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  • CLEX CMS Blog

Latest

  • Building custom python environments on top of conda/analysis3
  • Introduction to Pytorch
  • Python Perfomance Options
  • Speed up custom operations on large datasets with universal functions
  • Getting Seasonal Means for the season December-January-February

Tags

  • access
    • Adding a new task to a rose suite
  • bash
    • Filter Lists of Files in bash Using sed
    • Using GNU Parallel in bash scripts to optimize python processes
  • climatology
    • Climatologies with ‘Coarsen’
  • cmip
    • Using ARCCSSive to search CMIP5
    • Using CleF - Climate Finder to discover ESGF data at NCI
    • Using CleF 2: advanced command line functionalities
  • dask
    • Speeding up access to large datasets with Dask Delayed
    • API Calculation with Xarray + Dask
    • More efficent use of xarray.open_mfdataset()
    • Using a shapefile to select a region and calculate statistics
    • Introducing the dask-optimiser module
  • data
    • Using ARCCSSive to search CMIP5
    • Fast MOM collation with payu and mppnncombine-fast
    • Setting up NetCDF file attributes
    • Using OPeNDAP to access data remotely: MUR example
    • Using CleF - Climate Finder to discover ESGF data at NCI
    • Using CleF 2: advanced command line functionalities
    • Storage - where, what, why and how?
    • How and when to use PBS Jobfs on NCI HPC systems
    • More efficent use of xarray.open_mfdataset()
  • debug
    • Fortran Debugging Video Series
  • disk
    • Quick tip - Feed nci-file-expiry output back into itself
  • events
    • Basic event statistics
  • fortran
    • Fortran Debugging Video Series
    • How to create NetCDF files
    • Using Gadi’s software environment to build your applications
  • jupyter
    • Working with ARE notebooks in VS Code
    • Introducing the dask-optimiser module
  • model
    • Setting up a coupled model at a new resolution
  • netcdf
    • Python Tuesday: NetCDF Python library overview
    • How to create NetCDF files
    • Setting up NetCDF file attributes
    • Storage - where, what, why and how?
    • How and when to use PBS Jobfs on NCI HPC systems
    • More efficent use of xarray.open_mfdataset()
  • paleoclimate
    • An example of reading non-standard data using pandas and xarray
  • pandas
    • An example of reading non-standard data using pandas and xarray
  • payu
    • Fast MOM collation with payu and mppnncombine-fast
  • plotting
    • Improving maps with Cartopy
    • Python Plotting Basics
    • Subplots
    • Xarray plot types
    • Making a lat-lon reference plot
    • Visualisation in a Shiny App
    • Review of line plots with Xarray
    • Generating print-quality plots in R
    • How to animate 2D fields
    • Wrapping gridded data around the globe
    • Split Y Axis plots
  • pyproj
    • Converting between coordinate systems with Pyproj
    • Regridding from one coordinate system to another with pyproj
  • python
    • Improving maps with Cartopy
    • Python Plotting Basics
    • Reading ENVI_MET files
    • Subplots
    • Xarray plot types
    • Making a lat-lon reference plot
    • Python Tuesday: NetCDF Python library overview
    • Merge arrays with missing data
    • Using ARCCSSive to search CMIP5
    • Speeding up access to large datasets with Dask Delayed
    • Review of line plots with Xarray
    • Basic usage of python logging module
    • How to create NetCDF files
    • Find the value of a variable at the times when another variable is maximum
    • Using OPeNDAP to access data remotely: MUR example
    • Per-gridpoint time correlation of two models
    • How to animate 2D fields
    • Wrapping gridded data around the globe
    • Split Y Axis plots
    • Basic event statistics
    • Using xesmf to efficiently regrid data to another resolution
    • Using Gadi’s software environment to build your applications
    • Introducing the new hh5 conda environment
    • Working with ARE notebooks in VS Code
    • More efficent use of xarray.open_mfdataset()
    • Using a shapefile to select a region and calculate statistics
    • Introducing the dask-optimiser module
    • Using GNU Parallel in bash scripts to optimize python processes
    • Getting Seasonal Means for the season December-January-February
    • Speed up custom operations on large datasets with universal functions
    • Python Perfomance Options
    • Building custom python environments on top of conda/analysis3
  • python ML
    • Introduction to Pytorch
  • r
    • Visualisation in a Shiny App
    • Generating print-quality plots in R
  • raster
    • Using a shapefile to select a region and calculate statistics
  • regridding
    • Setting up a coupled model at a new resolution
    • Using xesmf to efficiently regrid data to another resolution
    • Regridding from one coordinate system to another with pyproj
  • shapefile
    • Using a shapefile to select a region and calculate statistics
  • storage
    • Storage - where, what, why and how?
    • How and when to use PBS Jobfs on NCI HPC systems
    • Quick tip - Feed nci-file-expiry output back into itself
  • um
    • Adding a new task to a rose suite
  • video
    • Fortran Debugging Video Series
  • vscode
    • Working with ARE notebooks in VS Code
  • xarray
    • Reading ENVI_MET files
    • Xarray plot types
    • Python Tuesday: NetCDF Python library overview
    • Merge arrays with missing data
    • Speeding up access to large datasets with Dask Delayed
    • Review of line plots with Xarray
    • Find the value of a variable at the times when another variable is maximum
    • Using OPeNDAP to access data remotely: MUR example
    • Per-gridpoint time correlation of two models
    • Climatologies with ‘Coarsen’
    • Converting between coordinate systems with Pyproj
    • Regridding from one coordinate system to another with pyproj
    • API Calculation with Xarray + Dask
    • An example of reading non-standard data using pandas and xarray
    • More efficent use of xarray.open_mfdataset()
    • Using a shapefile to select a region and calculate statistics
    • Introducing the dask-optimiser module
    • Getting Seasonal Means for the season December-January-February
    • Speed up custom operations on large datasets with universal functions

