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This data has achieved Bronze level on 22 October 2015 which means this data makes a great start at the basics of publishing open data.
Climate Prediction Center (CPC) Global Monthly Leaky Bucket Soil Moisture Analysis
Summary
- Type of release
- ongoing release of a series of related datasets
- Data Licence
- Not Applicable
- Content Licence
- Creative Commons CCZero
- Verification
- automatically awarded
- Release Date
- 26 September 2015
- Modified Date
- 27 September 2015
- Update Frequency
- monthly
- Publishers
- National Oceanic and Atmospheric Administration, Department of Commerce
- Identifier
- climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis
- Landing Page
- http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis
- Theme
- climate5434
- Temporal Coverage
- 1 January 1948 — 25 August 2014
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Description
Monthly global soil moisture, runoff, and evaporation data sets produced by the Leaky Bucket model at 0.5? ? 0.5? resolution for the period from 1948 to the present. The land model is a one?layer ?bucket? water balance model, while the driving input fields are Climate Prediction Center monthly global precipitation over land, which uses over 17,000 gauges worldwide, and monthly global temperature from GHCN-CAMS (Fan and Van den Dool 2008). The output consists of global monthly soil moisture, evaporation, and runoff, starting from January 1948. A distinguishing feature of this data set is that all fields are updated monthly, which greatly enhances utility for near real time purposes. Data validation shows that the land model does well; both the simulated annual cycle and interannual variability of soil moisture are reasonably good against the limited observations in different regions. Refer to these papers: Fan, Y. and H. van den Dool (2004), Climate Prediction Center global monthly soil moisture data set at 0.5? resolution for 1948 to present, J. Geophys. Res., 109, D10102, doi:10.1029/2003JD004345. Fan, Y. and H. van den Dool (2008), A global monthly land surface air temperature analysis for 1948?present, J. Geophys. Res., 113, D01103, doi:10.1029/2007JD008470.
General Information
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This data is described at
http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis Do you think this data is incorrect? Let us know
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This data is published by
National Oceanic and Atmospheric Administration, Department of Commerce Do you think this data is incorrect? Let us know
Legal Information
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The rights statement is at
http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis Do you think this data is incorrect? Let us know
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Outside the US, this data is available under
Creative Commons CCZero Do you think this data is incorrect? Let us know
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There are
yes, and the rights are all held by the same person or organisation Do you think this data is incorrect? Let us know
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The content is available under
Creative Commons CCZero Do you think this data is incorrect? Let us know
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This data contains
no data about individuals Do you think this data is incorrect? Let us know
Practical Information
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The data appears in this collection
http://catalog.data.gov/organization/noaa-gov Do you think this data is incorrect? Let us know
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This data changes
no Do you think this data is incorrect? Let us know
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The data is
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Technical Information
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Releases of this data are listed at
http://catalog.data.gov/api/rest/package/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis Do you think this data is incorrect? Let us know
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Find out how to contact someone about this data at
http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis Do you think this data is incorrect? Let us know
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Find out how to suggest improvements to publication at
http://www.data.gov/issue/?media_url=http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-monthly-leaky-bucket-soil-moisture-analysis Do you think this data is incorrect? Let us know