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HadEX2: Gridded Temperature and Precipitation Climate Extremes Indices (CLIMDEX data)

NCAR Climate Data Guide Image using HadEX2 data.

HadEX2 provides gridded, station-based indices of temperature- and precipitation- related climate extremes. It is intended for climate change detection and attribution studies and climate model evaluation. Twenty-nine indices, including daily maximum and minimum temperatures, number of frost days, maximum 1-day precipitation, and growing season length are provided for 1901 to 2010 at monthly timesteps on a 2.5° latitude x 3.75 ° longitude grid. Definitions of these core indices follow recommendations set forth by the CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETTCCDI). Input data are from approximately 7000 temperature and 11000 precipitation observing stations distributed worldwide.  The indices are computed for each station, and then the indices are gridded using an angular distance weighting scheme. Compared with the precipitation-based indices, the temperature-based indices generally show larger spatial coherence and large-scale averages that are more robust to sampling gaps. 

Key Strengths:

  • Large number of indices provided calculated with standard, intuitive definitions of extremes
  • Most global coverage of the "extremes" datasets, incorporating stations from Europe, Southeast Asia, and Latin America, in addition to GHCN-Daily
  • More quality control and homogenization of stations performed than for GHCNDEX

Key Limitations:

  • Not routinely updated
  • Underlying station data not as accessible as the GHCN-Daily stations

Years of Record

1901/01 to 2010/12
temporal metadataID:

Formats

Timestep

Monthly | Annual

Domain

Global

Spatial Resolution

2.5° latitude x 3.75° longitude

Ocean or Land

Land Only

Missing Data Flag

missing data present

Vertical Levels

Surface Data Set

Input Data

temperature and precipitation data from numerous sources

Earth system components and main variables

Atmosphere, Maximum Air Temperature, Minimum Air Temperature, Land, Freeze/Thaw

Suggested Data Citation

Donat, M. G., et al. (2013), Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset, J. Geophys. Res. Atmos., 118, 2098–2118

Data Access: Please Cite data sources, following the data providers' instructions.

  1. View and Download data (netCDF, ASCII) at CLIMDEX
  2. Hadley Centre direct download of HadEX2 netCDF files

Key Figures

Click the thumbnails to view larger sizes

Thumbnails

Captions
NCAR Climate Data Guide Image using HadEX2 data. Change in the mean compared with changes in extremes: Top panel, JJA mean temperature change in the NOAA MLOST dataset; middle panel - change in daytime high temperatures, TXx, in HadEX2; bottom panel - change in nighttime minimum temperatures, TNx. An increase in nighttime lows is more pronounced than an increase in daytime highs. Credit: NCAR Climate Data Guide (D. Schneider).

Cite this page

National Center for Atmospheric Research Staff (Eds). Last modified 17 Feb 2014. "The Climate Data Guide: HadEX2: Gridded Temperature and Precipitation Climate Extremes Indices (CLIMDEX data)." Retrieved from https://climatedataguide.ucar.edu/climate-data/hadex2-gridded-temperature-and-precipitation-climate-extremes-indices-climdex-data.

Acknowledgement of any material taken from this page is appreciated. On behalf of experts who have contributed data, advice, and/or figures, please cite their work as well.

HadEX2: Gridded Temperature and Precipitation Climate Extremes Indices (CLIMDEX data)

HadEX2 provides gridded, station-based indices of temperature- and precipitation- related climate extremes. It is intended for climate change detection and attribution studies and climate model evaluation. Twenty-nine indices, including daily maximum and minimum temperatures, number of frost days, maximum 1-day precipitation, and growing season length are provided for 1901 to 2010 at monthly timesteps on a 2.5° latitude x 3.75 ° longitude grid. Definitions of these core indices follow recommendations set forth by the CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETTCCDI). Input data are from approximately 7000 temperature and 11000 precipitation observing stations distributed worldwide.  The indices are computed for each station, and then the indices are gridded using an angular distance weighting scheme. Compared with the precipitation-based indices, the temperature-based indices generally show larger spatial coherence and large-scale averages that are more robust to sampling gaps. 

1901-01/2010-12

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