Re: Reorganizing two arrays into one

And this is the only error to the script: "fatal:escorc: The last dimension
of x must be equal to the last dimension of y" reflecting the mentioned
error above.

On Tue, Apr 16, 2013 at 11:34 AM, Skylar Haines <skylar.haines@maine.edu>wrote:

> Thanks Adam!
>
> That worked great. Now I have a new problem involving the ordering of my
> dimensions so that I can run a correlation.
> The script works fine until the command for the correlation,
> "Z=escorc(ZZ1(:,:,:),ZZ2(:,:,:))" What I am trying to do is run a
> correlation between ERA_Interim Seasonal MSLP (time,lat,lon) with ice core
> data(time,concentration). At this point I created a loop to get the
> datasets to have the same amount of data (44 points), so they are
> comparable, but I am not sure if I have organized their respective
> dimensions correctly to run a correlation.
>
> I hope this makes sense, and appreciate all help!
>
> -Skylar
>
> 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
>
> ;;;;;read in ITASE 02-1 NA ice core
> data***************************************************
>
> data1=readAsciiTable("/Users/sky/Desktop/NCL_class/NCL_Final/ITASE-02-1_DJF_JJA_seasonal.txt",2,"float",0)
> printVarSummary(data1)
> ;print(data1)
> yr = data1(0:43,0)
> ts = data1(0:43,1)
> yr@_FillValue= -9999.99
> ts@_FillValue= -9999.99
> ;print(ts)
>
> n_ts=dimsizes(ts)
> n_yr=dimsizes(yr)
> ;data1!0 = "time"
> ;data1!1 = "concentration"
>
> ;;;;;read in Seasonal ERA
> MSLP************************************************************************
>
> infile="/Users/sky/Desktop/NCL_class/NCL_Final/ERA_interim_monthlymean_MSL_Wind_1979_2001.grib"
> f=addfile(infile,"r")
> MSLP=f->MSL_GDS0_SFC_123(:,:,:) ;read in MSL data
> MSLP=MSLP*0.01 ;convert MSL pressure to mb
> ;WS=f->10SI_GDS0_SFC_123 (:,:,:) ;read in wind speed data
> lat=f->g0_lat_1
> lon=f->g0_lon_2
>
> nMSLP=dimsizes(MSLP)
> ;print("nMSLP="+nMSLP)
> nlat=dimsizes(lat)
> nlon=dimsizes(lon)
> ;print("nlat="+nlat)
> time=f->initial_time0_hours ;read in time
> ntime=dimsizes(time)
> ;print("ntime="+ntime)
> ;printVarSummary(time)
>
> ;T_season =month_to_seasonN(time,(/"DJF","JJA"/))
> ;printVarSummary(T_season)
> ;nT_season=dimsizes(T_season)
> ;print("nT_season="+nT_season)
> MSLP_season=month_to_seasonN(MSLP,(/"DJF","JJA"/))
> printVarSummary(MSLP_season)
> nMSLP_season=dimsizes(MSLP_season)
> print("nMSLP_season="+nMSLP_season)
>
>
>
> ws_MSLP= new((/46,nlat,nlon/),"float")
>
>
> ws_MSLP(0::2,:,:) = (/ MSLP_season(0,:,:,:) /) ; assign season 0 to the
> 0th, 2nd, 4th, etc time slots.
> ws_MSLP(1::2,:,:) = (/ MSLP_season(1,:,:,:) /) ; assign season 1 to the
> 1st, 3rd, 5th, etc time slots.
>
>
> printVarSummary(ws_MSLP)
>
>
> Z1=new((/46,nlat,nlon/),"float") ;populate with ERA MSLP data
> do i=0,43
> Z1(i,:,:) = (/ws_MSLP(i,:,:)/)
> end do
>
> Z2=new((/n_ts,nlat,nlon/),"float")
> do i=0,43
> Z2(i,:,:)=(/ts(i)/) ;populate Z2 for all years with timeseries
> end do
>
>
>
> Z1!0="time"
> Z1!1="lat"
> Z1!2="lon"
> Z2!0="time"
> Z2!1="lat"
