libsim Versione 7.2.0

◆ volgrid6d_compute_stat_proc()

subroutine volgrid6d_compute_stat_proc ( type(volgrid6d), intent(inout)  this,
type(volgrid6d), intent(out)  that,
integer, intent(in)  stat_proc_input,
integer, intent(in)  stat_proc,
type(timedelta), intent(in)  step,
type(datetime), intent(in), optional  start,
logical, intent(in), optional  full_steps,
real, intent(in), optional  frac_valid,
type(timedelta), intent(in), optional  max_step,
logical, intent(in), optional  weighted,
logical, intent(in), optional  clone 
)

General-purpose method for computing a statistical processing on data in a volgrid6d object already processed with the same statistical processing, on a different time interval specified by step and start.

This method tries to apply all the suitable specialized statistical processing methods according to the input and output statistical processing requested. The argument stat_proc_input determines which data will be processed, while the stat_proc argument determines the type of statistical process to be applied and which will be owned by output data.

The possible combinations are:

  • stat_proc_input = 254

    • stat_proc = 0 average instantaneous observations
    • stat_proc = 2 compute maximum of instantaneous observations
    • stat_proc = 3 compute minimum of instantaneous observations
    • stat_proc = 4 compute difference of instantaneous observations

    processing is computed on longer time intervals by aggregation, see the description of volgrid6d_compute_stat_proc_agg()

  • stat_proc_input = *

    • stat_proc = 254 consider statistically processed values as instantaneous without any extra processing

    see the description of volgrid6d_decompute_stat_proc()

  • stat_proc_input = 0, 1, 2, 3, 4, 200

    • stat_proc = stat_proc_input recompute input data on different intervals

    the same statistical processing is applied to obtain data processed on a different interval, either longer, by aggregation, or shorter, by differences, see the description of volgrid6d_recompute_stat_proc_agg() and volgrid6d_recompute_stat_proc_diff() respectively; it is also possible to provide stat_proc_input /= stat_proc, but it has to be used with care.

  • stat_proc_input = 0

    • stat_proc = 1

    a time-averaged rate or flux is transformed into a time-integrated value (sometimes called accumulated) on the same interval by multiplying the values by the length of the time interval in seconds, keeping constant all the rest, including the variable; the unit of the variable implicitly changes accordingly, this is supported officially in grib2 standard, in the other cases it is a forcing of the standards.

  • stat_proc_input = 1

    • stat_proc = 0

    a time-integrated value (sometimes called accumulated) is transformed into a time-averaged rate or flux on the same interval by dividing the values by the length of the time interval in seconds, see also the previous description of the opposite computation.

If a particular statistical processing cannot be performed on the input data, the program continues with a warning and, if requested, the input data is passed over to the volume specified by the other argument, in order to allow continuation of processing. All the other parameters are passed over to the specifical statistical processing methods and are documented there.

Parametri
[in,out]thisvolume providing data to be recomputed, it is not modified by the method, apart from performing a volgrid6d_alloc_vol on it
[out]thatoutput volume which will contain the recomputed data
[in]stat_proc_inputtype of statistical processing of data that has to be processed (from grib2 table), only data having timerange of this type will be processed, the actual statistical processing performed and which will appear in the output volume, is however determined by stat_proc argument
[in]stat_proctype of statistical processing to be recomputed (from grib2 table), data in output volume that will have a timerange of this type
[in]steplength of the step over which the statistical processing is performed
[in]startstart of statistical processing interval
[in]full_stepsif .TRUE. apply processing only on intervals starting at a forecast time or a reference time modulo step
[in]frac_validminimum fraction of valid data required for considering acceptable a recomputed value, default=1.
[in]weightedif provided and .TRUE., the statistical process is computed, if possible, by weighting every value with a weight proportional to its validity interval
[in]cloneif provided and .TRUE. , clone the gaid's from this to that

Definizione alla linea 290 del file volgrid6d_class_compute.F90.

