Ontario Climate Data Portal (OCDP)

What is this data portal?

A collection of frequently used data sets from yorku.ca/ocdp and many simple python codes for reading, plotting and exporting the data. (total size: ~580M in zip format or ~1.0GB after unzip). For the Terabytes daily data of individual models, we provided programs to directly read them from OCDP database. Users don't need download them to local machine.

Data for Maps section

• Basic Variables (temperature, minimum temperature, maximum temperature and precipitation)

  • Convert data to standard csv files
  • Read and map the changes of the basic variables for 2050s and 2080s relative to reference period (1986-2005)

• Climate extremes indices (38 widely used indices)

  • Convert indices data to standard csv files
  • Read and map the changes of the indices for 2050s and 2080s relative to the reference period

Data for Time series section

• Read and plot annual variation of provincial averages and decadal variations for 50 regions and 150 cities

Data for data download section

• Ensemble mean

  • Provincial averages
  • Regional averages
  • Municipalities
  • Grids

• Individual models <br/>For daily data of individual models, our codes could directly read the data from the OCDP site. So, users don't need download the huge data to local machine. We will not upload these daily data sets to our github site as well.

  • Municipalites
  • Grids

Why shoud we make it?

As there are a lot of data sets provided by OCDP in different formats, some beginners don't know how to use these data sets in their researches. To facilitate the use of the data, we copied some frequently used data sets to this site and provided simply python programs to process these data sets.

Who made it?

The yorku.ca/ocdp developer team. (contact us:lamps@yorku.ca)

When we made it?

We began develop this site in October 2019 and we are continue to improve it according to feedback from our users.

Where should I put it?

Anything in this site is open source. Any one can fork it or clone it to his/her local machine and revise the code according to specific requirements.

How should I use it?

Install Python 3.6+ and dependent packages

Install Anaconda. After this installation, updated python and most popular python packages are installed (e.g., jupyter notebook, numpy, pandas, matplotlib, scipy, requests).

conda install geopandas
conda install h5py

Warning: The package geopandas depends on many geographic packages, which are not easy to install with pip. Therefore, we strongly recommend users use conda to install geopandas (for generate maps).

Clone and unzip to your local machine

cd (your path)/ocdpData/pythonCode
jupyter notebook

Revise (e.g., variable name, location, model name, RCP, or other settings) and run the code.

If users do not want to use jupyter notebook, they can copy codes to python files and run python programs in general python environment.

JavaScript and html5 programs

In this directory, we stored main html5 programs and linked JavaSript file and an example sub link for the front page and maps, data, time series and documents pages:

• index.htm -- front page
• index_app_maps.htm -- maps
• index_app_timeseries.htm -- time series
• index_app_data.htm -- data
• index_app_documents.htm -- documents

Back to OCDP

License

MIT