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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 Land Surface Air Temperature 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-land-surface-air-temperature-analysis
Landing Page
http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-land-surface-air-temperature-analysis
Theme
climate5434
Temporal Coverage
1 January 1948 — 25 August 2014

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Description

A station observation-based global land monthly mean surface air temperature dataset at 0.5 x 0.5 latitude-longitude resolution for the period from 1948 to the present was developed at the Climate Prediction Center, National Centers for Environmental Prediction. This data set is different from some existing surface air temperature data sets in: (1) using a combination of two large individual data sets of station observations collected from the Global Historical Climatology Network version 2 and the Climate Anomaly Monitoring System (GHCN + CAMS), so it can be regularly updated in near real time with plenty of stations and (2) some unique interpolation methods, such as the anomaly interpolation approach with spatially-temporally varying temperature lapse rates derived from the observation-based Reanalysis for topographic adjustment. When compared with several existing observation-based land surface air temperature data sets, the preliminary results show that the quality of this new GHCN + CAMS land surface air temperature analysis is reasonably good and the new data set can capture most common temporal-spatial features in the observed climatology and anomaly fields over both regional and global domains. The study also reveals that there are clear biases between the observed surface air temperature and the existing Reanalysis data sets, and they vary in space and seasons. Therefore the Reanalysis 2 m temperature data sets may not be suitable for model forcing and validation. The GHCN + CAMS data set will be mainly used as one of land surface meteorological forcing inputs to derive other land surface variables, such as soil moisture, evaporation, surface runoff, snow accumulation and snow melt, etc. As a byproduct, this monthly mean surface air temperature data set can also be applied to monitor surface air temperature variations over global land routinely or to verify the performance of model simulation and prediction. Refer to this paper: Fan, Y. and H. van den Dool, 2008: A global monthly land surface air temperature analysis for 1948-present. J. Geophys. Res., 113, doi: 10.1029/2007JD008470.


General Information


Legal Information

This dataset has been created by US Government which means it is required to be in the public domain. However US copyright law only allows open access by US citizens, we have assumed the data is equivalently licensed as CC0 for the rest of the world as this is in the spirit of the US Government’s Open Data policy.
  • The rights statement is at

    http://catalog.data.gov/dataset/climate-prediction-center-cpc-global-land-surface-air-temperature-analysis Do you think this data is incorrect? Let us know

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Practical Information

  • The data appears in this collection

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  • This data changes

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