An Overview of the Global Historical Climatology Network-Daily Database

Matthew J. Menne National Climatic Data Center, Asheville, North Carolina

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Imke Durre National Climatic Data Center, Asheville, North Carolina

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Russell S. Vose National Climatic Data Center, Asheville, North Carolina

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Byron E. Gleason National Climatic Data Center, Asheville, North Carolina

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Tamara G. Houston National Climatic Data Center, Asheville, North Carolina

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Abstract

A database is described that has been designed to fulfill the need for daily climate data over global land areas. The dataset, known as Global Historical Climatology Network (GHCN)-Daily, was developed for a wide variety of potential applications, including climate analysis and monitoring studies that require data at a daily time resolution (e.g., assessments of the frequency of heavy rainfall, heat wave duration, etc.). The dataset contains records from over 80 000 stations in 180 countries and territories, and its processing system produces the official archive for U.S. daily data. Variables commonly include maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two-thirds of the stations report precipitation only. Quality assurance checks are routinely applied to the full dataset, but the data are not homogenized to account for artifacts associated with the various eras in reporting practice at any particular station (i.e., for changes in systematic bias).

Daily updates are provided for many of the station records in GHCN-Daily. The dataset is also regularly reconstructed, usually once per week, from its 20+ data source components, ensuring that the dataset is broadly synchronized with its growing list of constituent sources. The daily updates and weekly reprocessed versions of GHCN-Daily are assigned a unique version number, and the most recent dataset version is provided on the GHCN-Daily website for free public access. Each version of the dataset is also archived at the NOAA/National Climatic Data Center in perpetuity for future retrieval.

Corresponding author address: Matthew J. Menne, National Climatic Data Center, 151 Patton Avenue, Asheville, NC 28801. E-mail: matthew.menne@noaa.gov

Abstract

A database is described that has been designed to fulfill the need for daily climate data over global land areas. The dataset, known as Global Historical Climatology Network (GHCN)-Daily, was developed for a wide variety of potential applications, including climate analysis and monitoring studies that require data at a daily time resolution (e.g., assessments of the frequency of heavy rainfall, heat wave duration, etc.). The dataset contains records from over 80 000 stations in 180 countries and territories, and its processing system produces the official archive for U.S. daily data. Variables commonly include maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two-thirds of the stations report precipitation only. Quality assurance checks are routinely applied to the full dataset, but the data are not homogenized to account for artifacts associated with the various eras in reporting practice at any particular station (i.e., for changes in systematic bias).

Daily updates are provided for many of the station records in GHCN-Daily. The dataset is also regularly reconstructed, usually once per week, from its 20+ data source components, ensuring that the dataset is broadly synchronized with its growing list of constituent sources. The daily updates and weekly reprocessed versions of GHCN-Daily are assigned a unique version number, and the most recent dataset version is provided on the GHCN-Daily website for free public access. Each version of the dataset is also archived at the NOAA/National Climatic Data Center in perpetuity for future retrieval.

Corresponding author address: Matthew J. Menne, National Climatic Data Center, 151 Patton Avenue, Asheville, NC 28801. E-mail: matthew.menne@noaa.gov
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  • Alexander, L. V., and Coauthors, 2006: Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res., 111, D05109, doi:10.1029/2005JD006290.

    • Search Google Scholar
    • Export Citation
  • Alexandersson, H., 1986: A homogeneity test applied to precipitation data. Int. J. Climatol., 6, 661675.

  • Caesar, J., Alexander L. , and Vose R. S. , 2006: Large-scale changes in observed daily maximum and minimum temperatures: Creation and analysis of a new gridded data set. J. Geophys. Res., 111, D05101, doi:10.1029/2005JD006280.

    • Search Google Scholar
    • Export Citation
  • Della-Marta, P. M., Haylock M. R. , Luterbacher J. , and Wanner H. , 2007: Doubled length of western European summer heat waves since 1880. J. Geophys. Res., 112, D15103, doi:10.1029/2007JD008510.

    • Search Google Scholar
    • Export Citation
  • Doherty, S. J., and Coauthors, 2009: Lessons learned from IPCC AR4: Scientific developments needed to understand, predict, and respond to climate change. Bull. Amer. Meteor. Soc., 90, 497513.

    • Search Google Scholar
    • Export Citation
  • Dupigny-Giroux, L.-A., Ross T. F. , Elms J. D. , Truesdell R. , and Doty S. R. , 2007: NOAA’s Climate Database Modernization Program: Rescuing, archiving, and digitizing history. Bull. Amer. Meteor. Soc., 88, 10151017.

    • Search Google Scholar
    • Export Citation
  • Durre, I., Menne M. J. , and Vose R. S. , 2008: Strategies for evaluating quality assurance procedures. J. Appl. Meteor. Climatol., 47, 17851791.

    • Search Google Scholar
    • Export Citation
  • Durre, I., Menne M. J. , Gleason B. E. , Houston T. G. , and Vose R. S. , 2010: Robust automated quality control of daily surface observations. J. Appl. Meteor. Climatol., 49, 16151633.

    • Search Google Scholar
    • Export Citation
  • Gleason, B. E., Peterson T. C. , Groisman P. Ya. , Easterling D. R. , Vose R. S. , and Ezell D. S. , 2002: A new global daily temperature and precipitation data set. Preprints, 13th Symp. on Global Change and Climate Variations, Orlando, FL, Amer. Meteor. Soc., P1.16. [Available online at https://ams.confex.com/ams/annual2002/webprogram/Paper27803.html.]

  • GLOBE Task Team, and Coauthors, 1999: The Global Land One-Kilometer Base Elevation (GLOBE) Digital Elevation Model, version 1.0. National Oceanic and Atmospheric Administration National Geophysical Data Centerdigital database. [Available online at http://www.ngdc.noaa.gov/mgg/topo/globe.html.]

