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subroutine vol7d_recompute_stat_proc_agg |
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type(vol7d), intent(inout) |
this, |
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type(vol7d), intent(out) |
that, |
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integer, intent(in) |
stat_proc, |
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type(timedelta), intent(in) |
step, |
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type(datetime), intent(in), optional |
start, |
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logical, intent(in), optional |
full_steps, |
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real, intent(in), optional |
frac_valid, |
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type(vol7d), intent(inout), optional |
other, |
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integer, intent(in), optional |
stat_proc_input |
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) |
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Specialized method for statistically processing a set of data already processed with the same statistical processing, on a different time interval.
This method performs statistical processing by aggregation of shorter intervals. Only floating point single or double precision data are processed.
The output that vol7d object contains elements from the original volume this satisfying the conditions
- real single or double precision variables
- timerange (vol7d_timerange_class::vol7d_timerange::timerange) of type stat_proc (or stat_proc_input if provided)
- any p1 (analysis/observation or forecast)
- p2 > 0 (processing interval non null, non instantaneous data) and equal to a multiplier of step
Output data will have timerange of type stat_proc and p2 = step. The supported statistical processing methods (parameter stat_proc) are:
- 0 average
- 1 accumulation
- 2 maximum
- 3 minimum
- 4 difference
- 6 standard deviation
- 200 vectorial mean
The start of processing period can be computed automatically from the input intervals as the first possible interval modulo step, or, for a better control, it can be specified explicitly by the optional argument start. Notice that start indicates the beginning of the processing interval, so in the final volume, the first datum may have time equal to start + step, e.g. in the case when time is the verification time, which is typical for observed datasets.
The purpose of the optional argument stat_proc_input is to allow processing with a certain statistical processing operator a dataset already processed with a different operator, by specifying the latter as stat_proc_input; this is useful, for example, if one wants to compute the monthly average of daily maximum temperatures; however this has to be used with care since the resulting data volume will not carry all the information about the processing which has been done, in the previous case, for example, the temperatures will simply look like monthly average temperatures.
- Parametri
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[in,out] | this | volume providing data to be recomputed, it is not modified by the method, apart from performing a vol7d_alloc_vol on it |
[out] | that | output volume which will contain the recomputed data |
[in] | stat_proc | type of statistical processing to be recomputed (from grib2 table), only data having timerange of this type will be recomputed and will appear in the output volume |
[in] | step | length of the step over which the statistical processing is performed |
[in] | start | start of statistical processing interval |
[in] | full_steps | if .TRUE. and start is not provided, apply processing only on intervals starting at a forecast time or a reference time modulo step |
[in] | frac_valid | minimum fraction of valid data required for considering acceptable a recomputed value, default=1. |
[in,out] | other | optional volume that, on exit, is going to contain the data that did not contribute to the statistical processing |
[in] | stat_proc_input | to be used with care, type of statistical processing of data that has to be processed (from grib2 table), only data having timerange of this type will be recomputed, the actual statistical processing performed and which will appear in the output volume, is however determined by stat_proc argument |
Definizione alla linea 430 del file vol7d_class_compute.F90.
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