> Z2!2="lon"
>
>
> ;Reorder dimensions - must save in new grids
> ;-------------------------------------------
> ZZ1=Z1(lat|:,lon|:,time|:) ;REANALYSIS GRIDS
> ZZ2=Z2(lat|:,lon|:,time|:) ;TIMESERIES GRIDS
>
>
> ;Run 0-lag correlation function
> ;------------------------------
> Z=escorc(ZZ1(:,:,:),ZZ2(:,:,:))
>
> print(Z)
>
> ;Z is the 2D correlation map that you will plot
>
> end
>
>
> On Mon, Apr 15, 2013 at 9:01 PM, Adam Phillips <asphilli@ucar.edu> wrote:
>
>> Hi Skylar,
>> I think you can just use index subscripting to do what you want. Try this:
>> MSL_SEASON_new= new((/46,241,480/),"float")
>> (You don't need to have a 4D array with the first dimension as size one.)
>>
>> (assign dimension names and coordinate variables as you were)
>>
>> then:
>> MSL_SEASON_new(0::2,:,:) = (/ MSL_SEASON(0,:,:,:) /) ; assign season 0 to
>> the 0th, 2nd, 4th, etc time slots.
>> MSL_SEASON_new(1::2,:,:) = (/ MSL_SEASON(1,:,:,:) /) ; assign season 1 to
>> the 1st, 3rd, 5th, etc time slots.
>>
>> This is of course untested, so check the new array to make sure that the
>> above coding is doing what you want/expect it to.
>>
>> If the above doesn't help please let ncl-talk know.
>> Adam
>>
>>
>>
>> On 4/15/13 6:50 PM, Skylar Haines wrote:
>>
>> All,
>>
>> I have converted ERA Interim monthly data into seasonal data, DJF and
>> JJA, and get my variable:
>>
>> Variable: MSL_season
>> Type: float
>> Total Size: 21285120 bytes
>> 5321280 values
>> Number of Dimensions: 4
>> Dimensions and sizes: [season | 2] x [initial_time0_hours | 23] x
>> [g0_lat_1 | 241] x [g0_lon_2 | 480]
>> Coordinates:
>> season: [DJF..JJA]
>> initial_time0_hours: [1569072..1761936]
>> g0_lat_1: [90..-90]
>> g0_lon_2: [ 0..359.25]
>> Number Of Attributes: 10
>> center : European Center for Medium-Range Weather Forecasts (RSMC)
>> long_name : Seasonal Means: Mean sea level pressure
>> units : Pa
>> _FillValue : 1e+20
>> level_indicator : 1
>> gds_grid_type : 0
>> parameter_table_version : 128
>> parameter_number : 151
>> forecast_time : 0
>> forecast_time_units : hours
>> (0) nMSL_season=2
>> (1) nMSL_season=23
>> (2) nMSL_season=241
>> (3) nMSL_season=480
>>
>>
>> I would like to be able to have this data in a single array such that
>> the seasons, DJF and JJA, are in relative order (i.e. DJF 1979, JJA 1979,
>> DJF 1979-1980, JJA 1980, etc.):
>>
>> MSL_SEASON= new((/1,46,241,480/),"float")
>>
>> MSL_SEASON!0="season"
>> MSL_SEASON!1="time"
>> MSL_SEASON!2="lat"
>> MSL_SEASON!3="lon"
>>
>>
>> MSL_SEASON&season = season
>> MSL_SEASON&time = time
>> MSL_SEASON&lat = lat
>> MSL_SEASON&lon = lon
>>
>>
>> Seems to me like a simple task, but I have been struggling with it for
>> a while now. I'm not sure whether a loop may be involved. I am not sure of
>> the correct syntax regarding coordinate subscripting, either.
>>
>> Any help would greatly be appreciated.
>>
>> -Skylar
>>
>>
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>

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Received on Tue Apr 16 09:36:29 2013