" ; xaxis</div><div>res@tiYAxisString = "Variance" ; yaxis</div><div><br></div><div>splt = specx_ci(spec, 0.05, 0.95)</div><div><br></div><div>res@xyLineColors = (/"foreground","green","blue",<wbr>"red"/)</div><div>plot = gsn_csm_xy(wks,f,splt,res) ; create plot</div><div>end</div></div><div><br></div><div>I'll appreciate any help.</div><div><br></div><div>Many thanks,</div><div><br></div><div>Lyndz</div><div><br></div></div>
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