interpolate using quadratic returns nan

What happened?

When using a multiple dimensions xarray (like time, x and y), the quadratic function is not working anymore with interpolate, it returns only nan. slinear is ok. quadratic is only ok when using only a dimension (like only a lat/lon value).

What did you expect to happen?

No response

Minimal Complete Verifiable Example

import xarray as xr

ds = xr.tutorial.load_dataset("ersstv5")
# Generate a subset
subset = ds['sst'].isel(time=slice(0,10),lat=slice(20,40),lon=slice(20,40))
## Plot images
subset.plot(col="time",col_wrap=6)

# Interpolate with quadratic
subset_quadratic = subset.resample(time='10D').interpolate('quadratic')
## subset_quadratic is now full of NaN
subset_quadratic.plot(col="time",col_wrap=6)

# Working with only time dimension
subset_quadratic = subset.isel(lat=0,lon=0).resample(time='10D').interpolate('quadratic')
subset_quadratic.plot()

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

No response

Environment

Start by running the reported xarray tutorial example with subset.resample(time='10D').interpolate('quadratic'), comparing multidimensional output with the one-dimensional case. Trace the resample/interpolate entry points to identify where quadratic interpolation produces NaN across lat and lon, then add a regression test showing valid multidimensional results.