  • Guttman, N. B., and Quayle R. G. , 1990: A review of cooperative temperature data validation. J. Atmos. Oceanic Technol., 7, 334339.

  • Hubbard, K. G., Goddard S. , Sorensen W. D. , Wells N. , and Osugi T. T. , 2005: Performance of quality assurance procedures for an applied climate information system. J. Atmos. Oceanic Technol., 22, 105112.

    • Search Google Scholar
    • Export Citation
  • Janis, M. J., 2002: Observation-time-dependent biases and departures for daily minimum and maximum air temperatures. J. Appl. Meteor., 41, 588603.

    • Search Google Scholar
    • Export Citation
  • Jones, P. D., and Coauthors, 1985: A grid point surface air temperature data set for the Northern Hemisphere. U.S. Department of Energy Carbon Dioxide Research Division Tech. Rep. TRO22, 251 pp.

  • Jones, P. D., Raper S. C. B. , Cherry B. S. G. , Goodess C. M. , and Wigley T. M. L. , 1986: A grid point surface air temperature data set for the Southern Hemisphere 1851-1984. U.S. Department of Energy Carbon Dioxide Research Division Tech. Rep. TR027, 73 pp.

  • Karl, T. R., and Coauthors, 1995: Critical issues for long-term climate monitoring. Climatic Change, 31, 185221, doi:10.1007/BF01095146.

    • Search Google Scholar
    • Export Citation
  • Klein Tank, A. M. G., and Coauthors, 2002: Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int. J. Climatol., 22, 14411453.

    • Search Google Scholar
    • Export Citation
  • Kunkel, K. E., Easterling D. R. , Hubbard K. , and Redmond K. , 2004: Temporal variations in frost-free season in the United States: 1895–2000. Geophys. Res. Lett., 31, L03201, doi:10.1029/2003GL018624.

    • Search Google Scholar
    • Export Citation
  • Kunkel, K. E., Easterling D. R. , Redmond K. , Hubbard K. , Andsager K. , Kruk M. , and Spinar M. , 2005: Quality control of pre-1948 cooperative observer network data. J. Atmos. Oceanic Technol., 22, 16911705.

    • Search Google Scholar
    • Export Citation
  • Lawrimore, J. H., Menne M. J. , Gleason B. E. , Williams C. N. , Wuertz D. B. , Vose R. S. , and Rennie J. , 2011: An overview of the Global Historical Climatology Network monthly mean temperature dataset, version 3. J. Geophys. Res., 116, D19121, doi:10.1029/2011JD016187.

    • Search Google Scholar
    • Export Citation
  • Legates, D. R., and Willmott C. J. , 1990a: Mean seasonal and spatial variability in gauge corrected global precipitation. Int. J. Climatol., 10, 111127.

    • Search Google Scholar
    • Export Citation
  • Legates, D. R., and Willmott C. J. , 1990b: Mean seasonal and spatial variability in global surface air temperature. Theor. Appl. Climatol., 41, 1121.

    • Search Google Scholar
    • Export Citation
  • Legates, D. R., and McCabe G. J. Jr., 1999: Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model evaluation. Water Resour. Res., 35, 233241.

    • Search Google Scholar
    • Export Citation
  • Menne, M. J., Williams C. N. Jr., and Vose R. S. , 2009: The U.S. Historical Climatology Network monthly temperature data, version 2. Bull. Amer. Meteor. Soc., 90, 9931007.

    • Search Google Scholar
    • Export Citation
  • Min, S.-K., Zhang X. , Zwiers F. W. , and Hegerl G. C. , 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378381, doi:10.1038/nature09763.

    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., and Vose R. S. , 1997: An overview of the Global Historical Climatology Network temperature database. Bull. Amer. Meteor. Soc., 78, 28372849.

    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., Daan H. , and Jones P. , 1997: Initial selection of a GCOS surface network. Bull. Amer. Meteor. Soc., 78, 21452152.

  • Peterson, T. C., Vose R. S. , Razuvaev V. N. , and Schmoyer R. L. , 1998: Global Historical Climatology Network (GHCN) quality control of monthly temperature data. Int. J. Climatol., 18, 11691179.

    • Search Google Scholar
    • Export Citation
  • Reek, T., Doty S. R. , and Owen T. W. , 1992: A deterministic approach to the validation of historical daily temperature and precipitation data from the Cooperative Network. Bull. Amer. Meteor. Soc., 73, 753765.

    • Search Google Scholar
    • Export Citation
  • Schmidlin, T. W., Wilks D. S. , McKay M. , and Cember R. P. , 1995: Automated quality control procedure for the “water equivalent of snow on the ground” measurement. J. Appl. Meteor., 34, 143151.

    • Search Google Scholar
    • Export Citation
  • Thorne, P. W., and Coauthors, 2011: Guiding the creation of a comprehensive surface temperature resource for twenty-first-century climate science. Bull. Amer. Meteor. Soc., 92, ES40ES47.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., and Coauthors, 2007: Observations: Surface and atmospheric climate change. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 235–336.

  • Vose, R. S., Schmoyer R. L. , Steurer P. M. , Peterson T. C. , Heim R. , Karl T. R. , and Eischeid J. K. , 1992: The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. Oak Ridge National Laboratory Environmental Sciences Division Publ. 3912, 324 pp.

  • WMO, 2003: Manual on the Global Observing System: Volume 1—Global aspects. World Meteorological Organization Document WMO 544, 58 pp.

  • You, J., and Hubbard K. G. , 2006: Quality control of weather data during extreme events. J. Atmos. Oceanic Technol., 23, 184197.

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