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ncl脚本运行遇到一些问题，终端提示如下
不知哪位大神可以提示一下原因以及解决办法。
脚本如下（ps：该脚本为pop程序的脚本，如有做过pop的可否帮忙看看程序，谢谢！）
; ==============================================================
; POPanalysis: Calculate POPs
; This is a user donated script.
; *It is NOT supported software.
; ==============================================================
; Calculate POPs from SST data
; ==============================================================
load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
load "/home/gyy/pop/PrnOscPat_driver.ncl" ; creates the POPs from EOFs
load "/home/gyy/pop/pltEofPop.ncl" ; plot EOF/POP
load "/home/gyy/pop/pltClim.ncl" ; plot climatology
; ==============================================================
; MAIN
; ==============================================================
wcStrt = systemfunc("date")
netCDF = True ; create nc for POP
dirNC = "/home/gyy/pop/" ; dir for output nc
pltDir = "/home/gyy/pop/" ; dir for plots
pltEOF = True
pltPOP = True
pltCLIM = True
pltType = "ps"
pltName = "POP"
; ==============================================================
; User defined parameters that specify region of globe and time period
; ==============================================================
latS = 29.75 ; spatial domain
latN = 29.75
lonL = 30.25
lonR = 119.75
kPOP = 1 ; decide which POP we want to look at
POPphase = (/"precursor","peak"/) ; (/ 0, 1/)
yrStrt = 1958
yrLast = 2008
neof = 10 ; number of EOFs
nPOP = 2 ; number of POPs
optEOF = True
optETS = False
REDUCE = False ; reduce spatial density
nskip = 2 ; only when REDUCE=True
mskip = 2
; ==============================================================
; Open the file
; ==============================================================
patho = "/home/gyy/pop/" ; path for output
pathi = "/home/gyy/pop/" ; path to source
ifile = "SODA_SST.nc"
varname= "temp" ; variable name
f = addfile (pathi+ifile, "r") ; entire file
; ==============================================================
; Read only the user specified period and region
; ==============================================================
TIME = f->time ; ALL time on file
YYYY = cd_calendar(TIME,-1)/100 ; ALL years
iYYYY = ind(YYYY.ge.yrStrt .and. YYYY.le.yrLast) ; indices of year subset
nTIME = dimsizes(iYYYY)
; read full year subset
if (getfilevartypes(f, varname).eq."short") then ; clarity
DATA = short2flt(f->$varname$(iYYYY,:,:,:))
else
DATA = f->$varname$(iYYYY,:,:,:)
end if
printVarSummary(DATA) ; variable overview
; ==============================================================
; If dataset longitudes are -180=>180, flip to (nominally) span 0=>360
; Only if both'lonL' and 'lonR' are positive.
; ==============================================================
if (lonL.ge.0 .and. lonR.gt.0 .and. DATA&lon(0).lt.0) then
DATA = lonFlip(DATA) ; flip longitudes
;printVarSummary(DATA)
end if
; ==============================================================
; Subset to the time period (full years) and region of interest
; Optionally: reduce the grid point density for less memory.
; ==============================================================
if (REDUCE) then
data = DATA(:,::nskip,{lonL:lonR:mskip})
else
data = DATA(:,:,{lonL:lonR})
end if
delete(DATA) ; reduce memory
printVarSummary(data) ; data to be used
; ==============================================================
; Remove annual cycle from the data: create anomalies
; . use only full years to find annual cycle
; ==============================================================
clim = clmMonTLL(data) ; calculcate climatology
;printVarSummary(clim)
data = calcMonAnomTLL(data, clim) ; remove annual cycle
;printVarSummary(data) ; variable overview
ntim = dimsizes(data&time)
; =================================================================
; remove linear trend in time: data(time,lat,lon): time is dimension # 0)
; =================================================================
data = dtrend_n(data, False, 0)
; =================================================================
; normalize data at each gridpoint by local standard deviation at each grid pt
; =================================================================
data = dim_standardize_n(data,1,0)
; =================================================================
; low pass (lp) filter
; remove short time scale variance (everything shorter than 18 months)
; =================================================================
ihp = 0 ; lowpass filter
sigma = 1
nWgt = 37 ; loose 18 months each end
fca = 1./18. ; 18 months
wgt = filwgts_lanczos(nWgt,ihp,fca,data@_FillValue,sigma)
datalp= wgt_runave_n_Wrap(data,wgt,0,0) ; running average (time)
datalp@long_name = "Low Pass: "+data@long_name
printVarSummary(datalp) ; (time,lat,lon)
; =================================================================
; Reorder (lat,lon,time) the input data so time is rightmost dimension.
; This is the order expected by the 'eofunc'
; =================================================================
xlp = datalp(lat|:,lon|:,time|:)
delete(datalp) ; no longer needed
; =================================================================
; find EOFs: no weighting is performed here due to limited lat range
; =================================================================
eof = eofunc_Wrap(xlp, neof, optEOF) ; find first neof EOFs
eof_ts = eofunc_ts_Wrap (xlp, eof, optETS) ; time series
printVarSummary( eof ) ; examine EOF variables
printVarSummary( eof_ts )
; +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
; A driver for the POP matrix operations.
; +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
pop_results = PrnOscPat_driver(eof, eof_ts, kPOP) ; returns a list
print(pop_results) ; containing variables
; =================================================================
; For convenience & clarity extract each of the two elements
; and place them into separate variables reather than acces
; via 'list' syntax.
; =================================================================
pop_ts = pop_results[0] ; POP time series (nEOF,time)
printVarSummary(pop_ts)
;print("pop_ts: min="+min(pop_ts)+" max="+max(pop_ts))
pop_pat = pop_results[1] ; POP patterns (nEOF,lat,lon)
printVarSummary(pop_pat)
;print("pop_pat: min="+min(pop_pat)+" max="+max(pop_pat))
delete(pop_results) ; no longer needed
; ===========================================================
; Miscellaneous for file creation and plots
; ===========================================================
sfx = get_file_suffix(ifile, 0)
froot = sfx@fBase
yyyymm = cd_calendar(eof_ts&time,-2)/100
yrfrac = yyyymm_to_yyyyfrac(yyyymm, 0.0)
yyyymm!0 = "time"
yrfrac!0 = "time"
yyyymm&time = eof_ts&time
yrfrac&time = eof_ts&time
if (netCDF) then
; ===========================================================
; NETCDF: write POP data to file: Use simple method of writing netCDF
; ===========================================================
pathNC = dirNC+"POP_"+froot+".nc"
system("/bin/rm -f " + pathNC) ; remove file if exists
fout = addfile(pathNC,"c")
setfileoption(fout,"DefineMode",True)
; create global attributes
fileAtt = True
fileAtt@creation_date = systemfunc("date")
fileattdef(fout,fileAtt)
fout->yyyymm = yyyymm
fout->yrfrac = yrfrac
fout->POP_TS = pop_ts
fout->POP_PATTERN = pop_pat
fout->EOF_TS = eof_ts
fout->EOF = eof
end if
;============================================================
; PLOTS
;============================================================
if (pltEOF) then
pltEofPop(eof_ts, eof, yrfrac, froot, pltType, "EOF", "BlueYellowRed")
end if ; pltEOF
if (pltPOP) then
pltEofPop(pop_ts, pop_pat, yrfrac, froot, pltType, "POP", "BlueYellowRed")
end if ; pltPOP
if (pltCLIM) then
pltClim(clim, froot, pltType, "CLIM", "BlAqGrYeOrReVi200")
end if ; pltCLIM
wallClockElapseTime(wcStrt, "POPanalysis", 0)
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