292 CALL volgrid_get_vol_2d(that, i3, i, j, i6, voldatiout)
293 ndtr = 0
294 DO n = 1, map_ttr(i,j)%arraysize
295 IF (map_ttr(i,j)%array(n)%extra_info == dtratio(n1)) THEN
296 ndtr = ndtr + 1
297 CALL volgrid_get_vol_2d(this, i3, map_ttr(i,j)%array(n)%it, &
298 map_ttr(i,j)%array(n)%itr, i6, voldatiin)
299
300 IF (ndtr == 1) THEN
301 voldatiout = voldatiin
302 IF (lclone) THEN
303 CALL copy(this%gaid(i3, map_ttr(i,j)%array(n)%it,&
304 map_ttr(i,j)%array(n)%itr,i6), that%gaid(i3,i,j,i6))
305 ELSE
306 that%gaid(i3,i,j,i6) = this%gaid(i3, map_ttr(i,j)%array(n)%it, &
307 map_ttr(i,j)%array(n)%itr,i6)
308 ENDIF
309
310 ELSE ! second or more time
311 SELECT CASE(stat_proc)
312 CASE (0, 200, 1, 4) ! average, vectorial mean, accumulation, difference
313 WHERE(c_e(voldatiin(:,:)) .AND. c_e(voldatiout(:,:)))
314 voldatiout(:,:) = voldatiout(:,:) + voldatiin(:,:)
315 ELSEWHERE
316 voldatiout(:,:) = rmiss
317 END WHERE
318 CASE(2) ! maximum
319 WHERE(c_e(voldatiin(:,:)) .AND. c_e(voldatiout(:,:)))
320 voldatiout(:,:) = max(voldatiout(:,:), voldatiin(:,:))
321 ELSEWHERE
322 voldatiout(:,:) = rmiss
323 END WHERE
324 CASE(3) ! minimum
325 WHERE(c_e(voldatiin(:,:)) .AND. c_e(voldatiout(:,:)))
326 voldatiout(:,:) = min(voldatiout(:,:), voldatiin(:,:))
327 ELSEWHERE
328 voldatiout(:,:) = rmiss
329 END WHERE
330 END SELECT
331
332 ENDIF ! first time
333 ENDIF ! dtratio(n1)
334 ENDDO ! ttr
335
336#ifdef DEBUG
337 CALL l4f_log(l4f_debug, &
338 'compute_stat_proc_agg, ndtr/dtratio/frac_valid: '// &
339 t2c(ndtr)//'/'//t2c(dtratio(n1))//'/'//t2c(lfrac_valid))
340#endif
341 IF (ndtr > 0) THEN ! why this condition was not here before?
342 IF (real(ndtr)/real(dtratio(n1)) >= lfrac_valid) THEN ! success
343 IF (stat_proc == 0) THEN ! average
344 WHERE(c_e(voldatiout(:,:)))
345 voldatiout(:,:) = voldatiout(:,:)/ndtr
346 END WHERE
347 ENDIF
348 CALL volgrid_set_vol_2d(that, i3, i, j, i6, voldatiout)
349#ifdef DEBUG
350 CALL l4f_log(l4f_debug, &
351 'compute_stat_proc_agg, coding lev/t/tr/var: '// &
352 t2c(i3)//'/'//t2c(i)//'/'//t2c(j)//'/'//t2c(i6))
353#endif
354 ELSE
355! must nullify the output gaid here, otherwise an incomplete field will be output
356 IF (lclone) THEN
357 CALL delete(that%gaid(i3,i,j,i6))
358 ELSE
359 CALL init(that%gaid(i3,i,j,i6)) ! grid_id lacks a nullify method
360 ENDIF
361#ifdef DEBUG
362 CALL l4f_log(l4f_debug, &
363 'compute_stat_proc_agg, skipping lev/t/tr/var: '// &
364 t2c(i3)//'/'//t2c(i)//'/'//t2c(j)//'/'//t2c(i6))
365#endif
366 ENDIF
367 ENDIF ! ndtr > 0
368
369 ENDDO ! level
370 ENDDO ! var
371 ENDDO ! dtratio
372 CALL delete(map_ttr(i,j))
373 ENDDO do_otime

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