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using Zarr, YAXArrays
using DimensionalData
using CFTime
# chunksize(c) = Cubes.cubechunks(c)
store ="gs://cmip6/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp585/r1i1p1f1/3hr/tas/gn/v20190710/"@time g =open_dataset(zopen(store, consolidated=true))
c = g.tas
@time kelvinCube = c[time=Between(DateTime("2030-01-01"), DateTime("2030-04-01"))]
@timesavecube(kelvinCube, "temp-02.zarr")
julia> kelvinCube
384×192×721 YAXArray{Float32,3} with dimensions:
Dim{:lon} Sampled{Float64} 0.0:0.9375:359.0625 ForwardOrdered Regular Points,
Dim{:lat} Sampled{Float64} Float64[-89.28422753251364, -88.35700351866494, …, 88.35700351866494, 89.28422753251364] ForwardOrdered Irregular Points,
Ti Sampled{DateTime} DateTime[2030-01-01T00:00:00, …, 2030-04-01T00:00:00] ForwardOrdered Irregular Points
units: K
name: tas
Total size:202.78 MB
Ti should has a length of 721.
However, the length of time dimension in the zarr file is 880
ds =Cube("temp-02.zarr") # correct if open by YAXArrays
ds.Time
julia># length of time is 880
times =zopen("temp-02.zarr/Time")[:]
CFTime.timedecode(times, "days since 1980-01-01", "standard")
880-element Vector{DateTime}:2029-12-12T03:00:002029-12-12T06:00:002029-12-12T09:00:002029-12-12T12:00:002029-12-12T15:00:002029-12-12T18:00:002029-12-12T21:00:002029-12-13T00:00:002029-12-13T03:00:002029-12-13T06:00:002029-12-13T09:00:002029-12-13T12:00:002029-12-13T15:00:00⋮2030-03-30T12:00:002030-03-30T15:00:002030-03-30T18:00:002030-03-30T21:00:002030-03-31T00:00:002030-03-31T03:00:002030-03-31T06:00:002030-03-31T09:00:002030-03-31T12:00:002030-03-31T15:00:002030-03-31T18:00:002030-03-31T21:00:002030-04-01T00:00:00
Ti should has a length of 721.
However, the length of time dimension in the zarr file is 880
Double check in Python
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