Merge pull request #126 from Ouranosinc/climate_dataset_section

Repair Climate Information Ressources notebook code.

Author: vindelico

ecdg_report/datasets/Climate_Data_Fundamentals.ipynb

@@ -187,9 +187,9 @@
     "### CF Conventions (Climate and Forecast Metadata Conventions)\n",
     "::: {#id .callout collapse=\"true\"}\n",
     "### Click for details\n",
-    "**Created by:** International climate science community (NOAA, UCAR, and others) in 2003 (CF-1.0)</br>  \n",
-    "**Purpose:** Standardized metadata conventions for climate and forecast datasets</br>  \n",
-    "**Typical use:** Metadata framework for [netCDF](#netcdf-network-common-data-form) climate datasets</br>  \n",
+    "**Created by:** International climate science community (NOAA, UCAR, and others) in 2003 (release of CF-1.0)</br>\n",
+    "**Purpose:** Standardized metadata conventions for climate and forecast datasets</br>\n",
+    "**Typical use:** Metadata framework for [netCDF](#netcdf-network-common-data-form) climate datasets</br>\n",
     "**Distinguishing features:** </br>\n",
     "\n",
     "- Standard variable naming conventions\n",
@@ -202,7 +202,7 @@
     "CF Conventions are not a data format themselves but a widely adopted metadata standard used primarily with [netCDF](#netcdf-network-common-data-form) files. They define how variables, coordinates, units, and metadata should be described so that datasets can be interpreted consistently across software tools and research communities. For example, CF specifies how latitude, longitude, time, and vertical coordinates should be encoded, as well as standard variable names such as “*air_temperature*.” This allows climate analysis software to automatically recognize and process datasets without manual interpretation. Most modern climate datasets, including CMIP and CORDEX climate model simulations and many reanalysis products follow CF conventions. By ensuring consistent metadata structure across thousands of datasets, CF conventions play a critical role in enabling interoperability and large-scale climate data analysis.\n",
     ":::\n",
     "\n",
-    "### Zarr\n",
+    "### Zarr \n",
     "::: {#id .callout collapse=\"true\"}\n",
     "### Click for details\n",
     "**Created by:** [Zarr Open-source scientific computing community](https://zarr.dev/) in 2016</br>\n",
@@ -217,7 +217,7 @@
     "- Works well with object storage (e.g., cloud data lakes)\n",
     "\n",
     "**Description**</br>\n",
-    "Zarr is a storage format designed for large multidimensional arrays stored in distributed or cloud environments. Unlike traditional formats such as [netCDF](#netcdf-network-common-data-form) or [HDF5](#hdf5-hierarchical-data-format-version-5) that store data in a single file, Zarr stores datasets as collections of compressed chunks organized in directories or object storage systems. This structure allows efficient parallel access and partial loading of datasets without reading entire files. Zarr has become popular in cloud-based scientific computing environments such as the [Pangeo ecosystem](https://pangeo.io/), where massive climate datasets are accessed by distributed analysis tools. Many large climate archives are experimenting with converting netCDF collections into Zarr format to improve performance and accessibility for large-scale data analysis in cloud computing environments.\n",
+    "Zarr (**Z**ipped **arr**ay) is a storage format designed for large multidimensional arrays stored in distributed or cloud environments. Unlike traditional formats such as [netCDF](#netcdf-network-common-data-form) or [HDF5](#hdf5-hierarchical-data-format-version-5) that store data in a single file, Zarr stores datasets as collections of compressed chunks organized in directories or object storage systems. This structure allows efficient parallel access and partial loading of datasets without reading entire files. Zarr has become popular in cloud-based scientific computing environments such as the [Pangeo ecosystem](https://pangeo.io/), where massive climate datasets are accessed by distributed analysis tools. Many large climate archives are experimenting with converting netCDF collections into Zarr format to improve performance and accessibility for large-scale data analysis in cloud computing environments.\n",
     ":::\n",
     "\n",
     "### GeoTIFF (Geographic Tagged Image File Format)\n",

ecdg_report/datasets/Climate_Information_Ressources.ipynb

@@ -9,11 +9,7 @@
     "<!--- This section is quarto yml with a list of all refernces to be included on this page --->\n",
     "---\n",
     "title: Climate Information Resources\n",
-<<<<<<< climate_dataset_section
     "\n",
-=======
-    "  \n",
->>>>>>> main
     "---"
    ]
   },
@@ -26,9 +22,6 @@
     "\n",
     "## ClimateData.ca\n",
     "The [ClimateData.ca](https://climatedata.ca) online platform offers a wide range of resources related to the past and future Canadian climate data, as well as analysis tools and a large quantity of educational materials to support the assessment of climate change impacts and the development of mitigation and adaptation strategies. The site allows users to visualize climate projections over Canada and [download](https://climatedata.ca/download/) a number of datasets, notably Adjusted and Homogenized Canadian Climate Data ([AHCCD](../datasets/observed_data/AHCCD-CanHom_Station_Data.ipynb)), future building design values, Intensity-Duration-Frequency (IDF) rainfall data and observations from Canadian stations. The site also include information on [IDF Curves](https://climatedata.ca/learn/?#module-175), [infrastructure design in the context of a changing climate](https://climatedata.ca/learn/?#module-176), [seasonal forecasts](https://climatedata.ca/learn/?#module-212) as well as a series of resources on [climate science and climate data](https://climatedata.ca/learn/?), amongst others.\n",
-    "\n",
-    "## Climate READi Climate Data User Guide\n",
-    "[EPRI’s Climate Data User Guide](https://apps.epri.com/climate-data-user-guide/en/) is a technical resource for electrical system planners, regulators, and stakeholders that explains how to select, interpret, and apply climate and weather data for physical climate risk assessment relevant to energy systems. It describes sources and types of observed and projected climate information, outlines statistical concepts and methods for analyzing historical records and future projections, compares major climate models and emission scenarios, and provides guidance on choosing appropriate datasets and metrics for specific planning and resilience applications. The guide also discusses the relevance of different climate variables and extreme events to energy infrastructure performance and reliability, highlights common data limitations (e.g., downscaling and interpolation issues). The guide also outlines how to choose appropriate climate projections and datasets for specific planning applications, discusses climate change impacts on energy infrastructure performance and reliability, and provides references and practical guidance to support the use of climate information in resilience planning. The focus of the guide is on the United States, but much of the information is also relevant for Canada.\n",
     " \n",
     "## Climate-Resilient Buildings and Core Public Infrastructure (CRBCPI): An Assessment of the Impact of Climate Change on Climatic Design Data in Canada\n",
     "The [\"Climate-Resilient Buildings and Core Public Infrastructure: An Assessment of the Impact of Climate Change on Climatic Design Data in Canada”](https://publications.gc.ca/collections/collection_2021/eccc/En4-415-2020-eng.pdf) report by Environment and Climate Change Canada examines how historical climate variability and future climate change are altering climatic design data that guide infrastructure planning, design, and performance in Canada. It assesses observed changes and projected trends in key climate variables that inform design standards, such as temperature, precipitation, wind, and freeze-thaw cycles, and evaluates how these changes affect design parameters used for buildings and core public infrastructure under changing climate conditions. [Appendix 1](https://climate-scenarios.canada.ca/?page=buildings-report#appendix-1.1) includes tables of projected changes for each climatic design variable under different global warming levels. A summary of the report is available [here](https://climate-scenarios.canada.ca/?page=CRBCPI-general-summary).\n",