Editing Basin Geometry and Mountain Snowpack Responses to Climate Change: Data, Code, and Figures

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Division(s) to which this Record Belongs

CCRN: Changing Cold Regions Network
DRI: Drought Research Initiative
GWF: Global Water Futures
GWFO: Global Water Futures Observatories
INARCH: International Network of Alpine Research Catchment Hydrology
IP3: Improving Processes & Parameterization for Prediction in Cold Regions Hydrology
MAGS: The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study

Related Information

Overview Research Site Status and Provenance Access and Downloads

Section 1: Overview

Name of Research Project

Related Project	Part

Program Affiliations

CCRN: Changing Cold Regions Network
DRI: Drought Research Initiative
GWF: Global Water Futures
GWFO: Global Water Futures Observatories
GIWS: Global Institute for Water Security
INARCH: International Network of Alpine Research Catchment Hydrology
IP3: Improving Processes and Parameterization for Prediction in Cold Regions Hydrology
MAGS: The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study

Related Research Project(s)

Dataset Title

Additional Information

Creators and Contributors

Abstract

Purpose

Plain Language Summary

Keywords

Citations

Section 2: Research Site

Temporal Extent

Begin Date	End Date

Geographic Bounding Box

West Boundary Longitude
East Boundary Longitude
North Boundary Latitude
South Boundary Latitude

Is Boundary Rectangular

Yes

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Research Site Description (if needed)

Basin

Subbasin

Specific Locations (if needed)

Research Site Location

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Display

View on Global Map

Description: Latitude: Longitude: Classification: Subclassification: Regions, Bounding Boxes, and Pins:

Section 3: Status and Provenance

Dataset Version

Dataset Creation Date

Status of data collection/production

Planned

In Progress

Abandoned

Complete

Dataset Completion or Abandonment Date

Data Update Frequency

Continually

Daily

Weekly

Biweekly

Monthly

Anually

As needed

Irregular

None planned

Unknown

Creation Software

Primary Source of Data

Unknown/Unspecified
Census
Field collected samples
Field experiment
Field observation
Field survey
Human biological samples
Lab experiment
Model simulation
Previously collected
Qualitative (from observations or interviews)
Social survey
Traditional knowledge
Other Source of Data (Please specify in field below)

Other Source of Data (if applicable)

Data Lineage (if applicable). Please include versions (e.g., input and forcing data, models, and coupling modules; instrument measurements; surveys; sample collections; etc.)

1. Description of methods used for collection/generation of data:

Temperature and snow observations (snow course and snow pillow) obtained from government repositories. Elevation data obtained from GLOBE DEM. Model outputs generated by CRHM.

Manual snow survey site locations (Government of BC - https://catalogue.data.gov.bc.ca/dataset/9f653102-5627-45a7-bd4c-686e365ee04a)
Manual snow survey site data (Government of BC - https://catalogue.data.gov.bc.ca/dataset/705df46f-e9d6-4124-bc4a-66f54c07b228)
Snow pillow data (Government of BC - https://aqrt.nrs.gov.bc.ca/Data/)
Climate Normals (ECCC - https://climate.weather.gc.ca/climate_normals/index_e.html)
Global Land One-kilometer Base Elevation (NOAA - https://doi.org/10.7289/V52R3PMS)

2. Methods for processing the data: NA

3. Instrument- or software-specific information needed to interpret the data:

The version of Python used in this analysis is 3.7.6. Required packages are listed below in the code-specific information section and in the notebook preamble.

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CODE-SPECIFIC INFORMATION FOR: BasinHypsometryCRHM-Final.ipynb
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1. Brief description of the code:

Jupyter notebook does the following: 
- calculates and clusters basin hypsometries
- assesses the skill of simple linear accumulation gradients and synthetic temperatures against observational data
- imports results of the CRHM model runs to assess snow pack and snow melt responses to increased temperatures
- produces figures contained in the Shea et al. (2021) publication

2. List required dependencies:

CRHM 05/15/19
Python 3.7.6
datetime 4.3
matplotlib 3.1.2
matplotlib-base 3.1.2
pandas 0.25.3
glob2 0.7
scipy 1.3.2
geopandas 0.8.0
scikit-learn 0.22

3. Instructions to install or use the code:

Use jupyter notebook to open the code, and ensure that all packages are installed. Outputs from the CRHM model are provided in the data folder, but users can also obtain and run the CRHM model using the .obs files contained in the CRHMobs subfolder.

4. List any required input:

Data subfolder.

5. List expected output:

To produce figures used in the paper, create a new subfolder called 'Figure' and uncomment the plt.savefig() commands.

Section 4: Access and Downloads

Access to the Dataset

Does the data have access restrictions?

No restriction (data is currently open to public)
Limited (data is currently under embargo until publication)
Limited (data involves intellectual property issues related to local or traditional knowledge)
Limited (release of data may cause harm to the environment or to the public)
Limited (pre-existing data has been used and is subject to access restrictions)
Limited (data involves human subjects)
Limited (data is supported by industry partnerships)
Limited (data is supported by government partnerships)

Downloading and Characteristics of the Dataset

Download Links and Instructions

Total Size of all Dataset Files (GB)

File formats and online databases

Link to online database or web services (e.g., WISKI, ECCC)
Archive files (.zip, .rar, .7z, .tar, .tgz, .tar.gz, etc.)
CSV files (.csv - comma or tab separated value files)
Excel document files (.xlsx, .xls)
Image files (e.g., .tiff, .jpeg, .png, .gif, etc.)
NetCDF files (.netcdf, .nc)
Text files (.txt)
Word document files (.docx, .doc)
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Other Data Formats (if applicable)

List of Parameters and Variables