wrf.g_cloudfrac.get_low_cloudfrac¶
- wrf.g_cloudfrac.get_low_cloudfrac(wrfin, timeidx=0, method='cat', squeeze=True, cache=None, meta=True, _key=None, vert_type='height_agl', low_thresh=None, mid_thresh=None, high_thresh=None, missing=<MagicMock name='mock().item()' id='140499233145616'>)¶
Return the cloud fraction for the low level clouds.
If the vertical coordinate type is ‘height_agl’ or ‘height_msl’, the default cloud levels are defined as:
300 m <= low_cloud < 2000 m 2000 m <= mid_cloud < 6000 m 6000 m <= high_cloud
For ‘pressure’, the default cloud levels are defined as:
97000 Pa <= low_cloud < 80000 Pa 80000 Pa <= mid_cloud < 45000 Pa 45000 Pa <= high_cloud
Note that the default low cloud levels are chosen to exclude clouds near the surface (fog). If you want fog included, set low_thresh to ~99500 Pa if vert_type is set to ‘pressure’, or 15 m if using ‘height_msl’ or ‘height_agl’. Keep in mind that the lowest mass grid points are slightly above the ground, and in order to find clouds, the low_thresh needs to be set to values that are slightly greater than (less than) the lowest height (pressure) values.
When using ‘pressure’ or ‘height_agl’ for vert_type, there is a possibility that the lowest WRF level will be higher than the low_cloud or mid_cloud threshold, particularly for mountainous regions. When this happens, a fill value will be used in the output.
This functions extracts the necessary variables from the NetCDF file object in order to perform the calculation.
- Parameters:
wrfin (
netCDF4.Dataset
,Nio.NioFile
, or an iterable) – WRF-ARW NetCDF data as anetCDF4.Dataset
,Nio.NioFile
or an iterable sequence of the aforementioned types.timeidx (
int
orwrf.ALL_TIMES
, optional) – The desired time index. This value can be a positive integer, negative integer, orwrf.ALL_TIMES
(an alias for None) to return all times in the file or sequence. The default is 0.method (
str
, optional) – The aggregation method to use for sequences. Must be either ‘cat’ or ‘join’. ‘cat’ combines the data along the Time dimension. ‘join’ creates a new dimension for the file index. The default is ‘cat’.squeeze (
bool
, optional) – Set to False to prevent dimensions with a size of 1 from being automatically removed from the shape of the output. Default is True.cache (
dict
, optional) – A dictionary of (varname, ndarray) that can be used to supply pre-extracted NetCDF variables to the computational routines. It is primarily used for internal purposes, but can also be used to improve performance by eliminating the need to repeatedly extract the same variables used in multiple diagnostics calculations, particularly when using large sequences of files. Default is None.meta (
bool
, optional) – Set to False to disable metadata and returnnumpy.ndarray
instead ofxarray.DataArray
. Default is True._key (
int
, optional) – A caching key. This is used for internal purposes only. Default is None.vert_type (
str
, optional) – The type of vertical coordinate used to determine cloud type thresholds. Must be ‘height_agl’, ‘height_msl’, or ‘pres’. The default is ‘height_agl’.low_thresh (
float
, optional) – The lower bound for what is considered a low cloud. If vert_type is ‘pres’, the default is 97000 Pa. If vert_type is ‘height_agl’ or ‘height_msl’, then the default is 300 m.mid_thresh (
float
, optional) – The lower bound for what is considered a mid level cloud. If vert_type is ‘pres’, the default is 80000 Pa. If vert_type is ‘height_agl’ or ‘height_msl’, then the default is 2000 m.high_thresh (
float
, optional) – The lower bound for what is considered a high level cloud. If vert_type is ‘pres’, the default is 45000 Pa. If vert_type is ‘height_agl’ or ‘height_msl’, then the default is 6000 m.
- Returns:
The cloud fraction array for low level clouds. If xarray is enabled and the meta parameter is True, then the result will be a
xarray.DataArray
object. Otherwise, the result will be anumpy.ndarray
object with no metadata.- Return type: