This module computes statistical values over timesteps of the same day. Depending on the chosen operator the minimum, maximum, range, sum, average, variance or standard deviation of timesteps of the same day is written to outfile. The time of outfile is determined by the time in the middle of all contributing timesteps of infile. This can be change with the CDO option –timestat_date <first|middle|last>.
Usage
cdo_dayavg(ifile, complete_only = NULL, ofile = NULL)
cdo_daymax(ifile, complete_only = NULL, ofile = NULL)
cdo_daymean(ifile, complete_only = NULL, ofile = NULL)
cdo_daymin(ifile, complete_only = NULL, ofile = NULL)
cdo_dayrange(ifile, complete_only = NULL, ofile = NULL)
cdo_daystd(ifile, complete_only = NULL, ofile = NULL)
cdo_daystd1(ifile, complete_only = NULL, ofile = NULL)
cdo_daysum(ifile, complete_only = NULL, ofile = NULL)
cdo_dayvar(ifile, complete_only = NULL, ofile = NULL)
cdo_dayvar1(ifile, complete_only = NULL, ofile = NULL)Value
Operators that output one or more files return a character vector to the output files.
Operators that output an indefinite number of files return a string with the basename of the files.
Operatos that don't return filenames return a character vector with the string output.
Details
daymin Daily minimum
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = min\{i(t',x), t_1<t'<=t_n\}
daymax Daily maximum
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = max\{i(t',x), t_1<t'<=t_n\}
dayrange Daily range
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = range\{i(t',x), t_1<t'<=t_n\}
daysum Daily sum
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = sum\{i(t',x), t_1<t'<=t_n\}
daymean Daily mean
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = mean\{i(t',x), t_1<t'<=t_n\}
dayavg Daily average
For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = avg\{i(t',x), t_1<t'<=t_n\}
daystd Daily standard deviation
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = std\{i(t',x), t_1<t'<=t_n\}
daystd1 Daily standard deviation (n-1)
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = std1\{i(t',x), t_1<t'<=t_n\}
dayvar Daily variance
Normalize by n. For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = var\{i(t',x), t_1<t'<=t_n\}
dayvar1 Daily variance (n-1)
Normalize by (n-1). For every adjacent sequence t_1, ...,t_n of timesteps of the same day it is:
o(t,x) = var1\{i(t',x), t_1<t'<=t_n\}