Archive

  • 2024
    • Building custom python environments on top of conda/analysis3
    • Introduction to Pytorch
    • Python Perfomance Options
  • 2023
    • Speed up custom operations on large datasets with universal functions
    • Getting Seasonal Means for the season December-January-February
    • Using GNU Parallel in bash scripts to optimize python processes
    • Introducing the dask-optimiser module
    • Using a shapefile to select a region and calculate statistics
    • More efficent use of xarray.open_mfdataset()
    • Working with ARE notebooks in VS Code
    • Adding a new task to a rose suite
    • Quick tip - Feed nci-file-expiry output back into itself
    • Introducing the new hh5 conda environment
    • How to stop temporary files filling up your /home directory on Gadi
  • 2022
    • Using Gadi’s software environment to build your applications
    • How and when to use PBS Jobfs on NCI HPC systems
    • Data Quarantine
    • Storage - where, what, why and how?
    • An example of reading non-standard data using pandas and xarray
  • 2021
    • Trajectories in regions
    • API Calculation with Xarray + Dask
    • Regridding from one coordinate system to another with pyproj
    • Converting between coordinate systems with Pyproj
    • Effect of rounding on coordinates with Xarray
    • Example to improve code design
    • Climatologies with ‘Coarsen’
    • Using xesmf to efficiently regrid data to another resolution
  • 2020
    • Using CleF 2: advanced command line functionalities
    • Basic event statistics
    • Using CleF - Climate Finder to discover ESGF data at NCI
    • Split Y Axis plots
    • Wrapping gridded data around the globe
  • 2019
    • Compare data with different calendars
    • How to animate 2D fields
    • Per-gridpoint time correlation of two models
    • Filter Lists of Files in bash Using sed
    • Generating print-quality plots in R
    • Setting up a coupled model at a new resolution
    • Using OPeNDAP to access data remotely: MUR example
  • 2018
    • Find the value of a variable at the times when another variable is maximum
    • Setting up NetCDF file attributes
    • Fast MOM collation with payu and mppnncombine-fast
    • How to create NetCDF files
    • Basic usage of python logging module
    • Review of line plots with Xarray
    • Speeding up access to large datasets with Dask Delayed
    • Visualisation in a Shiny App
    • Using ARCCSSive to search CMIP5
    • Fortran Debugging Video Series
    • Merge arrays with missing data
    • Python Tuesday: NetCDF Python library overview
    • Making a lat-lon reference plot
    • Xarray plot types
    • Subplots
    • Reading ENVI_MET files
    • Python Plotting Basics
    • Improving maps with Cartopy

Links

  • CLEX
  • CMS Wiki
  • NCI
  • Repository
  • Open issue
  • .rst

regridding

regridding#

regridding

  • Setting up a coupled model at a new resolution
  • Using xesmf to efficiently regrid data to another resolution
  • Regridding from one coordinate system to another with pyproj

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