issue_comments: 573034827

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https://github.com/pydata/xarray/issues/3681#issuecomment-573034827 https://api.github.com/repos/pydata/xarray/issues/3681 573034827 MDEyOklzc3VlQ29tbWVudDU3MzAzNDgyNw== 35968931 2020-01-10T13:27:52Z 2020-01-10T13:27:52Z MEMBER

Looks like instead of using compat you can tell concat to just use the indexers (so lat, lon etc.) from the leftmost object using join='left', so it will ignore the (small) differences and return you python ds3 = xr.concat([ds1,ds2], dim='time', join='left')

<xarray.Dataset> Dimensions: (bnds: 2, lat: 96, lon: 144, time: 1152) Coordinates: height float64 2.0 * lon (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5 * lat (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0 * time (time) object 2006-01-16 12:00:00 ... 2101-12-16 12:00:00 Dimensions without coordinates: bnds Data variables: time_bnds (time, bnds) object 2006-01-01 00:00:00 ... 2102-01-01 00:00:00 lat_bnds (time, lat, bnds) float64 -90.0 -89.05 -89.05 ... nan nan nan lon_bnds (time, lon, bnds) float64 -1.25 1.25 1.25 ... 356.2 356.2 358.8 tas (time, lat, lon) float32 244.75986 244.83588 ... nan nan Attributes: institution: Norwegian Climate Centre institute_id: NCC experiment_id: rcp26 source: NorESM1-ME 2011 atmosphere: CAM-Oslo (CAM4-Oslo-... model_id: NorESM1-ME forcing: GHG, SA, Oz, Sl, BC, OC parent_experiment_id: historical parent_experiment_rip: r1i1p1 branch_time: 56940.0 contact: Please send any requests or bug reports to noresm... initialization_method: 1 physics_version: 1 tracking_id: fd266701-a253-4b74-91e1-5c0213483ba2 product: output experiment: RCP2.6 frequency: mon creation_date: 2012-05-16T19:40:05Z history: 2012-05-16T19:40:05Z CMOR rewrote data to comply ... Conventions: CF-1.4 project_id: CMIP5 table_id: Table Amon (01 February 2012) 81f919710c21dca8a17... title: NorESM1-ME model output prepared for CMIP5 RCP2.6 parent_experiment: historical modeling_realm: atmos realization: 1 cmor_version: 2.7.1 Is that what you're after? Best to check through the data explicitly

 
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