[ncl-talk] sub: Time selection

[Will Hobbs]

Since nobody else has bitten;

There are several approaches to the problem of getting non-standard seasonal averages; my personal experience is that the most universally-convenient way (if not necessarily the most computationally-efficient) is to reshape the array from a (time, location) format to (year,<month or day>,locn..), where obviously the <month or day> depends on whether you’re using monthly or daily data. You can then simply average across the 2nd dimension for the time indices that you want.

I’ve attached a function that will do this for monthly data, - if you have daily data you’ll need to edit it. NB this is not an official NCL function, and I take no responsibility if it breaks your machine, your data, or your career 😊

Will

From: ncl-talk <ncl-talk-bounces at mailman.ucar.edu> on behalf of dale zuri via ncl-talk <ncl-talk at mailman.ucar.edu>
Reply to: dale zuri <dalezuri at gmail.com>
Date: Saturday, 27 March 2021 at 1:46 pm
To: Ncl-talk <ncl-talk at ucar.edu>
Subject: [ncl-talk] sub: Time selection

Hi NCL users,
How to choose JJAS to compute the seasonal average from 1981-2005. ?
I would appreciate any help.

Thanks
DZ

names = getfilevarnames(f)
print(names)
x   = f->ice
time   = f->T
printVarSummary(x)
utc_date = cd_calendar(time, -2)
print(utc_date)
Number of Dimensions: 4
Dimensions and sizes:   [T | 14086] x [zlev | 1] x [lat | 720] x [lon | 1440]
Coordinates:
            T: [1358..15443]
            zlev: [ 0.. 0]
            lat: [-89.875..89.875]
            lon: [0.125..359.875]
Number Of Attributes: 8
  pointwidth :   1
  valid_max :   100
  scale_factor :        0.01
  missing_value :       -999
  units :       percentage
  valid_min :   0
  long_name :   Sea ice concentration
  standard_name :       sea_ice_area_fraction


Variable: utc_date
Type: integer
Total Size: 56344 bytes
            14086 values
Number of Dimensions: 1
Dimensions and sizes:   [14086]
Coordinates:
Number Of Attributes: 1
  calendar :    standard
(0)     19810920
(1)     19810921
(2)     19810922
(3)     19810923
(14085) 20200413



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