Average cumulative mass balance of reference Glaciers worldwide

core

Files Size Format Created Updated License Source
2 66kB csv zip 6 months ago 2 months ago ODC-PDDL-1.0 Average cumulative mass balance of reference Glaciers worldwide
Average cumulative mass balance of "reference" Glaciers worldwide from 1945-2014 sourced from US EPA and the World Glacier Monitoring Service (WGMS). This is cumulative change in mass balance of a set of "reference" glaciers worldwide beginning in 1945. The values represents the average of all the read more
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Data Files

File Description Size Last changed Download
glaciers 1kB csv (1kB) , json (6kB)
glacier-mass-balance_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 6kB zip (6kB)

glaciers  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
Year 1 year Year of measurement
Mean cumulative mass balance 2 number Average mass of measured glacier
Number of observations 3 number Number of glaciers observed

Read me

Average cumulative mass balance of “reference” Glaciers worldwide from 1945-2014 sourced from US EPA and the World Glacier Monitoring Service (WGMS). This is cumulative change in mass balance of a set of “reference” glaciers worldwide beginning in 1945. The values represents the average of all the glaciers that were measured. Negative values indicate a net loss of ice and snow compared with the base year of 1945. For consistency, measurements are in meters of water equivalent, which represent changes in the average thickness of a glacier.

Data

Sources

Related publications:

WGMS (2015): Global Glacier Change Bulletin No. 1 (2012-2013). Zemp, M., Gärtner-Roer, I., Nussbaumer, S.U., Hüsler, F., Machguth, H., Mölg, N., Paul, F., and Hoelzle, M. (eds.), ICSU(WDS)/IUGG(IACS)/UNEP/UNESCO/WMO, World Glacier Monitoring Service, Zurich, Switzerland, 230 pp. Based on database version: doi: 10.5904/wgms-fog-2015-11. WGMS (2013): Glacier Mass Balance Bulletin No. 12 (2010-2011). Zemp, M., Nussbaumer, S.U., Naegeli, K., Gärtner-Roer, I., Paul, F., Hoelzle, M. and Haeberli, W. (eds.), ICSU (WDS) / IUGG (IACS) / UNEP / UNESCO / WMO, World Glacier Monitoring Service, Zurich, Switzerland: 106 pp., publication based on database version:doi:10.5904/wgms-fog-2013-11.

WGMS (2012): Fluctuations of Glaciers 2005-2010 (Vol. X): Zemp, M., Frey, H., Gärtner-Roer, I., Nussbaumer, S.U., Hoelzle, M., Paul, F. & W. Haeberli (eds.), ICSU (WDS)/ IUGG (IACS)/ UNEP/ UNESCO/ WMO, World Glacier Monitoring Service, Zurich, Switzerland. Based on database version doi: 10.5904/wgms-fog-2012-11.

WGMS (World Glacier Monitoring Service). 2015 update to data originally published in: WGMS. 2013. Glacier mass balance bulletin no. 12 (2010–2011). Zemp, M., S.U. Nussbaumer, K. Naegeli, I. Gärtner-Roer, F. Paul, M. Hoelzle, and W. Haeberli (eds.). ICSU (WDS)/IUGG (IACS)/UNEP/UNESCO/WMO. Zurich, Switzerland: World Glacier Monitoring Service. http://wgms.ch/downloads/wgms_2013_gmbb12.pdf. WGMS World Glacier Monitoring Service, Zurich, Switzerland

License

Data

EPA is Federal Government so public domain we would assume.

WGMS make their data available as “Open access for scientific and educational purposes under requirement of correct citation”:

WGMS (2015): Fluctuations of Glaciers Database. World Glacier Monitoring Service, Zurich, Switzerland. DOI:10.5904/wgms-fog-2015-11.

Additional work

All the additional work made to build this Data Package is made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/

Citations

WGMS (World Glacier Monitoring Service). 2015 update to data originally published in: WGMS. 2013. Glacier mass balance bulletin no. 12 (2010–2011). Zemp, M., S.U. Nussbaumer, K. Naegeli, I. Gärtner-Roer, F. Paul, M. Hoelzle, and W. Haeberli (eds.). ICSU (WDS)/IUGG (IACS)/UNEP/UNESCO/WMO. Zurich, Switzerland: World Glacier Monitoring Service. http://wgms.ch/downloads/wgms_2013_gmbb12.pdf.

Useful info

There does seem to be more recent data because there are graphs with more recent e.g. graphs like this on Climate.gov, or PDF data like this from World Glacier monitoring service and this PDF from WGMS.

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

data get https://datahub.io/core/glacier-mass-balance
data info core/glacier-mass-balance
tree core/glacier-mass-balance
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/glacier-mass-balance/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/glacier-mass-balance/r/0.csv

curl -L https://datahub.io/core/glacier-mass-balance/r/1.zip

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

json_file <- 'https://datahub.io/core/glacier-mass-balance/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))
    print(data)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/core/glacier-mass-balance/datapackage.json'

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('https://datahub.io/core/glacier-mass-balance/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        print(resource.read())

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'https://datahub.io/core/glacier-mass-balance/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
;(async () => {
  const dataset = await Dataset.load(path)
  // get list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()
Datapackage.json