def METHOD_NAME(cls, shape, chunks=None):
    size = int(np.prod(shape))
    dims = ["time", "y", "x"]
    a_data = np.linspace(0, 1, size, dtype=np.float64).reshape(shape)
    a = xr.DataArray(a_data, dims=dims)
    b_data = np.linspace(-1, 0, size, dtype=np.float64).reshape(shape)
    b = xr.DataArray(b_data, dims=dims)
    if chunks:
        a.encoding.update(chunks=chunks, chunksizes=chunks)
        b.encoding.update(chunks=chunks, chunksizes=chunks)
        return xr.Dataset(dict(a=a, b=b)) \
            .chunk(chunks={dims[i]: chunks[i]
                           for i in range(len(dims))})
    else:
        return xr.Dataset(dict(a=a, b=b))