Calculating anomalies of 6-hourly data sets
Added by Lyndon Mark Olaguera about 6 years ago
Dear CDO-support,
I would like to ask how can I calculate anomalies or multi-year means (at least) from 6-hourly data sets.
I have 6-hourly data of wind from 1979-2017. In this case, I have to consider the leap years.
I tried using the yhourmean (multi-year hourly mean) function but this ignores the leap years.
Is there a way to do this in CDO?
I'll appreciate any help.
--Lyndz
Replies (4)
RE: Calculating anomalies of 6-hourly data sets - Added by Ralf Mueller about 6 years ago
hi!
what do exactly mean with multi-year means? running mean over two years? or compute the yearly mean value from your 30year input?
cheers
ralf
RE: Calculating anomalies of 6-hourly data sets - Added by Lyndon Mark Olaguera about 6 years ago
Hi Ralf,
Thank you for the response.
What I mean by multi-year mean is like the 1979-2017 mean per timestep (climatology): The average of all 00Z,06Z,12Z, and 18Z of January 1 from 1979-2017, and so on and so forth.
Update:
I already found a way to do this. The yhourmean works for the 6-hourly data as well.
It's just that the year of February 29 in the final output follows the nearest leap year (2016), while all other dates follow the last year (2017).
I solved this using the setyear command in CDO.
--Lyndz
RE: Calculating anomalies of 6-hourly data sets - Added by Ralf Mueller about 6 years ago
may be deleting the 29 February would help here: Use the operator del29feb for that ... just in case
RE: Calculating anomalies of 6-hourly data sets - Added by Pankaj Upadhyaya almost 6 years ago
Dear Lyndz,
In line with your problem, I have a similar issue. I want to calculate 6hr anomaly wrt. 21 days running mean i.e 21X4=84 timesteps. Could you please help me? Thanks in advance-