How to calculate monthly mean from daily netCDF file?

How to calculate monthly mean from daily netCDF file?

Hello I have a netcdf file with daily data. Shape of the file is (5844, 89, 89) i.e 16 years data. I tried to get monthly average from daily data. I am looking for simillar to resample function in pandas dataframe. Is there anyways to do that in python. As I know it is very easy to calculate by using cdo and nco but I am looking in python.

How to calculate a flux quantity in netCDF?

Calculate a flux quantity Simple math and how to change the variable type Add or modify file attributes Rename a variable, dimension, or attribute Concatenating files (appending in time) Fixing the time variable, Part I: Adding a record dimension.

Are there any command line utilities for netCDF?

A set of command-line utilities called netCDF operators (NCOs)are available on most of the linux machines, and Mac and PC versions can be downloaded. NCOs permit you to perform simple calculations and manipulations of netCDF or HDF4 files with only a minimal knowledge of the netcdf files.

What can a NCO do for a netCDF file?

NCOs permit you to perform simple calculations and manipulations of netCDF or HDF4 files with only a minimal knowledge of the netcdf files. NCOs can be an order of magnitude faster than processing data with matlab or other analysis packages.

How to convert TIF data to netCDF format?

Please note that your data will not be shared to anybody without your intervention. Upload your TIF (GTiff, TIFF, GeoTIFF) data (widely used in software like BEAM and ER Mapper) and convert them by one click to NETCDF format (widely used in software like QGIS).

How are time averages stored in a NCO?

In this case the time averages are the averages over 5 days. With the exception of ncrcat, there are always only one input and one output file in a NCO operation. One way to include two or more input variables in a calculation is to append additional variable files to a file. The reanalysis daily-average data is stored as one year per file.

https://www.youtube.com/watch?v=hrm5RmsVXo0