Python xarray xr.open_mfdataset error "ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation"

Question

I am facing an issue using xarray xr.open_mfdataset. I assume it happens because my netcdf files do not have a time dimension (daily mean values; only one timestep each file). However; I do not understand how I could merge the files despite this? The files have the same lat and lon dimensions. Any suggestion? Many thanks for hints! Please find my code + netcdf file description + error message below.

CODE:

%matplotlib inline
import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
import os
import warnings
from shapely.geometry.polygon import LinearRing
from matplotlib import gridspec

MYPATH = os.path.join("C:\\","Users","Judith Marina","phd","Data","Satellite_data","NorthSea_Storms")
print(MYPATH)
input_root = os.path.join(MYPATH,"Xaver_AQUA_MODIS_L3_NSST")
print(input_root)

dir_list = os.listdir(input_root)
print("Files and directories in '", input_root, "' :")
#prints all files
print(dir_list)

ds = xr.open_mfdataset(dir_list)

ERROR MESSAGE:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
C:\Users\JUDITH~2\AppData\Local\Temp/ipykernel_6028/798315470.py in <module>
----> 1 ds = xr.open_mfdataset(dir_list)

~\miniconda3\lib\site-packages\xarray\backends\api.py in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)
    934             # Redo ordering from coordinates, ignoring how they were ordered
    935             # previously
--> 936             combined = combine_by_coords(
    937                 datasets,
    938                 compat=compat,

~\miniconda3\lib\site-packages\xarray\core\combine.py in combine_by_coords(data_objects, compat, data_vars, coords, fill_value, join, combine_attrs, datasets)
    973         concatenated_grouped_by_data_vars = []
    974         for vars, datasets_with_same_vars in grouped_by_vars:
--> 975             concatenated = _combine_single_variable_hypercube(
    976                 list(datasets_with_same_vars),
    977                 fill_value=fill_value,

~\miniconda3\lib\site-packages\xarray\core\combine.py in _combine_single_variable_hypercube(datasets, fill_value, data_vars, coords, compat, join, combine_attrs)
    624         )
    625 
--> 626     combined_ids, concat_dims = _infer_concat_order_from_coords(list(datasets))
    627 
    628     if fill_value is None:

~\miniconda3\lib\site-packages\xarray\core\combine.py in _infer_concat_order_from_coords(datasets)
    142 
    143     if len(datasets) > 1 and not concat_dims:
--> 144         raise ValueError(
    145             "Could not find any dimension coordinates to use to "
    146             "order the datasets for concatenation"

ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation

NETCDF FILE CHARACTERISTICS

File.variables.keys()
KeysView(Frozen({'sst': <xarray.Variable (lat: 4320, lon: 8640)>
[37324800 values with dtype=float32]
Attributes:
    long_name:      Sea Surface Temperature
    units:          degree_C
    standard_name:  sea_surface_temperature
    valid_min:      [-1000]
    valid_max:      [10000]
    display_scale:  linear
    display_min:    [-2.]
    display_max:    [45.], 'qual_sst': <xarray.Variable (lat: 4320, lon: 8640)>
[37324800 values with dtype=float32]
Attributes:
    long_name:  Quality Levels, Sea Surface Temperature
    valid_min:  [0]
    valid_max:  [5], 'lat': <xarray.IndexVariable 'lat' (lat: 4320)>
array([ 89.979164,  89.9375  ,  89.89583 , ..., -89.895836, -89.93751 ,
       -89.97918 ], dtype=float32)
Attributes:
    long_name:      Latitude
    units:          degrees_north
    standard_name:  latitude
    valid_min:      [-90.]
    valid_max:      [90.], 'lon': <xarray.IndexVariable 'lon' (lon: 8640)>
array([-179.97917, -179.9375 , -179.89584, ...,  179.89583,  179.93752,
        179.97917], dtype=float32)
Attributes:
    long_name:      Longitude
    units:          degrees_east
    standard_name:  longitude
    valid_min:      [-180.]
    valid_max:      [180.], 'palette': <xarray.Variable (rgb: 3, eightbitcolor: 256)>
array([[ 91,  10, 118, ..., 238, 223,   8],
       [237, 216,   8, ...,   8, 224, 127],
       [  8, 224, 119, ...,   0,   0,   0]], dtype=uint8)}))