* Sören Gebbert <soerengebb...@googlemail.com> [2015-05-18 13:08:08 +0200]:

> Hi Nikos,
> sorry for the late response.
> 
> The aggregation of daily relative time STRDS with Gregorian monthly
> granularity is not possible, since in relative time mode, there is no
> connection between daily and monthly calendar hierarchy. The reason is
> that in relative time mode there is no starting point in calendar time
> at which day 1,2 or n starts. Hence you never know to which month or
> year a day is associated, because of the lack of a calendar hierarchy.

Right.

> The number of days per month and per year are different in the
> Gregorian calendar, hence the output of r.sun.daily should be in my
> humble opinion yearly and monthly specific.

The differences are so subtle (for example for Linke Turbdity) that
maybe it doesn't make sense to have different data sets for different
years. See also, for example the monthly sums of global irradiation on a
horizontal surface (kWh/m2) period 1998-2011 from
<http://re.jrc.ec.europa.eu/pvgis/download/data/hor_rad_PVGIS_cmsaf_monthly_latlon.zip>.

They are just 12 maps. To get the average values, one needs to divide
with... ? 30 for all months?

Having absolute timestamps would make life easier with the
fantastic temporal framework. I'll re-do again my workflow and decide
upon a year. After all, I did extract the following for a specific year
(don't remember which one it was now :-?):

January|1|31|01
February|32|59|02
March|60|90|03
April|91|120|04
May|121|151|05
June|152|181|06
July|182|212|07
August|213|243|08
September|244|273|09
October|274|304|10
November|305|334|11
December|335|365|12

> However, you can create a second STDS with relative time, that
> contains of 12 maps with the according time intervals (31 days, 28/29
> days, ...) and use t.rast.aggregate.ds to aggregate the first STRDS
> based on the time intervals of the second STDS.

That's cool!  Danke vielmals Soeren.

Nikos
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