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290023410 MDU6SXNzdWUyOTAwMjM0MTA= 1844 How to broadcast along dayofyear botev 1889878 closed 0     16 2018-01-19T16:01:16Z 2022-06-22T15:30:45Z 2018-01-23T17:07:17Z NONE      

Ok so here is the problem I'm trying to solve, for which I did not find any solution: I have a spatial dataset with the following format (tempeature over time on a spatial grid): Dimensions: (depth: 1, latitude: 481, longitude: 781, time: 730) Coordinates: * time (time) datetime64[ns] 2016-01-01T11:59:37.961193472 ... * longitude (longitude) float32 -75.0 -74.9167 -74.8333 -74.75 -74.6667 ... * latitude (latitude) float32 25.0 25.0833 25.1667 25.25 25.3333 25.4167 ... * depth (depth) float32 0.494025 Data variables: thetao (time, depth, latitude, longitude) float64 ... Attributes: title: daily mean fields from Global Ocean Physics Analysis an... institution: MERCATOR OCEAN references: http://www.mercator-ocean.fr source: MERCATOR PSY4QV3R1 Conventions: CF-1.0 history: Data extracted from dataset http://opendap-glo.mercator... time_min: 578556.0 time_max: 596052.0 julian_day_unit: hours since 1950-01-01 00:00:00 z_min: 0.494024991989 z_max: 0.494024991989 latitude_min: 25.0 latitude_max: 65.0 longitude_min: -75.0 longitude_max: -10.0 These all contain temperture values. From another source I receive specially calibrated mean and standard deviation of temperatures for every day of the year. The mean dataset (std is the same) looks like this: Dimensions: (dayofyear: 366, depth: 1, latitude: 481, longitude: 781) Coordinates: * longitude (longitude) float32 -75.0 -74.9167 -74.8333 -74.75 -74.6667 ... * latitude (latitude) float32 25.0 25.0833 25.1667 25.25 25.3333 25.4167 ... * depth (depth) float32 0.494025 * dayofyear (dayofyear) int64 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 ... Data variables: thetao (dayofyear, depth, latitude, longitude) float64 25.06 25.16 ... What I want to achieve is to construct from the temperatures dataset a new one with standardized temperatures. The issue is I do not know how. The first thing I thought is to do something like: new_dset = (dset.groupby("time.dateofyear") - mean) / std However, the issue now is that I can't undo the "groupby". At this point I did not manage to figure out of how to either undo this, or in general the right approach for performing the operation I want. 

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